May 2024
The roles of vitamin B12, 25(OH)D, and folate in primary nocturnal enuresis: A single center experience
Ahmet Keleş 1, Ahmet Karakeçi 2, Rahmi Onur 3
1 Department of Urology, Faculty of Medicine, Istanbul Medeniyet University, Istanbul, 2 Department of Urology, Faculty of Medicine, Fırat University, Elazığ, 3 Department of Urology, Faculty of Medicine, Marmara University, Istanbul, Turkey
DOI: 10.4328/ACAM.22020 Received: 2023-10-22 Accepted: 2024-01-08 Published Online: 2024-02-15 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):297-300
Corresponding Author: Ahmet Keleş, Department of Urology, Faculty of Medicine, Istanbul Medeniyet University, Prof. Dr. Süleyman Yalçın City Hospital, Fahrettin Kerim Gökay Caddesi, 34720, Istanbul, Turkey. E-mail: drkeles2009@yahoo.com P: +90 505 395 49 37 Corresponding Author ORCID ID: https://orcid.org/0000-0001-5436-1803
This study was approved by the Ethics Committee of Fırat University Faculty of Medicine (Date: 2020-11-12, No: 97132852/050.01.04/)
Aim: In this study, we investigated the connections between children born late preterm (LPT) and their susceptibility to nocturnal enuresis, examining their vitamin B12, folate, iron, and 25(OH)D levels.
Material and Methods: From April 2018 to December 2020, the research group comprised 146 children with PNE who appeared at state hospital urology clinics, whereas the control group included 102 healthy children who presented at the pediatric clinics. Primary nocturnal enuresis was characterized as having more than four wet nights per week in children aged 5 to 13 years. Both groups’ hospital records were compared in terms of age, height, weight, vitamin B12, folate, ferritin, and iron levels.
Results: There was no difference found in demographic characteristics between our study and control groups. In agreement with the literature, the mean vitamin B12, 25(OH)D, and folate levels were significantly lower in the enuresis group than in the control group.
Discussion: The delayed CNS development or the onset of sleep problems may be caused by low levels of vitamin B12, folate, and 25(OH)D in PNE patients. To find out how PNE and folate levels are related, a more extensive series is required.
Keywords: Vitamin B12, 25(OH)D, Folate, Iron, Primary Nocturnal Enuresis
Introduction
Nocturnal enuresis (NE) is a term used to describe involuntary urination during sleep in a child who is five years of age or older and does not have any urogenital malformations or congenital or acquired central nervous system problems [1,2]. Enuresis, in conjunction with daytime voiding situations, is viewed as significant if more bedwetting episodes occur once per month and a minimum frequency of three times per 3 months [3]. It is undeniable that PNE has both psychological and economic effects on children and families. Nevertheless, despite its predominance, its pathogenesis remains unclear.
The pathogenesis of PNE has been linked to a delay in the maturation of the central nervous system. In previous studies, anomalies in arginine vasopressin secretion, bladder dysfunction, and sleep disorders have also been implicated in the development of PNE [4,5]. However, a role for vitamin and mineral nutrition has also been proposed.
Similarly, rodent models have also shown that iron deficiency during pregnancy and lactation alters myelination, neurotransmitters, neurometabolic, and gene/protein profiles before and after iron replenishment at weaning. Infants with iron deficiency anemia (IDA) had lower social-emotional, neurophysiological, cognitive, and motor development test results compared to the control group [6]. Iron, vitamin B12, and folate are vitamins essential for the development of the nervous system. These findings highlight the role of vitamin nutrition in PNE.
Recent evidence suggests that vitamin 25 (OH) D deficiency in children may be a risk factor for nocturnal enuresis [7]. Vitamin D regulates calcium excretion in the proximal tubule by affecting calcium-sensing receptor genes, thus indirectly affecting fluid retention [8]. Some investigators have demonstrated the relationship between nocturia and obstructive sleep apnea [9], which is a consequence of low serum levels of vitamin 25(OH)D in children [10].
No studies in the English literature have evaluated concomitant blood vitamin B12 and 25-hydroxy vitamin D levels in children with PNE, to our best knowledge. Thus, the purpose of this study was to compare vitamin 25(OH)D, vitamin B12, folate, and iron levels in pediatric patients with PNE with those in otherwise healthy pediatric participants.
Material and Methods
Our study used a retrospective cohort approach. After obtaining the ethics committee’s approval for the study, data were gathered from the electric clinical records of the participating government hospital. We searched the health administrative data using the International Classification of Diseases-10 (ICD-10) codes. The integrity of each diagnosis was changed twofold and checked freely by 2 authors who analyzed the medical records and discharge reports. All the findings of the selected patients were deemed appropriate.
Study population
Patients with monosymptomatic NE, aged 5 to 13, who claimed over four wet nights per week and visited the government hospital between April 2018 and December 2020, were included in our study. A total of 248 children were included in this study, out of which 146 children aged between 5 to 13 years and diagnosed with PNE were included. The sample included 52 girls and 94 boys. Additionally, 102 children who did not have any disease and were selected for routine health checks among healthy children in outpatient clinics were also included in the study. These children, comprising 47 girls and 55 boys who did not have enuretic problems, were compared with the other groups to investigate their epidemiological information and clinical outcomes. The control group was randomly chosen according to the strategy of block randomization to create sample groups of equivalent example sizes from the hospital information system. We excluded those with a history of congenital kidney abnormality as well as urinary tract, neurologic abnormalities, any chronic disease, previous urinary tract infection, or a history of glomerular disease.
Examinations
Senior urologists and pediatricians treated all patients. While detailed physical examinations of the children were made and their age, gender, height, and weight values were noted, data such as bowel habits, family history of enuresis, frequency of daytime urine, and several wet nights were obtained from the interviews obtained from the mothers of the children. Blood tests were taken toward the beginning of the day after around 8 hours of fasting. Serum vitamin D levels were evaluated with the 25-hydroxy vitamin D (Monobind, USA) pack. All participants’ serum vitamin B12, vitamin D, folate, ferritin, and iron levels were assessed. Results are displayed using the mean ± standard deviation (SD) and ranges.
Statistic
The statistical program SPSS, version 25.0, was used to analyze the data that had been collected (SPSS Inc., Chicago IL, USA). Paired samples t-test and Mann-Whitney 𝑈 test were utilized for statistical evaluation. For statistical significance, a difference had to be P 0.05.
Ethical Approval
This study was approved by the Ethics Committee of Fırat University Faculty of Medicine (Date: 2020-11-12, No: 97132852/050.01.04/)
Results
Table 1 shows the overall characteristics of the groups. The PNE group had an average age of 9.4 ± 2.79 years, while the control group had an average age of 8.6 ± 2.69 years. Age, gender, bowel habits, body mass index, number of wet nights per week, and urine osmolality did not differ substantially across research groups. There were no variations in biochemically mean hemoglobin, hematocrit, or mean corpuscular volume (MCV) values between the PNE and control groups (P > 0.05; Table 1). Enuresis was present in 83.56% of the parents in the enuresis group, which was considerably higher than in the control group. (P 0.001; Table 1)
The median level of serum 25(OH)D was 26.2 ng/ml. Regardless of seasonality, we discovered a significant difference between the PNE and control groups when vitamin 25(OH)D levels were compared between the two groups (p=0.007; Table 1). Mean 25 (OH) D levels were 24.24 ± 7.95 for PNE and 32.11 ± 11.24 for the control group.
Likewise, mean B12 and folate levels in the enuresis group were considerably lower than in the control group (p=0.001 and p=0.029, respectively) (Table 2). Table 2 provides a statistical comparison of serum ferritin and iron levels between the groups.
Discussion
This investigation led us to the realization that the blood levels of 25(OH)D, B12, and folic acid in children with NE were considerably lower than those in the control group. However, to the best of our knowledge, there is no published research from reliable English sources on the topic of vitamin D, B12, folate, and iron intake among patients with PNE. As a result, this study is the first of its kind.
The International Children’s Continence Society (ICCS) defines primary nocturnal enuresis as a symptom of intermittent incontinence during sleep [2]. Despite studies on this subject, the etiology of enuresis has not been elucidated. This is probably because of its multifactorial etiology. Psychogenic and behavioral components, delayed central nervous system maturation, sleep apnea, environmental effects, and deep sleep are among the most accused pathologies [9-10].
Early detection and treatment of VitB12 deficiency are critical in children and pregnant women to prevent severe anemia and permanent neurological deficiencies. Clinical research has provided strong evidence that enuresis treats developmental delay or maturation lag in central nervous system development [11]. The functional maturation theory states that delayed central nervous system control over the bladder at night is the leading factor in the pathophysiology of nocturnal enuresis [12,13].
While vitamin B12 plays an important role in many neurological events, especially in the development of the central nervous system, its deficiency can cause a wide range of neurological symptoms, from cognitive and behavioral changes to neural tube defects [11]. Similar to vitamin B12, folate is an essential vitamin for the proper development of the central nervous system, especially during early pregnancy, as folate deficiency can cause congenital neural tube defects. Folate deficiency, such as vitamin B12 deficiency, can cause neural pathology, especially cognitive dysfunction and dementia. Evidence for this is a demonstration of behavioral abnormalities in folate-deficient mice [14]. The uncertain etiopathogenesis of enuretic children has led us to measure vitamin B12 and folate levels, as they are effective in the maturation of neurogenic functions. Altunoluk et al. observed that vitamin B12 and Folate levels in the enuresis group were significantly lower than those in the control group in their study evaluating the effectiveness of B12 and folate in the etiology of NE in children [15]. Similar results have been reported by Albayrak et al. [16].
Li et al. discovered in their experimental investigation that mice lacking the vitamin D receptor had significantly higher 24-hour urine volume than the control group [17]. Similarly, a negative correlation has been demonstrated between serum vitamin D levels and nocturnal enuresis [7]. According to Kong et al., a normal quantity of vitamin D decreases renin gene transcription through the cAMP pathway. Polyuria occurs because of vitamin D receptor deficiency through an increase in renin [18]. Rahmani et al. asserted, however, that giving infants nocturnal enuresis vitamin D supplements considerably decreased the number of attacks [19]. Parallel to research in the literature, this study found that vitamin D levels in enuretic children were considerably lower in the control group.
Previous studies have reported that iron deficiency, such as vitamin B12 and folate deficiency, negatively affects neural maturation. In studies on this subject, impaired autonomic balance in favor of parasympathetic activity has been shown in children with iron-deficiency anemia [20]. In animal studies, various disorders have been observed during the development of the central nervous system in patients with gestational iron deficiency [21]. Given these findings, even though it is anticipated that iron deficiency anemia may contribute to the etiology of nocturnal enuresis, similar to the findings of Albayrak et al., blood iron and ferritin levels in children with enuresis were shown to be greater than those in the control group [16].
Another parameter investigated in the etiology of NE is family history. If one of the parents had a positive history, the incidence of NE in children was 44%, while this rate could reach up to 77% in children with a positive history in both parents [22]. Despite these available data, many researchers still believe that PNE is caused by the disruption of maturation of the central nervous system connections involved in bladder control [13].
Overall, while looking at children with NE in clinical practice, the coexistence of vitamin B12 and/or vitamin 25(OH)D deficiency should be followed if the patient has a high frequency of bedwetting.
Strengths and limitations
Our study offers certain key advantages. This is the first investigation, as far as we are aware, on the relationship between concurrent serum 25(OH)D and B12 levels in children with PNE. The study’s weaknesses are the limited sample size, retrospective design, and lack of consideration for climatization and seasonality. We utilized retrospective data from medical clinic records of our study group, social status, time spent under sunlight, parathyroid (PTH) levels, dressing habits, and children’s daily 25-hydroxy vitamin D intake. We have not assessed the long-term results or investigated the daytime urine volume. The inability to evaluate the effect of supplementation in children with low levels of these vitamins on the treatment of PNE can be considered another limiting factor.
Conclusions
Vitamin D, B12, and folate levels were considerably lower in children with PNE than in the control group in our research. We believe that delayed CNS development may be related to the low levels of 25-hydroxyvitamin D, B12, and folate in children with PNE. Large series and controlled trials in which the indicated vitamins will be employed in the treatment of patients with PNE with low vitamin D, B12, and folate levels will shed further light on this problem.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Franco I, von Gontard A, De Gennaro M. International Childrens’s Continence Society. Evaluation and treatment of nonmonosymptomatic nocturnal enuresis: A standardization document from the International Children’s Continence Society. J Pediatr Urol. 2013;9(2):234-243.
2. Austin PF, Bauer SB, Bower W, Chase J, Franco I, Hoebeke P, et al. The standardization of terminology of lower urinary tract function in children and adolescents: update report from the Standardization Committee of the International Children’s Continence Society. J Urol. 2014;191(6):1863-1865.
3. Nishizaki N, Obinata K, Kantake M, Yoshida N, Ohtomo Y, Niijima, et al. Association between the frequency of bedwetting and late preterm birth in children aged ≥5 years. Acta Paediatr. 2019;108(2):282-287.
4. Lei D, Ma J, Du X, Shen G, Tian M, Li G. Altered brain activation during response inhibition in children with primary nocturnal enuresis: An fMRI study. Hum Brain Mapp. 2012;33(12):2913-9.
5. Yu B, Kong F, Peng M, Ma H, Liu N, Guo Q. Assessment of memory/attention impairment in children with primary nocturnal enuresis: A voxel-based morphometry study. Eur J Radiol. 2012;81(12):4119-4122.
6. Thompson J, Biggs BA, Pasricha SR. Effects of daily iron supplementation in 2- to 5-year-old children: Systematic review and meta-analysis. Pediatrics. 2013;131(4):739-753.
7. Su MS, Xu L, Pan WF, Li CC. Current perspectives on the correlation of nocturnal enuresis with obstructive sleep apnea in children. World J Pediatr. 2019;15(2):109-116.
8. Firmenich CS, Elfers K, Wilkens MR, Breves G, Muscher-Banse AS. Modulation of renal calcium and phosphate transporting proteins by dietary nitrogen and/or calcium in young goats. J Anim Sci. 2018;96(8):3208-3220.
9. Leiberman A, Stiller-Timor L, Tarasiuk A, Tal A. The effect of adenotonsillectomy on children suffering from obstructive sleep apnea syndrome (OSAS): The Negev perspective. Int J Pediatr Otorhinolaryngol. 2006;70(10):1675-1682.
10. Mete T, Yalcin Y, Berker D, Ciftci B, Guven SF, Topaloglu O, et al. Obstructive sleep apnea syndrome and its association with vitamin D deficiency. J Endocrinol Invest. 2013;36(9):681-5.
11. Aaron S, Kumar S, Vijayan J, Jacob J, Alexander M, Gnanamuthu C. Clinical and laboratory features and response to treatment in patients presenting with vitamin B12 deficiency-related neurological syndromes. Neurol India. 2005;53(1):55-59.
12. Wang M, Zhang A, Qin Z, Xu S, Ban S, Zhang J, et al. Abnormal neural responses to emotional stimuli in children with primary monosymptomatic nocturnal enuresis. Eur Child Adolesc Psychiatry. 2019;28(7):949-956.
13. Von Gontard A, Schmelzer D, Seifen S, Pukrop R. Central nervous system involvement in nocturnal enuresis: Evidence of general neuromotor delay and specific brainstem dysfunction. J Urol. 2001;166(6):2448-2451.
14. Beaudin AE, Perry CA, Stabler SP, Allen RH, Stover PJ. Maternal Mthfd1 disruption impairs fetal growth but does not cause neural tube defects in mice. Am J Clin Nutr. 2012;95(4):882-891.
15. Yeung CK, Sreedhar B, Sihoe JD, Sit FK, Lau J. Differences in characteristics of nocturnal enuresis between children and adolescents: A critical appraisal from a large epidemiological study. BJU Int. 2006;97(5):1069-1073.
16. Albayrak S, Zengin K, Tanik S, Daar G, Ozdamar MY, Bakirtas H, et al. Vitamin B12, folate and iron levels in primary nocturnal enuresis. Pak J Med Sci. 2015;31(1):87-90.
17. Li YC, Kong J, Wei M, Chen ZF, Liu SQ, Cao LP. 1,25-Dihydroxyvitamin D(3) is a negative endocrine regulator of the renin-angiotensin system. J Clin Invest. 2002;110(2):229-238.
18. Kong J, Zhang Z, Li D, Wong KE, Zhang Y, Szeto FL, Musch MW, Li YC. Loss of vitamin D receptor produces polyuria by increasing thirst. J Am Soc Nephrol. 2008;19(12):2396-405.
19. Dossche L, Walle JV, Van Herzeele C. The pathophysiology of monosymptomatic nocturnal enuresis with special emphasis on the circadian rhythm of renal physiology. Eur J Pediatr. 2016;175(6):747-754.
20. Yokusoglu M, Nevruz O, Baysan O, Uzun M, Demirkol S, Avcu F, et al. The altered autonomic nervous system activity in iron deficiency anemia. Tohoku J Exp Med. 2007;212(4):397-402.
21. Greminger AR, Lee DL, Shrager P, Mayer-Pröschel M. Gestational iron deficiency differentially alters the structure and function of white and gray matter brain regions of developing rats. J Nutr. 2014;144(7):1058-66.
22. Ferrara P, Cammisa I, Zona M, Ottaviani D, Agazzi C, Gatto A. Do sleep disorders influence the prognosis and the tesponse to the therapy in enuretic children?. Urol Res Pract. 2023;49(1):59-62.
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Ahmet Keleş, Ahmet Karakeçi, Rahmi Onur. The roles of vitamin B12, 25(OH)D, and folate in primary nocturnal enuresis: A single center experience. Ann Clin Anal Med 2024;15(5):297-300
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The relationship between CD3+ and CD4+ T lymphocyte ratio and rejection & infection in renal transplantation patients
Eyup Kaplan 1, Erkan Demir 2, Ugur Erken 2
1 Department of Urology, Gaziantep City Hospital, Gaziantep, 2 Department of Urology, Faculty of Medicine, Cukurova University, Adana, Turkey
DOI: 10.4328/ACAM.22037 Received: 2023-11-05 Accepted: 2023-12-25 Published Online: 2024-03-26 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):301-306
Corresponding Author: Eyup Kaplan, Department of Urology, Gaziantep City Hospital, Gaziantep, Turkey. E-mail: dreyup001@hotmail.com P: +90 552 655 27 26 Corresponding Author ORCID ID: https://orcid.org/0009-0001-8635-9852
This study was approved by the Ethics Committee of Çukurova University Faculty of Medicine (Date: 2013-04-04, No: 18/5)
Aim: In our study, we aimed to investigate the changes in T lymphocyte markers the infections seen after renal transplantation and rejection diagnosis and the differential diagnosis.
Material and Methods: A total of 56 patients were enrolled in follow-up after renal transplantation. They were hospitalized due to failure in renal function tests of 31 patients were divided into two groups with clinical and laboratory features of infection and rejection. As the control group who had come to the examination of infection after renal transplantation and rejection were 25 patients without rejection doubt. 10 patients in control group had transplantation from cadaveric donors. In serum samples of patients with T-lymphocyte markers, CD3, CD4, CD8 levels were studied by flowcytometrical methods. Surface markers of T lymphocytes relationship with clinical infection and rejection were investigated
Results: CD3, CD4 and CD8 cells in terms of infection and rejection were not significantly different between the two groups. The cell surface determinants were similar to the groups of infection and rejection of transplant recipients and the control group. However cadaveric donor organ transplant recipients CD3, CD4 and CD8 levels were significantly decreased compared to infection and rejection groups. Lymphocyte markers and WBC lymphocytes ratio in the first and second tracking infection and rejection group when compared to the values, were not statistically different.
Discussion: Renal transplant recipients and especially after induction therapy with ATG measured monitoring the levels of T lymphocytes may provide clinical benefits, in critical cases of infection and rejection may be suggestive.
Keywords: Renal Transplantation, acute rejection, infection, CD3, CD4, CD8.
Introduction
End-stage chronic renal failure (ESRD) is a health problem with high morbidity and mortality, the incidence of which is increasing every year in our country and around the world. Today, three renal replacement therapy models are applied to patients with ESRD. These treatment models are hemodialysis, peritoneal dialysis and renal transplantation, respectively. As of 2013, the number of patients diagnosed with ESRD in Turkey exceeded 70 thousand. While the majority of these patients receive dialysis treatment, only around 2500 – 3000 patients receive renal transplantation annually throughout the country [1].
According to the United States Renal Database System (USRDS) data, when ESRD patients who underwent renal transplantation were compared with patients on the national waiting list receiving dialysis treatment, it was shown that patients who underwent renal transplantation had a 68% lower risk of death after 3 to 4 years of follow-up [2]. Meta-analyses have shown that renal transplantation is the main and most important form of treatment in ESRD patients, with higher quality of life and lower morbidity and mortality rates compared to dialysis treatments [2, 3].
With the influence of the development and diversity of drugs used after renal transplantation, 5-year graft survival rates have reached 95% in living donor transplants and 89% in cadaver transplants. The survival rates of the patients were found to be 95% and 91%, respectively. The main causes of mortality after transplantation are cardiovascular diseases and infection [2-4]. As kidney transplantation becomes more common, the increase in post-transplant problems has led to transplant recipients being considered a “special patient group”. Minimizing the problems that this special patient group may encounter after transplantation should be one of the main goals of transplantation treatment, and the main ways to achieve this are the selection and preparation of patients to be transplanted, post-transplant follow-up, and early diagnosis and intervention of conditions such as rejection/infection [2-4].
Today, there are no markers that will allow us to make a definitive diagnosis of rejection after renal transplantation. A biopsy may still be needed to diagnose rejection. Again, differentiating infection from rejection after renal transplantation is also an important problem. Infection and rejection can sometimes occur together, making this a more complex problem [5, 6]. In this study, we asked, “What is the role of T lymphocyte markers in the diagnosis and differential diagnosis of rejection/infection in patients who have undergone renal transplantation and present to the clinic with infection/rejection findings? Is there an increase or decrease in T lymphocyte subgroups among these clinical conditions?”, “Immunosuppression.” We aimed to find answers to questions such as “What is the difference between the dose and the change in lymphocyte subgroups?”
Material and Methods
This study was approved by the Ethics Committee of Çukurova University Faculty of Medicine (Date: 04/04/2013, No: 18/5). This prospectively planned study included 56 patients who were followed up after renal transplantation by Çukurova University Faculty of Medicine Organ Transplantation Center between January 2010 and March 2014. The patients were informed about the study and an informed signed consent form approved by the Çukurova University Scientific Research Projects Board (project number: TF2013LTP19) was obtained. During the hospitalization period, 3 cc blood samples were taken from these patients into a complete blood count tube with the preliminary diagnosis of infection/rejection. As a control group, 15 patients without any suspicion of rejection/infection, who applied to the Urology outpatient clinic of Çukurova University Faculty of Medicine and came for follow-up after renal transplantation, were included in the study.
Patients admitted to our clinic had fever, tenderness in the transplanted kidney, edema, decreased urine output, weight gain, elevated white blood cells, an increase of 0.3 mg/dl/day or more in serum creatinine, and proteinuria. Renal biopsy was performed in 2 patients and rejection was diagnosed. Since the patients in the other rejection group did not accept biopsy, rejection treatment was given. Renal function tests improved with immunosuppressive therapy.
Clinical findings, urine and blood cultures were used as basis for distinguishing infection/rejection groups. Four of the patients in the infection group had positive urine cultures and four had positive blood cultures, and antibiotics were given in accordance with the culture. Of the patients with urine culture growth, 3 had ESBL (+) Staph Aureus growth and 1 had Strep agalactia growth. Of the patients with blood culture growth, 2 had ESBL (+) Klebsiella pneumonia, 1 had Acinetobacter baumanii, and 1 had Staph Hominis growth. Empiric antibiotic therapy was given to 4 patients whose cultures showed no growth, based on complete urinalysis. Kidney function tests improved with antibiotic treatment. Of the patients with no growth in their cultures and normal urinalysis, 3 had lung infection and 2 had spondylodiscitis.
In the cadaver group, patients who were transplanted from cadavers and used ATG (anti-thymocyte globulin) as immunosuppressant were included.
All patients were monitored daily for physical examination, temperature, pulse, blood pressure, urine amount, complete blood count and blood biochemistry. CD3, CD4, CD8, CD45 levels were taken as the first follow-up, along with a complete blood count before treatment, when the patients were hospitalized. T lymphocyte marker levels, which were checked again at the end of the treatment, were taken as the second follow-up and these parameters were compared.
In the patient and control groups, complete blood count, SDM, CRP, PCT, BUN, creatinine and drug level (Tacrolimus) were studied in the Central laboratory of Çukurova University Faculty of Medicine. CD3, CD4, CD8, CD45 were examined by flow cytometry method in the immunohematology laboratory.
Statistical analysis
SPSS 17.0 package program was used in the statistical analysis of the data. Categorical measurements were summarized as numbers and percentages, and continuous measurements were summarized as mean and standard deviation (median and minimum – maximum where necessary). Chi Square test or Fisher test statistics were used to compare categorical variables. Distributions were checked when comparing continuous measurements between groups. Since the data were not distributed parametrically, the Mann Whitney U test was used in comparisons. The first and second follow-up results of lymphocyte ratios in CD3, CD4, CD8 and WBC were evaluated with the Wilcoxon test. For p < 0.05, the results were considered statistically significant.
Results
The average age of the 56 patients included in the study is 34.8±13.4 years and the range is from the lowest to 7 and the highest to 70. The patients participating in the study were evaluated in four groups: infection group (n = 17), rejection group (n = 14), control group (n = 15) and cadaver group (n = 10). The average age of patients in the infection arm was 34.8±18.7, the average age of patients in the rejection group was 36.6±11.0, the average age of patients in the control group was 32.2±7.9, and the average age of patients in the cadaver group was 37.6±14.2 (Table 1) (p=0.898). The groups were similar in terms of age.
58.8% (33) of all patients were male and 41.2% (23) were female. As for gender distribution of the groups, 52.9% of the patients in the infection arm, 50.0% of the patients in the rejection group, and 80.0% of the patients in the cadaver group were male. In the control group, the rate of male patients was 66.7%. There was no difference between the groups in terms of gender (p = 0.573) (Table 1).
The distribution of lymphocyte ratios in WBC among the groups and the T lymphocyte markers CD3, CD4, CD8 were examined (Table 2). When we examined the CD3 cell values by groups, the CD3 median value of the patients in the infection arm was 74.0 (52.0-93.7), the CD3 median value of the patients in the rejection arm was 83.4 (54.0-94.5), and the CD3 median value of the patients in the control group was 54.2 (34.7-74.7). When the groups were evaluated in terms of CD3, there was no statistical difference between the infection, rejection and healthy control groups. However, the CD3 median value of the cadaver group was statistically significant and lower than the other groups (Table 2).
When we examine CD4 cell values by groups, the median CD4 value of patients in the infection group is 43.5 (21.5-53.3), the median CD4 value of patients in the rejection group is 40.6 (24.0-68.1), and the median CD4 value of patients in the control group is 39.4 (32.6-58.5), and the median CD4 value of the patients in the cadaver group was 29.0 (20.0-38.5). When the groups were evaluated in terms of CD4, there was no statistical difference between the infection, rejection and healthy control groups. However, the CD4 median value of the cadaver group was statistically significantly lower than the other groups (Table 2).
When we examined the CD8 cell values by groups, the CD8 median value of the patients in the infection arm was 35.1 (19.0-59.0), the CD8 median value of the patients in the rejection arm was 38.8 (20.0-63.2), the CD8 median value of the patients in the control group was 45.7 (32.0-58.3), and the median CD8 value of patients in the cadaver group was 38.7 (27.7-48.0). When the groups were evaluated in terms of CD8, it was determined that the only statistical difference was between the infection group and the healthy control group. The CD8 median value of the control group was statistically significantly higher than the infection group (Table 2).
When we examined the lymphocyte ratio in the WBC of the patients according to groups, the median value of the lymphocyte ratio in the WBC of the patients in the infection group was 15.8 (5.6-37.0), the median value of the lymphocyte ratio in the WBC of the patients in the rejection group was 14.5 (1.8-28.0), the median value of the lymphocyte ratio in the WBC of the patients in the control group was 20.6 (13.9-27.8), and the median value of lymphocyte ratio in WBC of patients in the cadaver group was 1.7 (1.0-2.1). When the groups were evaluated in terms of the lymphocyte ratio in WBC, there was no statistical difference between the infection group, the rejection group and the control group. The lymphocyte ratio in WBC of the control group was statistically significantly higher than the rejection group. The median value of lymphocyte ratio in WBC of the cadaver group was statistically significantly lower than the other groups (Table 2).
Patients in the infection group and rejection group in the study were examined in detail. Comorbid conditions, clinical features in the perioperative period, treatments applied and laboratory results were recorded. The two groups were similar in terms of general demographic and clinical information distributions.
Patients in the infection group and rejection group in the study were evaluated in terms of HLA compatibility, height, weight and laboratory parameters. When HLA compatibility was considered, 3/6 tissue compatibility was the most common in all groups. There was no difference between the groups in terms of PRA class 1 and class 2.
The platelet, BUN and creatinine values measured during the first follow-up were statistically different between the groups.
While the platelet median value of the infection group is 316000 (215000-600000), the platelet median value of the rejection group is 213500 (110000-400000). The first follow-up platelet value of the infection group was statistically significantly higher than the rejection group (p = 0.006).
While the median BUN value of the infection group was 13.0 (2.3-51.0), the median BUN value of the rejection group was 37.5 (15-116) (p=0.0001). The first follow-up BUN value of the infection group was statistically significantly lower than the rejection group. While the creatinine median value of the infection group is 1.0 (0.5-3.1), the median creatinine value of the rejection group is 2.2 (0.9-14.0). The first follow-up creatinine value of the infection group was statistically significantly lower than the rejection group (p = 0.004) (Table 3).
The first and second follow-up results of T lymphocyte markers of the patients followed in the study were evaluated according to groups. In the second follow-up, it was possible to measure the values in 8 of 17 patients in the infection group and in 10 of 14 patients in the rejection group. As for the lymphocyte ratios in WBC, it was possible to measure the second follow-up values in 5 of 17 patients in the infection group and in 6 of 14 patients in the rejection group.
When the groups were examined one by one over time, the change in the ratio of CD3, CD4 and CD8 cells and lymphocytes in WBC between the first and second follow-ups was not significant.
When the infection group was compared with the rejection group, there was no statistical difference in the ratio of CD3, CD4, CD8 cells and lymphocytes in WBC at both the first and second follow-up.
The CD4/CD8 ratio was calculated based on the T lymphocyte marker results of the patients followed in the study. The median value of the CD4/CD8 ratio of patients in the infection group was 1.2 (0.4-2.3), the median value of the CD4/CD8 ratio of patients in the rejection group was 1.1 (0.4-2.8), the median value of the CD4/CD8 ratio of patients in the control group was 0.8 (0.6-1.8), and the median value of the CD4/CD8 ratio of patients in the cadaver group was 0.6 (0.5-1.1). There was no statistical difference between the groups in terms of CD4/CD8 ratio (p = 0.151).
In terms of the second follow-up laboratory blood measurement results of the infection and rejection groups, only the BUN values were statistically different as a result of the comparison between the groups in the second measurement. While the median BUN value of the infection group is 16 (9-61), the median BUN value of the rejection group is 37 (21-149). The first follow-up BUN value of the infection group was statistically significantly lower than the rejection group (p = 0.006). The second follow-up measurements were compared with the first follow-up measurements, and the change over time (post-treatment) was examined. However, there was no statistically significant difference.
Discussion
Renal transplantation is currently the main treatment option in the treatment of end-stage renal failure patients, as it does not only prolong life but also improves the quality of life, eliminates the morbidity associated with dialysis treatments, and has a lower cost in the long term [7, 8].
Segundo et al investigated the relationship between the number of T regulatory cells in peripheral blood and graft survival. In the 5-year follow-up of 90 patients who underwent renal transplantation, they observed that graft survival was 6-12 months longer with high T regulatory cell levels (70% and above) [9]. T regulatory cells may play a role in antagonizing the inflammatory state and may be considered a good prognostic factor associated with kidney transplantation.
Peddi et al demonstrated that intermittent thymoglobulin therapy based on peripheral blood CD3 T lymphocyte count is safe and associated with a low rejection rate in kidney transplant recipients. Patients with end-stage renal disease have lower peripheral T and B cell counts than the healthy population. Ultra-low dose Thymoglobulin reduces peripheral lymphocytes in a dose-dependent manner. This dose-dependent approach will help develop optimal treatment strategies in renal transplant recipients [10]. In our study, the median CD3 T lymphocyte value in the group receiving induction therapy with ATG was found to be statistically significantly lower than the other groups. The main goal of induction therapy with ATG is to reduce the risk of acute rejection in the first week after organ transplantation. Indeed, while induction therapy provides a lower rate of acute rejection, it also poses a higher risk for infections and malignancies [11-13]. These complications have been associated with depletion of peripheral T cells due to excessive immunosuppression and low pretransplantation thymus function [14, 15].
Gurkan et al examined the recovery kinetics of T cell subsets following ATG treatment in adults and children. In adults, peripheral CD4+ T cell counts decreased by 85% after treatment with ATG, while recovery of the count began approximately 2 weeks later. After 2 months, an increase of up to 35% of the basal level was observed. On the other hand, when looking at CD8+ T cells, ATG administration only resulted in a 22% reduction. Complete recovery of T lymphocyte numbers takes up to 6 months. It did not detect any change in peripheral CD4 + or CD8 + T lymphocyte numbers in patients who were not given ATG [16]. In our study, the number of CD4+ T lymphocytes was found to be statistically significantly lower in the ATG-administered group compared to the other groups. No statistically significant difference was found in terms of CD4+ T lymphocytes in the infection, rejection and control groups. When the groups were evaluated in terms of CD8+ T lymphocytes, it was determined that the only statistical difference was between the infection group and the control group. It was found that the CD8+ T lymphocyte median value of the control group was statistically significantly higher than the infection group. Based on this finding, we think that the infection developed due to the decrease in cytotoxic CD8+ T lymphocytes in the infection group. In a study conducted by Welzl et al. in CMV seronegative patients, they showed that immunosuppressive treatment did not affect the number of CD8+ T lymphocytes, but there was a moderate increase in the number of CD4+ CD28+ T lymphocytes compared to the control group [17].
Machado et al. found that treatment management based on peripheral CD3 + T lymphocyte count in ATG monitoring after renal transplantation was 45% less drug used and 20% less costly than WBC count [18]. In our study, the decrease in the lymphocyte ratio in WBC and the decrease in the CD3+ T lymphocyte median value in patients given ATG compared to other groups supports this literature.
Ordonez et al. showed that in renal transplant recipients, the risk of acute rejection increased 6-fold with high levels of CD45RC expression on CD8+ T lymphocytes examined before transplantation. By using this biomarker, risk can be determined, the immunosuppressive regimen can be adjusted accordingly and the patient’s quality of life can be improved [19].
Identification of Th9, Th17, Th22 cells increased the number of different subsets of CD4+ T cells. It appears that Th17 cells and Th1 and Th2 cells play an important role in allograft rejection. In clinical and experimental studies conducted in the last 10 years, IL-17 has been shown to have a role in allograft rejection [20].
CD4 lymphopenia (<300/mm3) has been identified as an objective marker of excessive immunosuppression. CD4 lymphopenia has been determined as a risk factor for post-transplant neoplasms (skin cancer and post-transplant lymphoproliferative disorder), opportunistic infections and cardiovascular complications [21]. In another study investigating the number of CD4+ T lymphocytes and the frequency of genitourinary tumors, no significant relationship was found [22].
Berg et al evaluated groups of kidney transplant patients in their 5-year follow-up and showed that there was a relationship between the decrease in the number of CD8 + lymphocytes and their dysfunction. Again, in this study, no significant change was detected in CD4+ T lymphocyte subgroups (memory and regulatory) [23]. In our study, it was observed that the CD8+ T lymphocyte ratio decreased in all other groups compared to the control group. The CD8 median value of the control group was found to be statistically significantly higher than the infection group.
In a study by Torio et al., the measurement of intracellular ATP levels in CD4+ T lymphocytes was evaluated, based on the idea that the intracellular ATP level would increase in activated T lymphocytes. Intracellular ATP levels in kidney transplant patients who developed infection were found to be lower than in the control group and the rejection group. This may explain the increase in opportunistic infections due to immunosuppression. However, no significant difference was found between the rejection group and the healthy population or stable patients [24]. In another study, while intracellular ATP level decreased in case of infection, no significant relationship was found between tacrolimus and cyclosporine levels and intracellular ATP level [25].
To be the reason why the lymphocyte ratio in WBC was found to be significantly lower in the cadaver group compared to other groups. Again, the statistically significant increase in the lymphocyte ratio in WBC of the control group compared to other groups shows the adequacy of immunosuppressive treatment.
Conclusion
Considering the literature, our study is one of the few studies examining T cell subtypes in patients who have undergone renal transplantation in our country. Appropriate parameters are needed to enable early diagnosis and early treatment of acute renal allograft rejection. Monitoring T lymphocyte levels by flow cytometric method during the follow-up of induction therapy with ATG was found to be significant in terms of evaluating the adequacy and effectiveness of treatment. Failure to detect significant differences in the levels of T lymphocyte markers in the differential diagnosis of infection/rejection may be due to the small number of patients. Studies on larger patient groups are needed to clearly determine the clinical importance of T cell subtypes in patients who have undergone renal transplantation and to fully understand their impact on prognosis.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Fidan C, Agirbas I. The effect of renal replacement therapy on health-related quality of life in end-stage renal disease: a meta-analysis. Clin Exp Nephrol. 2023;27(10):829-46.
2. Zahr RS, Ataga KI, Lebensburger JD, Winer JC. Kidney failure outcomes in children and young adults with sickle cell disease in the United States Renal Data System. Pediatr Nephrol. 2023.
3. Rana Magar R, Knight S, Stojanovic J, Marks SD, Lafranca JA, Turner S, et al. Is preemptive kidney transplantation associated with improved outcomes when compared to non-preemptive kidney transplantation in children? a systematic review and meta-analysis. Transpl Int. 2022;35:10315.
4. Robinson AM, Karvellas CJ, Dionne JC, Featherstone R, Sebastianski M, Vandermeer B, et al. Continuous renal replacement therapy and transplant-free survival in acute liver failure: protocol for a systematic review and meta-analysis. Syst Rev. 2020;9(1):143.
5. Lee S, Chih H, Affandi J, Waters S, Irish A, Price P. Markers of terminally differentiated T-cells as predictors of vascular health in renal transplant recipients and healthy adults. Clin Immunol. 2023;255:109760.
6. Mirzakhani M, Shahbazi M, Akbari R, Dedinska I, Nemati E, Mohammadnia-Afrouzi M. Soluble cd30, the immune response, and acute rejection in human kidney transplantation: a systematic review and meta-analysis. Front Immunol. 2020;11:295.
7. Wang TS, Huang KH, Hsueh KC, Chen HA, Tam KW, Sun SH, et al. Efficacy and safety of once-daily prolonged-release tacrolimus versus twice-daily tacrolimus in kidney transplant recipients: A meta-analysis and trial sequential analysis. J Chin Med Assoc. 2023;86(9):842-9.
8. Kanbay M, Ureche C, Copur S, Covic AM, Tanriover C, Esen BH, et al. Kidney transplantation: a possible solution to obstructive sleep apnea in patients with end-stage kidney disease. Sleep Breath. 2023;27(5):1667-75.
9. San Segundo D, Fernandez-Fresnedo G, Rodrigo E, Ruiz JC, Gonzalez M, Gomez-Alamillo C, et al. High regulatory T-cell levels at 1 year posttransplantation predict long-term graft survival among kidney transplant recipients. Transplant Proc. 2012;44(9):2538-41.
10. Tang Q, Leung J, Melli K, Lay K, Chuu EL, Liu W, et al. Altered balance between effector T cells and FOXP3+ HELIOS+ regulatory T cells after thymoglobulin induction in kidney transplant recipients. Transpl Int. 2012;25(12):1257-67.
11. Opelz G, Unterrainer C, Susal C, Dohler B. Efficacy and safety of antibody induction therapy in the current era of kidney transplantation. Nephrol Dial Transplant. 2016;31(10):1730-8.
12. Tang IY, Meier-Kriesche HU, Kaplan B. Immunosuppressive strategies to improve outcomes of kidney transplantation. Semin Nephrol. 2007;27(4):377-92.
13. Eisinger F, Muhlbacher T, Na A, Althaus K, Nadalin S, Birkenfeld AL, et al. Standardized, risk-adapted induction therapy in kidney transplantation. J Nephrol. 2023;36(7):2133-8.
14. Dedeoglu B, Meijers RW, Klepper M, Hesselink DA, Baan CC, Litjens NH, et al. Loss of cd28 on peripheral t cells decreases the risk for early acute rejection after kidney transplantation. Plos One. 2016;11(3):e0150826.
15. Schurmann M, Schurmann D, Schindler R, Meisel C, Liman P, Kruse J, et al. Impaired thymic function and CD4+ T lymphopenia, but not mannose-binding lectin deficiency, are risk factors for Pneumocystis jirovecii pneumonia in kidney transplant recipients. Transpl Immunol. 2013;28(4):159-63.
16. Gurkan S, Luan Y, Dhillon N, Allam SR, Montague T, Bromberg JS, et al. Immune reconstitution following rabbit antithymocyte globulin. Am J Transplant. 2010;10(9):2132-41.
17. Welzl K, Weinberger B, Kronbichler A, Sturm G, Kern G, Mayer G, et al. How immunosuppressive therapy affects T cells from kidney transplanted patients of different age: the role of latent cytomegalovirus infection. Clin Exp Immunol. 2014;176(1):112-9.
18. Machado FP, Vicari AR, Spuldaro F, Castro Filho JBS, Manfro RC. Polyclonal anti T-lymphocyte antibody therapy monitoring in kidney transplant recipients: comparison of CD3+ T cell and total lymphocyte counts. Einstein (Sao Paulo). 2018;16(4):eAO4278.
19. Ordonez-Fernandez L, Rodriguez-Ferreras A, Carriles C, Martinez-Torron A, Lazaro-Lopez E, Rosado-Maria MC. Pneumonia in a patient with kidney transplant treated with alirocumab and everolimus. Farm Hosp. 2019;43(2):74-6.
20. Wen Q, Hang G, Wang Y, Yu Z, Wang H, Chen B. Changes and significance of interleukin 17 expression in patients after renal transplantation. Transplant Proc. 2023;55(3):562-8
21. Suarez JF, Rosa R, Lorio MA, Morris MI, Abbo LM, Simkins J, et al. Pretransplant CD4 Count Influences Immune Reconstitution and Risk of Infectious Complications in Human Immunodeficiency Virus-Infected Kidney Allograft Recipients. Am J Transplant. 2016;16(8):2463-72.
22. Iwami D, Aramaki O, Shinohara N, Niimi M, Shirasugi N. Administration of donor splenocytes via the respiratory tract generates CD8alpha(+) regulatory dendritic cells and induces hyporesponsiveness to fully allogeneic cardiac grafts. Transpl Immunol. 2018;50:60-7.
23. van de Berg PJ, Hoevenaars EC, Yong SL, van Donselaar-van der Pant KA, van Tellingen A, Florquin S, et al. Circulating lymphocyte subsets in different clinical situations after renal transplantation. Immunology. 2012;136(2):198-207.
24. Torio A, Fernandez EJ, Montes-Ares O, Guerra RM, Perez MA, Checa MD. Lack of association of immune cell function test with rejection in kidney transplantation. Transplant Proc. 2011;43(6):2168-70.
25. Sugiyama K, Tsukaguchi M, Toyama A, Satoh H, Saito K, Nakagawa Y, et al. Immune monitoring with a lymphocyte adenosine triphosphate assay in kidney transplant recipients treated with a calcineurin inhibitor. Exp Clin Transplant. 2014;12(3):195-9.
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Eyup Kaplan, Erkan Demir, Ugur Erken. The relationship between CD3+ and CD4+ T lymphocyte ratio and rejection & infection in renal transplantation patients. Ann Clin Anal Med 2024;15(5):301-306
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Evaluation of sleep quality in rheumatoid arthritis patients
Mehmet Siddik Tuncay 1, Ozlem Sahin 2, Murat Semiz 3, Esra Semiz 4, Bulent Alim 2, Halil Peksen 5, Salih Salihoglu 5, Muhammed Fatih Sabuncu 1, Mehmet Salih Kilic 6, Ali Tavasli 7
1 Department of Physical Medicine and Rehabilitation, Liv Hospital, Gaziantep, 2 Department of Physical Medicine and Rehabilitation, Faculty of Medicine, Cumhuriyet University, Sivas, 3 Department of Psychiatry, Faculty of Medicine, Gulhane Military Medical Academy, Ankara, 4 Department of Physical Medicine and Rehabilitation, Halil Şivgin Çubuk State Hospital, Ankara, 5 Department of Physical Medicine and Rehabilitation, Sivas Numune Hospital, Sivas, 6 Department of Internal Medicine, Bossan Hospital, Gaziantep, 7 Department of Forensic Medicine, Branch Office, Gaziantep, Turkey
DOI: 10.4328/ACAM.22050 Received: 2023-11-15 Accepted: 2024-01-01 Published Online: 2024-03-27 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):307-312
Corresponding Author: Mehmet Siddik Tuncay, Department of Physical Medicine and Rehabilitation, Liv Hospital, Gaziantep, Turkey. E-mail: mehmet_s_tuncay@hotmail.com P: +90 541 276 63 49 Corresponding Author ORCID ID: https://orcid.org/0000-0002-8998-6552
This study was approved by the Ethics Committee of Cumhuriyet University (Date: 2013-02-12, No: 2013-02/11)
Aim: The purpose of this study was to evaluate treatment effects on sleep quality and fatigue in patients with RA. Besides, we aim to examine possible effects of disease activity, pain and socio-demographic features on sleep quality and fatigue.
Material and Methods: In this study, 78 patients diagnosed with RA according to the American Rheumatism Association (ACR) 1987 revised criteria and European League Against Rheumatism (EULAR) criteria were compared with a parallel healthy control group (n=48). All participants were given a socio-demographic questionnaire, the Pittsburgh Sleep Quality Index (PSQI), Multidimensional Assessment of Fatigue Scale (MAF), Visual Analog Scale (VAS), Disease Activity Score 28 (DAS28).
Results: The mean duration of diagnosis was 9.10±8.54 years and the mean score of DAS28 was 3.25±1.04 in patients with RA. In terms of total PSQI, the differences between two groups were found statistically significant (p=0.001; t=8.023). In terms of MAF, The differences between two groups were found statistically significant (p=0.001; t=3.668). The sleep disturbance and daytime functioning scores were found as 1.86 ± 0.69, 1.40 ± 0.83 respectively in non-biological DMARD group and 1.54±0.66; 0.84±0.93 in biological + non-biological DMARD group. There were statistically significant differences between groups (p=0.043; t=2.054, p=0.008; t=2.730). According to correlation analysis between DAS28 and disease duration, a positive correlation has been found (r = 0.297; p = 0.008).
Discussion: Patients with RA generally experience more fatigue and have worse sleep quality than healthy individuals. High disease activity can lead to longer sleep latency, reduced daytime functionality, and increased fatigue symptoms.
Keywords: Rheumatoid Arthritis, Pittsburgh Sleep Quality Index, Multidimensional Assessment of Fatigue Scale, Visual Analog Scale, Disease Activity Score-28
Introduction
Rheumatoid arthritis (RA) is a long-term autoimmune condition that causes inflammation, resulting in swollen joints and joint pain [1]. The chronic process of rheumatoid arthritis negatively affects physical, psychological, emotional and social functions from early stage of disease. Moreover, it causes deterioration of life quality among individuals [2]. The current treatment options can neither prevent RA nor treat completely. Therefore, the main purpose in treatment of RA is to minimize negative impact of disease on life by increasing life quality and decreasing disability. For an effective treatment protocol, the relationships between RA, functional status and quality of life must be well established. [3].
Sleep is one of the factors that affect life quality in patients with RA. Insufficient sleep is associated with impaired life quality, increased pain perception and morbidity/mortality in patients [2, 3]. The frequency of sleep disturbance problem ranges from %54 to %70 in patients with RA [4]. Therefore, accurate evaluation of sleep quality in RA has become more important recently [2]. It was observed that sleep fragmentation has caused more problems than sleep stage changes in patients with RA. Thus RA patients have longer duration of sleep latency, they wake up several times during the night, wake up early in the morning and have excessive daytime sleepiness [3, 4]. Although the sleep quality and fatigue have been examined in numerous researches, there are limited published data related to treatment impact on sleep quality and fatigue. Similarly there are also limited published data related to agents used in the treatment and their effects on sleep quality and fatigue [5].
The purpose of this study was to evaluate treatment effects on sleep quality and fatigue in patients with RA. In addition, we aim to examine possible effects of disease activity, pain and socio-demographic features on sleep quality and fatigue.
Material and Methods
The study was conducted at the Department of Physical Medicine and Rehabilitation, Cumhuriyet University, Faculty of Medicine, from March to December 2013. In this study, 78 patients diagnosed with RA according to the American Rheumatism Association (ACR) 1987 revised criteria and European League Against Rheumatism (EULAR) criteria were compared with a parallel healthy control group (n=48). All participants were enrolled in this study after obtaining written informed consent. Exclusion criteria for this study were accompanying psychiatric disorders, administration of psychotropic drugs which may effect on sleep, mental retardation and presence of a chronic systemic disease except RA.
Socio-demographic Questionnaire
This questionnaire includes socio-demographic data such as age, gender, educational state, socio-economical level and marital status of patients and control group.
Pittsburgh Sleep Quality Index (PSQI)
The PSQI is a tool used by patients to self-evaluate their sleep quality. It looks at seven different aspects of sleep, including the individual’s perception of their sleep quality, the time it takes to fall asleep, the duration of sleep, the efficiency of sleep, any disturbances during sleep, the use of sleep medication, and any dysfunction during the day. It also provides a total score for overall sleep quality. Validity and Reliability were performed by Agargün et al. in our country [6].
Multidimensional Assessment of Fatigue Scale (MAF)
The MAF inventory, developed by Belza et all., evaluates fatigue assessment in terms of five dimensions. The dimensions are labeled fatigue severity, frequency, daily function and psychological status. Each items’ outcome scores range from 0 to 10 and maximum score is determined as 50 points. It was explained to patients that higher scores indicates severe fatigue (0= no fatigue, 10= severe fatigue) [7].
Visual Analog Scale (VAS)
The VAS was used to measure of instant pain intensity in patients. The pain scale ratings range from 0 (no pain) to 10 (intolerably severe pain) [8].
Disease Activity Score 28 (DAS28)
The DAS28 was used to evaluate disease activity. Disease Activity Score calculated with the formula [0.56×The number of tender joints (TJ28) + 0.28×The number of swollen joint (SJ28) + 0.014× General Health Assessment (GHA) + 0.70× Erythrocyte Sedimentation Rate (ESR)]. The special type calculator is available to use these calculations. In the obtained results, level of disease activity has been accepted as low (DAS28 ≤ 3.2) and high (DAS28 > 3.2). [9].
Statistical Analysis
SPSS (Statistical Package for the Social Sciences, USA) software was used for analysis of data. Data were expressed as mean, standard deviation and percentage. The initial evaluation and comparison of normally distributed data were done using the Kolmogorov-Smirnov test. The Chi-square test was used for comparisons between multiple groups. The Pearson tests were used to analyze the presence of correlation. Statistical significance was determined by a p value of less than 0.05.
Ethical Approval
This study was approved by clinical ethics committee of Cumhuriyet University (Date: 2013-02-12, No: 2013-02/11).
Results
The research encompassed 78 individuals with RA and a control group of 48 healthy individuals. The average age of the participants in the patient group was found to be 48.08±10.95, while it was 45.70±6.98 in the control group. There were no significant disparities in terms of average age and gender between the patient group and the control group. The patient group in this study consisted of 11 males (14.1%) and 67 females (85.9%), while the control group comprised 11 males (22.9%) and 37 females (77.1%). The average duration of diagnosis for the patients with RA was 9.10±8.54 years, and the average DAS28 score was 3.25±1.04.
The mean of total PSQI in patient group was found to be 8.46±3.9, in control group was 4.04±2.24. There was a statistically significant differences between groups according to total PSQI means (p=0.001; t=8.023). The total mean score of MAF was 28.25±13.43 in the patient group and in the control group was 20.16±11.05. The differences between two groups were found statistically significant (p=0.001; t=3.668). The mean scores of all sub-scales of PSQI were statistically significant among the patient and control groups (Table 1).
Individuals’ sleep quality in this study was evaluated as ‘good sleep quality’ (PSQI ≤ 5) and ‘poor sleep quality’ (PSQI > 5) according to total PSQI score. When evaluated according to whether it is a good or poor sleep quality, statistically significant differences were found between the groups (x2=39.763; p=0.001); In the patient group, 17 of 78 patients (21.8%) had good sleep quality, and 61 (79.2%) patients had poor sleep quality. In the control group, 38 of 48 patients (79.2%) had good sleep quality and 10 (20.8%) had poor sleep quality. Patients were dichotomized as good and bad sleepers, and then compared according to DAS 28. Participants were classified according to DAS28 score as inactive or low disease activity patients (DAS28 score ≤3.2) and active or high disease activity patients (DAS28 score> 3.2). The disease was inactive in 12 (70.6%) of 17 good sleeper patients, active in 5 (29.4%) patients. In addition, disease was inactive in 31 (50.8%) of 61 bad sleeper patients, active in 30 (49.2%) patients. However, the rate of high disease activity in bad sleeper patients was higher than good sleeper patients, and there were no significant differences found between groups (x2=2.100; p=0.147).
The total PSQI score was found as 7.74±3.86 in low disease activity patients and 9.34±3.88 in high disease activity patients. There were no significant differences between the groups (p=0.074; t=1.813). The sleep latency and average of daytime functioning score was found as 1.53±1.00, 0.88±0.82 respectively in low disease activity patients and 2.20±0.96, 1.51±0.91 respectively in high disease activity patients. The difference between the two group was statistically significant (p=0.004; t=2.955, p=0.002; t=3.194 respectively). There was no statistically significant difference observed between the groups in other sleep quality sub-scales. Besides, the mean of MAF score was detected as 23.81±12.79 in low disease activity patients and 20.16±11.05 in high disease activity patients (p=0.001; t=3.459).
The patients were divided into two groups according to treatment. The first group received non-biologic DMARD treatment (n=45), while the second group was treated with a combination of non-biological and biological DMARD (n=33). According to examination results of all Pittsburgh sleep quality parameters, total PSQI score of non-biological DMARD group was found 9:08 ± 3.87. As for the biological + non-biological DMARD group, it was 7.60 ± 3.89. The difference was not statistically significant although lower total PSQI score was obtained from biologically + non-biological group (p=0.100; t=1.665). In the group treated with non-biological DMARDs, the scores for sleep disturbance and daytime functioning were found to be 1.86 ± 0.69 and 1.40 ± 0.83 respectively. In the group treated with both biological and non-biological DMARDs, these scores were 1.54±0.66 and 0.84±0.93 respectively. Statistically significant differences were observed between the groups (p=0.043; t=2.054, p=0.008; t=2.730). The MAF score was also different between the groups, with a score of 30.94±13.91 in the non-biological DMARD group and 24.59±12.01 in the group treated with both biological and non-biological DMARDs, indicating a statistically significant difference (p=0.038; t=2.109) (Table 2).
In terms of all PSQI sub-scales, MAF, VAS and DAS28 values There were no statistically significant differences between anti-TNF treated patients (n=20) and non-TNF treated patients (n=13). In our study, according to correlation analysis between DAS28 and disease duration, a positive correlation was found (r = 0.297; p = 0.008). Positive correlation was observed in all components of sleep quality and disease activity in correlation table (Table 3). There was statistically significant difference between the groups according to MAF scores (p=0.001; t=6.438). The average MAF score in individuals who had good and poor sleep quality was found as 17.87±10, 30.83±12.43 respectively.
Discussion
In present study, effects of treatment on various components of fatigue and sleep quality were examined in RA patients. Total PSQI and also all subgroups of PSQI were found worse in RA patients than healthy controls. When comparing treatment in patients, PSQI sleep disturbance and daytime functionality parameters performed better in patients treated with combination of non-biological and biological DMARD than non-biological DMARD therapy only. Besides, the fatigue scores were found lower in patients who were treated with combination of non-biological and biological DMARD therapy.
A considerable amount of RA patients stated that this disease prevent their sleep with co-occurrence of fatigue [2]. Difficulties in falling asleep, poor sleep quality and restfulness sleep were observed as well. The PSQI, or Pittsburgh Sleep Quality Index, is a tool that individuals can use to self-evaluate their sleep quality and duration. It was originally developed to analyze sleep patterns over a period of one month [10, 11]. Recently sleep quality of RA patients were examined with PSQI inventory [10, 11]. The RA patients had significantly worse sleep quality than healthy control groups according to total PSQI in those published data [10, 11]. Despite few studies with PSQI; influencing factors on sleep quality have not been examined well therefore etiology of sleep remains unclear in RA patients. Ulus et al. evaluated fatigue with MAF inventory in their sleep assessment research with PSQI. MAF scale is found to be useful in RA patients [12]. In this study, the fatigue score was found higher in RA patients than control group. Numerous researches have reported that the fatigue has impact on the subjective sleep quality and total PSQI score in RA patients with poor sleep [10, 11]. Impaired sleep quality and increased fatigue results obtained from our study in RA patients were found to be consistent with related published data. Additionally a positive correlation was found between MAF score and all sub-component of PSQI scale in our study.
Recently, Westhovens et al. [13] found a positive correlation between DAS28 and C-reactive protein levels with PSQI scores, while a negative correlation was observed with the Epworth Sleep Scale in relation to the disease activity of RA patients. A significant body of research has indicated that disease activity is a key factor influencing sleep quality. Furthermore, it has been observed that disease activity can have varying impacts on the seven sub-components of the PSQI [14]. Nicassio et al [14] have reported that DAS28 have no effect on PSQI. Fragia et al. [15] did not find any correlation between decreasing of disease activity and sleep disorders after the tocilizumab treatment. Results of our study showed that disease activity did not significantly affect the total PSQI score. It was affected only sleep latency and daytime functioning parameters. The differences in clinical characteristics of patients or study and patients’ subjective reasons may influence results.
Cytokines and immune functions, which have a regulation effect on sleeping-waking in brain and behavior, could influence the function and activation of patients with arthritis [16]. Specifically, TNF and IL-1 are not only provided biological activation of inflammatory disease but also provide homeostatic regulation in sleep/wake states. Symptoms such as sleep loss, sleepiness, fatigue, poor cognition and enhanced sensitivity to pain may be seen due to injection of exogenous IL1 or TNF [16]. Beneficial effects of DMARDs treatment in RA have been observed on pain, energy and sleep [16]. Positive acute changes with infliximab treatment of RA were reported in night sleep physiology and day sleep [16]. Vgontzas et al [17] applied etanercept, another TNF antagonist, in RA patients with obstructive sleep apnea and improvement in sleep latency moreover decreasing of sleepiness has been observed. The significant improvement was reported in pain, fatigue, sleep, physical and mental functions after 2 years of abatacept treatment in patients with an inadequate response to anti-TNF therapy.
Westhovens et al [13] were reported that sleep quality impaired in patients with uncontrolled treatment. Fatigue scores were decreased in patients with adalimumab treatment in long-term studies. However it was not statistically significant Solak et al [18] found that PSQI and pain scores were numerically lower in RA patients treated with anti-TNF agents. Taylor et al [19] could not detect any differences between Epworth sleepiness scale or PSQI scores, despite improvement in subjective fatigue after anti-TNF therapy and sleep efficiency in polysomnography. In study of Wolfe et al [20] RA patients were compared with FMF and individuals who had not any inflammatory diseases and sleep problems did not decrease even anti-TNF agent treatment. Sarıyıldız et al [21] were compared RA patients according to treatment and treatment did not affect the PSQI in analysis of cross-sectional data.
Our analysis did not reveal a notable enhancement in the overall PSQI scores of patients who received a mix of biological and non-biological DMARDs compared to those who were treated with only non-biological DMARDs. This observation aligns with previously reported studies. In recent studies, biological agent therapy was improved quality of sleep, although there was no significant improvement according to total PSQI in our study. The differences of study methods and patients’ features may cause these results. In contrast to previous research, no significant variations were observed in the impact on sleep quality and fatigue when patients on biologic agents were split into two categories: anti-TNF and non-anti-TNF.
Limitation
There was a limitation in our study. The assessment of sleep was examined with a self-report instrument without polysomnographic measurements. Additionally we held a cross-sectional examination in our study.
Conclusion
To sum up, patients who were treated with a mix of biological and non-biological DMARDs showed better results in the sleep disturbance and daytime functionality aspects of the PSQI compared to those who only received non-biological DMARDs. Additionally, the combined therapy of biological and non-biological DMARDs was found to have a beneficial effect on patient fatigue.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Bartikoski BJ, De Oliveira MS, Do Espirito Santo RC, et al. A review of metabolomic profiling in rheumatoid arthritis: Bringing new insights in disease pathogenesis, treatment and comorbidities. Metabolites. 2022;12(5):1-10.
2. Gouda W, Mokhtar M, Elazab SA, et al. Sleep disorders in patients with rheumatoid arthritis: Association with quality of life, fatigue, depression levels, functional disability, disease duration, and activity: A multicentre cross-sectional study. J Int Med Res. 2023;51(10):1-7.
3. Runge N, Arribas-Romano A, Labie C, et al. The effectiveness of exercise and physical activity programs on fatigue and sleep in people with arthritis – A systematic review with meta-analysis. Sleep Med Rev. 2023;71(8):101-5.
4. Slavich GM, Sacher J. Stress, sex hormones, inflammation, and major depressive disorder: Extending social signal transduction theory of depression to account for sex differences in mood disorders. Psychopharmacology (Berl). 2019;236(10):3063-79.
5. McQueen FM. Imaging in early rheumatoid arthritis. Best Pract Res Clin Rheumatol. 2013;27(4):499-522.
6. Agargun MY, Tekeoglu I, Gunes A, et al. Sleep quality and pain threshold in patients with fibromyalgia. Compr Psychiatry. 1999;40(3):226-8.
7. Gok K, Erol K, Cengiz G, et al. Comparison of level of fatigue and disease correlates in patients with rheumatoid arthritis and systemic sclerosis. Arch Rheumatol. 2018;33(3):316-21.
8. Kim HA, Park SY, Shin K. Implications of persistent pain in patients with rheumatoid arthritis despite remission status: Data from the KOBIO Registry. J Rheum Dis. 2022;29(4):215-22.
9. Bawazir YM. Clinicodemographic Profiles of Rheumatoid Arthritis Patients from a Single Center in Saudi Arabia. Open Access Rheumatol. 2020;12(12):267-75.
10. Chung SW, Hur J, Ha YJ, et al. Impact of sleep quality on clinical features of primary Sjogren’s syndrome. Korean J Intern Med. 2019;34(5):1154-64.
11. Hammam N, Gamal RM, Rashed AM, et al. Fatigue in rheumatoid arthritis patients: Association with sleep quality, mood status, and disease activity. Reumatol Clin (Engl Ed). 2020;16(5):339-44.
12. Ulus Y, Akyol Y, Tander B, et al. Sleep quality in fibromyalgia and rheumatoid arthritis: Associations with pain, fatigue, depression, and disease activity. Clin Exp Rheumatol. 2011;29(Suppl.69):S92-6.
13. Westhovens R, Van der Elst K, Matthys A, et al. Sleep problems in patients with rheumatoid arthritis. J Rheumatol. 2014;41(1):31-40.
14. Nicassio PM, Ormseth SR, Custodio MK, et al. Confirmatory factor analysis of the Pittsburgh Sleep Quality Index in rheumatoid arthritis patients. Behav Sleep Med. 2014;12(1):1-12.
15. Fragiadaki K, Tektonidou MG, Konsta M, et al. Sleep disturbances and interleukin 6 receptor inhibition in rheumatoid arthritis. J Rheumatol. 2012;39(1):60-2.
16. Gu J, Gu W, Lin C, et al. Human umbilical cord mesenchymal stem cells improve the immune-associated inflammatory and prothrombotic state in collagen type-?-induced arthritic rats. Mol Med Rep. 2015;12(5):7463-70.
17. Vgontzas AN, Zoumakis E, Lin HM, et al. Marked decrease in sleepiness in patients with sleep apnea by etanercept, a tumor necrosis factor-alpha antagonist. J Clin Endocrinol Metab. 2004;89(9):4409-13.
18. Solak B, Aydin B, Yuksekal G, et al. Restless legs syndrome in patients with psoriasis: Association with inflammation and sleep quality. Int J Dermatol. 2023;62(4):501-7.
19. Taylor-Gjevre RM, Gjevre JA, Nair BV, et al. Improved Sleep Efficiency after Anti-Tumor Necrosis Factor alpha Therapy in Rheumatoid Arthritis Patients. Ther Adv Musculoskelet Dis. 2011;3(5):227-33.
20. Wolfe F, Rasker JJ, Ten Klooster P, et al. Subjective Cognitive Dysfunction in Patients With and Without Fibromyalgia: Prevalence, Predictors, Correlates, and Consequences. Cureus. 2021;13(12):1-15.
21. Sariyildiz MA, Batmaz I, Bozkurt M, et al. Sleep quality in rheumatoid arthritis: Relationship between the disease severity, depression, functional status and the quality of life. J Clin Med Res. 2014;6(1):44-52.
Download attachments: 10.4328.ACAM.22050
Mehmet Siddik Tuncay, Ozlem Sahin, Murat Semiz, Esra Semiz, Bulent Alim, Halil Peksen, Salih Salihoglu, Muhammed Fatih Sabuncu, Mehmet Salih Kilic, Ali Tavasli. Evaluation of sleep quality in rheumatoid arthritis patients. Ann Clin Anal Med 2024;15(5):307-312
Citations in Google Scholar: Google Scholar
Comparison of two different device results measuring HbA1c by high performance liquid chromatography (HPLC) method
Ahmet Burak Gurpinar 1, Murat Cihan 2, Tevfik Noyan 1, Erhan Seyfi Demirhan 2
1 Department of Medical Biochemistry, Faculty of Medicine, Ordu University, 2 Department of Medical Biochemistry, Ordu University Training and Research Hospital, Ordu, Turkey
DOI: 10.4328/ACAM.22061 Received: 2023-12-01 Accepted: 2024-01-01 Published Online: 2024-03-26 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):313-317
Corresponding Author: Ahmet Burak Gurpinar, Department of Medical Biochemistry, Faculty of Medicine, Ordu University, Ordu, Turkey. E-mail: abgurp@yahoo.com P: +90 505 477 07 50 Corresponding Author ORCID ID: https://orcid.org/0000-0003-3227-4682
This study was approved by the Ethics Committee of Ordu University (Date: 2023-01-20, No: 2023/27)
Aim: HbA1c results, which are routinely measured in HA-8180T and HA-8180V model devices in our laboratory for HbA1c measurement, were divided into three groups based on diabetes mellitus diagnostic criteria with the aim of investigating the compatibility between the two devices at different HbA1c concentrations.
Material and Methods: For HbA1c analysis, the HbA1c values of 260 patients were measured in two devices (Arkray Adams HA-8180T and Arkray Adams HA-8180V) using the ion exchange chromatography method. According to the measured % HbA1c values, 3 groups (1st Group; n=87<5.7%, 2nd Group; n=96 5.7%- 6.4% and 3rd Group; n=77> 6.5%).
Results: Correlation (r=0.994, 95% Confidence Interval (CI) = 0.993-0.996, p<0.0001) of the measurement results obtained between the two devices and Passing-Bablok regression analysis [HA-8180T = 1.0xHA-8180V-0.20] (Slope 95% CI= 1.0-1.0, intercept 95% CI: -0.20-0.20) equation were obtained. According to the regression equation, the linearity between the devices was found to be (cusum test; p=0.90). In the Bland-Altman plot to evaluate the compatibility of the two devices, it was observed that the percentage change between the %HbA1c results obtained with HA-8180-T and the %HbA1c results obtained with HA-8180-V was 3% (95% CI: 2.83 – 3.12) higher on average.
Discussion: Due to the compatibility of the results measured between the two devices in this study, we think that the use of the HA-8180V device, which has a shorter result time, in laboratories with a higher number of tests may be appropriate in terms of reducing the workload.
Keywords: HbA1c, Device Comparison, HPLC, HA-8180 Analyzers
Introduction
Hemoglobin is a metalloprotein found in erythrocytes, containing iron and having oxygen-carrying capacity. In the normal adult human, the hemoglobin molecule (HbA) accounts for about 97% of hemoglobin from two alpha and two beta chains (α2β2). The terms glycated hemoglobin, HbA1c (A1C test, A1C) are common expressions used to describe the glycation product formed by non-enzymatic binding of hemoglobin (Hb) A0 to the N-terminal (1-deoxyfructosyl) valine amino acid glucose [1].
HbA1c indicates an average blood glucose level of 2-3 months and is a marker used not only to guide the diagnosis and treatment of diabetes but also to assess the quality of patient care and predict the risk of developing diabetes complications [2, 3]. The fact that both intra-individual (CVI) and inter-individual (CVG) biological variation of HbA1c is lower than fasting plasma glucose and/or 2-hour plasma glucose (CVI and CVG values for HbA1c and plasma glucose are 1.2% and 5.0% and 4.8% and 8.1%, respectively), does not require pre-test preparation, is not affected by acute stress and has high preanalytic stability makes the HbA1c test advantageous [1-4].
Device changes and changes in measurement methods are quite common in laboratories. Studies show that there may be significant differences between HbA1c levels determined by different methods [4, 5]. Due to the importance of comparable results all over the world, the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) in 1995 and the National Glycohemoglobin Standardization Program (NGSP) in the United States the following year initiated standardization programs for HbA1c measurement. Many different measurement methods have been developed for HbA1c. These methods are based on charge difference (ion exchange chromatography, electrophoresis, capillary electrophoresis, isoelectric focusing) and structural difference (affinity chromatography, immunochemical analyses, enzymatic methods) [6-8]. HPLC (High-Performance Liquid Chromatography) is one of the most common analytical techniques used to measure HbA1C. In HPLC, ion exchange or affinity columns are used to distinguish HbA1C from other hemoglobin molecules [9].
HbA1C ≥ 6.5% or ≥48 mmol/mol measured using a method standardized according to the Diabetes Control and Complications Study (DCCT) and certified by the National Glychemoglobin Standardization Program (NGSSP) is one of the diagnostic criteria for diabetes mellitus according to the American Diabetes Association (ADA) criteria. The HbA1C analysis method used by all laboratories in the United States is required to be calibrated according to the high-performance liquid chromatography (HPLC) method, which is the gold standard for HbA1C [10, 11].
Depending on the technical features of different models of HPLC devices used in routine HbA1c measurements, such as the yield time (column elution time) and the ability to measure in variant mode, the number of tests run in the laboratory and the yield times may vary. In previous studies, method performance comparison studies of HA-8180T and HA-8180V (ADAMS Arkray) model devices belonging to the same manufacturer have been conducted and it has been reported that the compatibility between both devices is quite good [12, 13] . The HA-8180T detects HbA2, HbF, HbA1c (Stable HbA1c, S-A1c), HbS, HbC, HbE, and HbD variants with an analysis time of 210 seconds. The HA-8180V device is a reverse phase cation exchange chromatography device that provides HbA1c and HbF in 48 seconds in fast mode and HbA1c and HbF in 90 seconds in variant mode, as well as HbS, HbC, HbE and HbD detection.
In this study, HbA1c results, which are routinely measured in HA-8180T and HA-8180V model devices in our laboratory and perform HbA1c measurement, were divided into three groups based on diabetes mellitus diagnostic criteria, and the aim was to investigate the compatibility between the two devices at different HbA1c concentrations.
Material and Methods
Whole blood samples of 260 patients who applied to the laboratory of Ordu Training and Research Hospital for HbA1c analysis were taken into K3-EDTA tubes (VacutainerTM Becton-Dickinson, Rutherford, NJ, USA). This study was approved by the Clinical Researchers Ethics Committee of Ordu University (Date: 20.01.2023, No: 2023/27). For HbA1c analysis, the HbA1c values of 260 patients were measured in two devices using the ion exchange chromatography method (Arkray Adams HA-8180T and Arkray Adams HA-8180V, Japan). According to the HbA1c values of the patients, 3 groups (1st group <5.7%, 2nd group 5.7% – 6.4%, and 3rd group> 6.5%) were formed. No variant Hb was observed in any of the patients. Quality control procedures were applied for both devices throughout the study. Two levels (normal and pathological level) of the ICC sample (extendSURE ®) were used daily for internal quality control (ICC). The lot numbers of the controls were the same during the study period for HA-8180T (Lot no: 7125) and HA-8180V (Lot no: 7119).
Statistical Analysis
All statistical analyses were performed with the MedCalc (version 20.009; Ostend, Belgium) statistical package program. The conformity of the variables to the normal distribution was assessed using the Kolmogorov-Smirnov test. Values were given as mean, standard deviation (SD), median, and Q1-Q3. Regression analysis and Bland-Altman compatibility Graph were used to evaluate the compatibility of the results obtained in both devices with each other. The significant difference between the groups was evaluated at the level of p<0.05.
Results
HbA1c values of 260 patients measured in both devices are shown in Table 1. The % HbA1c values of the patient samples measured in both devices according to the groups are shown in Table 2. The correlation between the two devices (r=0.994, 95% Confidence Interval (CI) = 0.993-0.996, p<0.0001) and the equation [HA-8180T = 1.0xHA-8180V-0.20](Slope 95% CI = 1.0-1.0, intercept 95% CI : -0.20-0.20) were obtained in the Passing-Bablok regression analysis of 260 patients (Figure 1). According to the regression equation, the cusum test between the devices was found to be (p=0.90). In the Bland-Altman plot to evaluate the compatibility of the two devices, it was observed that the percentage change between the %HbA1c results obtained with HA-8180-T and the %HbA1c results obtained with HA-8180-V was higher on average by 3% (95% CI: 2.83 – 3.12) (Figure 2).
Discussion
Hemoglobin A1c is the main parameter for monitoring glycemic control in diabetic patients. In 2010, HbA1c was included in the ADA Diabetes Care Standards as a diagnostic criterion. The World Health Organization concluded in 2011 that HbA1c could be used as a diagnostic test [14]. Due to increased standardization, its use as a diagnostic criterion in diabetes is also increasing. Therefore, it is even more important that HbA1c measurement methods have sufficient diagnostic precision and accuracy and are comparable with other methods [15].
For the diagnosis of diabetes and effective treatment follow-up, HbA1c measurement must be reliable, reproducible, and highly accurate. However, results that do not reflect the correct value in HbA1c measurement may be obtained as a result of various factors that may interfere with the measurement, such as hemoglobinopathies, iron deficiency anemia, or vitamin B12 deficiency [16]. Due to the presence of Hb variants, high or low HbA1c results lead to errors in the diagnosis and treatment of diabetes. Identification of Hb variants during or before the HbA1c measurement process requires the selection of an HbA1c measurement method that is not affected by the variant or derivative in question. Thus, it is possible to measure the glycated Hb accurately [17].
Many methods have been developed for HbA1c measurement. These methods assess the charge (ion-exchange chromatography and electrophoresis) and structural difference (boronate affinity chromatography and immunological tests) between glycolyzed and non-glycolyzed hemoglobin species [18]. While there are studies indicating that there is a very good agreement between HPLC and the turbidimetric inhibition immunoassay (TINIA) method, [19, 20] there are also studies indicating that HbA1c values measured by the HPLC method are higher than TINIA [4, 21, 22]. The reason for this height in the HPLC measurement method is the interaction of the HbA1c peak with other contents and abnormal Hb variants. The HPLC (Ion exchange) method is based on the charge of the globin component of Hb. They stated that since abnormal Hb fragments are less positively charged than HbA, similar to glycosylated hemoglobin, their elution together from the column may affect the measurement results [21]. In another study conducted by Kın Tekçe et al., they stated that the HbA1c results obtained with the MQ-2000 PT device using the ion exchange chromatography method for HbA1c measurement were measured on average 0.37 higher than Architect C 8000 using the Tinia method, but this difference was within the limits predicted by NGSP [22]. In another study by Cihan et al., two different NGSP-approved HbA1c measurement methods (HPLC and Tinia) were compared. The HbA1c levels of the patients were measured in three different hospitals as two devices using the HPLC method and a device using the TINIA method. At the end of the study, the mean HbA1c values measured by HPLC methods were found to be relatively higher than TINIA [4].
Similar to our study, in a study conducted by Urrechaga, the correlation between the results of the HA-8180T device and the HA-8180V device in the variant mode was found to be compatible, and the regression equation y=1,000x + 0.0 (Slope 95% CI 1,000-1,000; intercept 95% CI −0.00‐0.00) was obtained [12]. In this study, in which we evaluated the effect of two different models of ARKRAY HPLC devices using the Ion Exchange Chromatography method on HbA1c values, we determined that the devices can be used interchangeably according to the passing-block regression equation [HA-8180T = 1.0xHA-8180V-0.20] (Slope 95% CI= 1.0-1.0, intercept 95% CI: -0.20 – 0.20). In addition, we did not observe any deviation from the linearity according to the equation (Cusum test p=0.90). In another study by Urrechaga, HA-8180T and HA-8190V devices were compared and the regression equation obtained was y= 1.022x -2.34 (Slope 95% CI 1.010-1.029; intercept 95% CI − 2.67-1.77). In the Bland-Altman compatibility graph, the difference in the averages of the devices was stated as 1.2 mmol/mol (0.11%)(13). In our study, in the Bland-Altman graph to evaluate the compatibility of both devices, we found that the HbA1c results obtained with HA-8180T were 3% higher on average (95% CI: 2.83 – 3.12) as a percentage change compared to the HbA1c results obtained with HA-8180V. However, especially in patients with high HbA1c concentration (for Group 3; > 6.5% HbA1c), we observed that the percentage change difference between the measurement results of the devices decreased and the consistency between the results increased.
The difference between the measurement methods should not exceed the level of clinical significance determined by the NGSP. The maximum permissible bias for HbA1c is 1.9% and the desired bias is 1.2% [23] . In this study, in which we compared both devices working with the HPLC method, the HA-8180V device was operated in fast mode with shorter results, and it was observed that there was an average of 3% bias between the devices. Although the HbA1c measurement method by HPLC method is the same for both devices, we think that the average percentage bias between the devices may occur due to the different elution times of the HbA1c fractions and the use of different calibrators of the devices. Since the aim of this study is not to compare the performance of the two devices by performing all the verification steps, the fact that all the verification studies of the devices could not be carried out constitutes the main limitation of our study.
Conclusion
In conclusion, in this study, we found that the HbA1c measurement results performed in the fast mode of the HA-8080V device in patients without hemoglobinopathy fit quite well compared to the HA-8080T device, which gives results in a longer time. We think that it may be appropriate to use the HA-8180V device in laboratories with a high number of tests, as it can reduce the workload of laboratories with a short time to give results.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Little RR, La’ulu SL, Hanson SE, Rohlfing CL, Schmidt RL. Effects of 49 different rare Hb variants on HbA1c measurement in eight methods. J Diabetes Sci Technol. 2015;9(4):849-56.
2. Sacks DB, Bruns DE, Goldstein DE, Maclaren NK, McDonald JM, Parrott M. Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus. Clin Chem. 2002;48(3):436-72.
3. Goldstein DE, Lorenz RA, Malone JJ. Tests of glycemia in diabetes. Diabetes Care. 2000;23(1):80-2.
4. Cihan M, Üner A, Kılınçkaya MF, Noyan T. Comparison of high performance liquid chromatography and turbidimetric inhibition immunoassay methods for measurement of hemoglobin A1c. J Health Sci Med. 2022;5(5):1281-5.
5. Genc S, Omer B, Aycan-Ustyol E, Ince N, Bal F, Gurdol F. Evaluation of turbidimetric inhibition immunoassay (TINIA) and HPLC methods for glycated haemoglobin determination. J Clin Lab Anal. 2012;26(6):481-5.
6. Cohen MP, Witt J, Wu VY. Purified haemoglobin preparations in the evaluation of HbA1c determination by ion exchange chromatography. Ann Clin Biochem. 1993;30:265-71.
7. Marshall SM, Barth JH. Standardization of HbA1c measurements: a consensus statement. Ann Clin Biochem. 2000;37(1):45-6.
8. Kurt İ. Glikozile hemoglobin (HbA1c) ölçümü ve diabetes mellitusun uzun dönem glisemik kontrolünde kullanilmasi. Gulhane Med J. 2003:45(4):387-95.
9. Gupta S, Jain U, Chauhan N. Laboratory diagnosis of HbA1c: a review. J Nanomed Res. 2017;5(4):00120.
10. Association AD. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes—2021. Diabetes Care. 2021;44(1):15-33.
11. Noyan T, Üner A, Cihan M. Interference in the measurement of Hemoglobin A1c: Presence of Hemoglobin D. Türk Klinik Biyokimya Derg. 2022;20(3):132-35.
12. Urrechaga E. Analytical evaluation of the ADAMS(™) A1c HA8180T analyzer for the measurement of HbA1c. J Clin Lab Anal. 2018;32(1):22155.
13. Urrechaga E. Analytical evaluation and quality assessment of the ARKRAY ADAMS A1c HA-8190V for Hb A1c. Scand J Clin Lab Invest. 2023;83(2):136-42.
14. van der Hagen EAE, Leppink S, Bokkers K, Siebelder C, Weykamp CW. Evaluation of the ARKRAY HA-8190V instrument for HbA(1c). Clin Chem Lab Med. 2021;59(5):965-70.
15. Miedema K. Laboratory tests in diagnosis and management of diabetes mellitus. Practical considerations. Clin Chem Lab Med. 2003;41(9):1259-65.
16. Seydel GŞ, Güzelgül F. The effect of hemoglobin variants on high-performance liquid chromatography measurements of glycated hemoglobin. Int J Med of Biochem. 2021;4(1):25-8.
17. Bry L, Chen PC, Sacks DB. Effects of hemoglobin variants and chemically modified derivatives on assays for glycohemoglobin. Clin Chem. 2001;47(2):153-63.
18. John WG, Mosca A, Weykamp C, Goodall I. HbA1c standardisation: history, science and politics. Clin Biochem Rev. 2007;28(4):163-8.
19. Sriwimol W, Choosongsang P, Choosongsang P, Treerut P, Muenniam B, Makkong P, et al. Strong correlation and high comparability of capillary electrophoresis and three different methods for HbA1c measurement in a population without hemoglobinopathy. Scand J Clin Lab Invest. 2020;80(2):139-50.
20. Coskun A, Yavuz Ö, Memisogullari R, Kurt H. HbA1c Ölçümünde HPLC ve Türbidimetrik Immüno-inhibisyon Yöntemlerinin Karsilastirilmasi. Duzce Med J. 2007;9(1):15-9.
21. Ozcelik F, Yiginer O, Serdar M, Kurt I, Öztosun M, Arslan E, et al. Comparison of three methods for measurement of HbA1c. Turkish J Biochem. 2010;35(4):344-9.
22. Tekçe BK, Tekçe H, Aktaş G, Tosun M. HbA1c Ölçümünde Architect C 8000 ile MQ-2000PT Sonuçlarının Karşılaştırılması. JAREM. 2015;5(1):52-5.
23. Ricós C, Fernández-Calle P, Gonzalez-Lao E, Simón M, Díaz-Garzón J, Boned B, et al. Critical appraisal and meta-analysis of biological variation studies on glycosylated albumin, glucose and HbA1c. Adv Lab Med. 2020;1(3):20200029.
Download attachments: 10.4328.ACAM.22061
Ahmet Burak Gurpinar, Murat Cihan, Tevfik Noyan, Erhan Seyfi Demirhan. Comparison of two different device results measuring HbA1c by high performance liquid chromatography (HPLC) method. Ann Clin Anal Med 2024;15(5):313-317
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Predictors of mortality in lung cancer patients hospitalized with community-acquired pneumonia
Kaan Kara 1, Eyyup Cavdar 2
1 Department of Chest Desease, Yedikule Chest Diseases and Chest Surgery Training and Research Hospital, İstanbul, 2 Department of Oncology, Adiyaman Training and Research Hospital, Adiyaman, Turkey
DOI: 10.4328/ACAM.22068 Received: 2023-12-09 Accepted: 2024-01-22 Published Online: 2024-03-29 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):318-323
Corresponding Author: Kaan Kara, Department of Chest Desease, Yedikule Chest Diseases and Chest Surgery Training and Research Hospital, İstanbul, Turkey. E-mail: kaankara3643@yahoo.com P: +90 505 674 09 62 Corresponding Author ORCID ID: https://orcid.org/0000-0001-5896-2497
This study was approved by the Ethics Committee of Yedikule Chest Diseases and Chest Surgery Training and Research Hospital (Date: 2022-08-18, No: 2022-267)
Aim: Lung cancer is a common associated risk factor for pneumonia and increases the severity of pneumonia. In this study, we investigated predictive factors for mortality in patients with lung cancer hospitalized for pneumonia.
Material and Methods: In this retrospective study, 821 patients who were hospitalized between 2013-2018 were included. Clinic pathological patient information and laboratory data were obtained from the hospital archive. Evaluation of predictive factors for mortality was performed by logistic regression analysis and the area under the receiver operating characteristic curve (ROC-AUC).
Results: The 2-day mortality rate was 2.4% and the 30-day mortality rate was 14%. In the multivariate logistic regression analysis, hypotension status (OR=4.18, p=0.004), sodium level (OR=4.30, p=0.007), ALT level (OR=3.83, p=0.027) and calcium level (OR) =6.27, p<0.001) was found to be an independent predictive factor for 2-day mortality. In 30-day mortality analysis, hypotension (OR=1.59, p=0.045), albumin level (OR=0.39, p=0.003), LDH level (OR=2.91, p<0.001), sodium level (OR=1.72, p=0.016), eosinophil counts (OR=0.57, p=0.021) and CURB-65 (OR=2.44, p=0.003) score were independent predictive factors.
Discussion: Hypotension status, serum sodium level, serum ALT level and serum calcium level for 2-day mortality and hypotension status, serum albumin level, serum LDH level, serum sodium level, eosinophil counts, and CURB-65 score for 30-day mortality are potential predictive factors. These predictive factors which can be easily accessible in clinical practice, can be used in the identification of high-risk patients and follow-up of patients.
Keywords: Lung Cancer, Pneumonia, PSI, CURB-65, Mortality
Introduction
According to 2022 data, when skin cancers are excluded, lung cancer is one of the most common types of cancer and the most common cause of cancer-related deaths [1]. Despite the increase in treatment options, its high mortality continues because the vast majority of patients are diagnosed in advanced stage [2]. While the 5-year survival is 60% in early stages, it decreases to 6% in the metastatic stage [1]. Mortality may be directly related to lung cancer or may be due to different etiological reasons resulting from the systemic effects of lung cancer. Infections are one of the major causes of mortality. This is due to the immunosuppression caused by the cancer itself and the potential of the agents used for cancer treatment to weaken the immune system [3].
While pneumonia is the sixth-rate cause of death in the United State of America (USA), it is the first cause of death because of infection. Moreover, it is a disease that can cause high morbidity and increase mortality and health care costs. Most of the pneumonia cases are observed on the ambulatory. While the mortality in these patients is 1-5%, the average mortality is 12% in patients requiring hospitalization and 40% in patients who need intensive care support [4]. It is known that the comorbidities accompanying these patients change the mortality rates.
Lung cancer is one of the risk factors that significantly reduces the survival time of patients [5]. However, studies which involve only lung cancer patients are limited. Existing studies included either a small number of lung cancer patients or only a subgroup analysis of lung cancer analyses reported. In addition, studies have shown that scoring and risk factors such as CURB-65 and PSI, which are used to evaluate risky groups in community-acquired pneumonia, may be insufficient in patients with lung cancer, and that new scales and risk factor analysis are needed [6].
In this study, we investigated the predictive factors for mortality in the patients diagnosed with lung cancer and hospitalized for pneumonia in a pulmonology center. In this way, we aimed to identify risky groups and to find predictors that can help clinicians during treatment and patient monitoring.
Material and Methods
Study population
The study was designed as a single center and retrospective cohort analysis. Lung cancer patients, who were hospitalized and treated between January 2013-december 2018 in the pulmonary diseases service for community acquired pneumonia (CAP), were included.
The inclusion criteria of patients are:
1- Having pathologically confirmed diagnosis of lung cancer
2- To be over 18 years old.
3- Getting CAP diagnosis by a chest disease specialist
Those who were thought to have hospital-acquired pneumonia, those with history of brain metastases, those with a history of previous or concurrent secondary malignancies, those with missing clinical pathological data, those who were referred to the intensive care unit and those who were referred to a different hospital were excluded from the study.
Our hospital is one of the biggest pulmonology reference center in Turkey, and the definition of CAP and CAP treatment are carried out in accordance with national and international guidelines, especially ERS (European Respiratory Society) and ATS (American Thoracic Society). Patients included in the study were followed up and treated in accordance with the guidelines [7].
Data Collection
Patients’ demographic information, comorbidities, the first day of hospitalization examination’s vital findings (including fever, respiratory rate, blood pressure, oxygen saturation at rest, heart rate), clinicopathological features, pneumonia severity scores and serum laboratory parameters measured before hospitalization were recorded from the hospital archive. The most widely used validations were used for PSI and CURB-65 scoring, the original version was preserved and saved from the hospital archive [8].
In hypotension categorization, systolic blood pressure was used <100mmHg, but in CURB-65 and PSI scoring, systolic blood pressure <90mmHg and/or diastolic blood pressure ≤60mm/Hg was accepted in accordance with the original versions. As in previous studies, the severity index of pneumonia for CURB-65 ≥2 and PSI ≥4 points were accepted as severe disease and this categorization was used in analyzes.
Statistical Analysis
Statistical analyzes were performed by using SPSS Statistic software 24 (SPSS Inc., Chicago, III). Continuous variables were summarised as median and categorical variables as number and percentages. Normal distribution was evaluated by Kolmogorov-Smirnov test. The Mann-Whitney U test and Chi square (χ²) test were used in 2-day (early mortality) and 30-day (a month) mortality’s dependent factor analysis. Univariate and multivariate logistic regression analyzes were used to identify predictive factors for mortality. Variables with significant differences between the survivors and non-survivor’s groups were included in the logistic regression analysis. All continuous variables were categorized according to clinically used thresholds [9]. Odds Ratio (OR) was reported with the corresponding 95% confidence intervals (95% CI). The calibration of the models was evaluated using the Hosmer-Lemeshow goodness-of-fit test. The receiver operating characteristic curve (ROC curve) and the area under the ROC curve (ROC-AUC) were calculated to compare the independent prognostic factors. Statistical significance was accepted as p< 0.05.
Ethical Approval
This study was approved by the Ethics Committee of Yedikule Chest Diseases and Chest Surgery Training and Research Hospital (Date: 2022-08-18, No: 2022-267).
Results
Patient Characteristics
Total 821 patients who were suitable for the inclusion criteria were included in the study. The median age of patients was 65 (range:18-93) and 604 (73.6%) were male. 666 (81.1%) patients had non-small cell lung cancer histology. 751 (91.5%) patients were in the metastatic stage and most of them those included were patients receiving chemotherapy by oncology doctors. CURB-65 score of 70.3% and PSI score of 96.1% of patients were compatible with severe disease. (Table-1).
123 (15%) patients died during follow–up after hospitalization. While the 2-day mortality of the patients was determined as 2.4%, the 30-day mortality was determined as 14%.
Early Mortality (2-Days)
In our analysis of factors associated with early mortality hypotension status, albumin, Lactate dehydrogenase (LDH), sodium, aspartate transaminase (AST), alanine transaminase (ALT), calcium, neutrophil count, thrombocyte count, red cell distribution width (RDW), C Reactive protein (CRP), procalcitonin, and arterial blood gas pH levels were found as associated factors for 2-day mortality (p=0.014, p=0.001, p=0.004, p=0.002, p=0.002, p=0.006, p=0.003, p=0.047, p=0.037, p=0.001, p=0.007, p=0.017, and p=0.021, respectively) (Table 1).
To determine factors predicting 2-day mortality, univariate regression analysis was performed on the factors that had a statistically significant relationship with 2-day mortality. Hypotension, sodium, AST, ALT and calcium showed predictive feature (p=0.019, p=0.003, p=0.007, p<0.001, and p<0.001, respectively) (Table-2). A multivariate model was established to accurately assess the predictive factors for 2-day mortality with parameters found to be significant. Hypotension (OR=4.18, 95% CI: 1.56–11.23, p=0.004), low serum sodium (OR=4.30, 95% CI: 1.49–12.45, p=0.007), high serum ALT (OR=3.83, 95% CI: 1.16–12.62, p=0.027) and low serum calcium (OR=6.27, 95% CI: 2.41–16.28, p<0.001) found to be predictive factors associated with higher mortality. (Table-3). Hosmer-Lemeshow test showed that the model was well calibrated (p=0.764).
The 2-day mortality rate of the independent predictive factors was 4.1% in hypotension, 1.4% in non-hypotension, 4.6% in hyponatremia, 1% in non-hyponatremia, 6.7% in patients with high ALT level, 1.4% in patients with non-high ALT level, 7.4% in patients with hypocalcemia, and 1.3% in patients with non-hypocalcemia, respectively.
30-Day Mortality
Diabetes mellitus (DM), hypertension(HT), hypotension examination finding, albumin, protein, LDH, sodium, AST, calcium, total bilirubin, hemoglobin, neutrophil count, lymphocyte count, thrombocyte count, eosinophil count, RDW, CRP, procalcitonin level and CURB-65 score were found factors associated with 30 days mortality in this analysis (p=0.031, p=0.040, p=0.009, p<0.001, p<0.001, p<0.001, p=0.010, p=0.001, p=0.011, p=0.003, p=0.002, p<0.001, p=0.004, p=0.015, p=0.001, p<0.001, p<0.001, p=0.002, and p<0.001, respectively) (Table-1).
Factors which have statistically significant relationship with 30-day mortality were evaluated with univariate regression analysis in order to determine the factors predicting 30- day mortality. DM, HT, sign of hypotension, albumin, protein, LDH, sodium, AST, calcium, total bilirubin, hemoglobin count, eosinophil count, RDW, CRP, and CURB-65 score were found predictive ( p=0.041, p=0.045, p=0.010, p<0.001, p<0.001, p<0.001, p=0.002, p=0.007, p=0.001, p=0.004, p=0.018, p=0.001, p=0.004, p=0.033, and p=0.001, respectively) (Table-2).
In multivariate model established with predictors in univariate analysis, hypotension (OR=1.59, 95% CI: 1.01–2.49, p=0.045), low serum albumin (OR=0.39, 95% CI: 0.21–0.72, p=0.003), high serum LDH (OR=2.91, 95% CI: 1.82–4.63, p<0.001), hypontaremia (OR=1.72, 95% CI: 1.11–2.66, p=0.016), eosinopenia (OR=0.57, 95% CI: 0.35–0.92, p=0.021) and high CURB-65 score (OR=2.44, 95% CI: 1.37–4.34, p=0.003) showed independent predictive feature for 30 days mortality. (Table-3). The Hosmer-Lemeshow test confirmed the model (p=0.639). The 30-day mortality rate of the independent predictive factors were 18% in hypotension, 11.5% in non-hypotension, 18.4% in hypoalbuminemia, 5.7% in non-hypoalbuminemia, 21.2% in high serum LDH, 7.5% in non-high LDH levels, 18.6% in hyponatremia, 11% in non-hyponatremia, 17.4% in patients with eosinopenia, and 9% in patients with non-eosinopenia. Additionaly, the 30-day mortality rate was 16.8% for those with a CURB-65 score at high risk and 7.4% for those without a high risk.
Predictive performance of independent predictors
The comparison of independent predictive factors was evaluated with ROC-AUC analysis. Firstly, ROC-AUC curves were performed for factors predicting 2-day mortality. ROC-AUC value of hypotension status, serum sodium levels, serum ALT levels, and serum calcium levels were found to be 0.635 (95% CI: 0.51–0.76, p=0.039), 0.703 (95% CI: 0.61–0.79, p= 0.002), 0.680 (95% CI: 0.54–0.82, p= 0.006), and 0.696 (95% CI: 0.56–0.83, p= 0.003), respectively. And then ROC-AUC curves were performed for the evaluation of factors predicting 30-day mortality. ROC-AUC value of hypotension status, serum albumin levels, serum LDH levels, serum sodium levels, eosinophil count, and CURB-65 score were found to be 0.564 (95% CI: 0.51–0.62, p=0.028), 0.712 (95% CI: 0.66–0.76, p<0.001), 0.694 (95% CI: 0.64–0.75, p<0.001), 0.575 (95% CI: 0.52–0.64, p=0.010), 0.592 (95% CI: 0.54–0.65, p=0.002), and 0.741 (95% CI: 0.69–0.80, p<0.001), respectively (Figure).
Discussion
In this retrospective study, the prevalence and predictors of 2-day and 30-day mortality are evaluated with lung cancer patients hospitalized for pneumonia in a comprehensive pulmonology center in Turkey. In our study, 2-day mortality was 2.4% and 30-day mortality was 14%. Multivariate regression analysis showed that four variables were associated with 2-day mortality and six variables, including CURB-65, were associated with 30-day mortality, suggesting that these values have an important value in predicting mortality.
It is known that PSI and CURB-65 reveal predictive features for non-cancer patients with CAP [10]. However, in studies including cancer patients, there is no consensus for PSI and CURB-65. Aliberti et al. analyzed PSI and CURB-65’s predictive feature in a large cohort study consisting of 2621 patients, 280 of whom had cancer. He reported that both scorings were not associated with mortality in cancer patients [11]. CURB-65 and PSI were not found to be predictive for CAP in a study established in a cancer center in Korea [12]. A study of Gonzales at al. that only included cancer patients, CURB-65 and PSI were found to be poor predictive for mortality [6]. In our study, while PSI was not revealed as predictive for mortality, CURB-65 was revealed an independent predictive factor for 30-day mortality. Moreover, we found that CURB-65 is one of the most important predictors in our ROC-AUC analysis which we compared with other predictive factors. These differences between the studies that are included cancer patients can be caused by being different types of cancer patients, having different anti-cancer treatment or having different locations of metastasis. In addition, the superiority of CUBR 65 to PSI is an acceptable result in our study. Because in our study, which consisted of all hospitalized patients, almost all patients got into high-risk group in this scoring because of giving additional points to malignancies in the PSI scoring system, and this situation affects the results.
In current studies, it has been reported that eosinophils play a defensive role against bacteria [13]. And also eosinopenia has been identified as an early predictor of sepsis and mortality [14, 15]. In our study eosinopenia was found as a poor predictor for 30 days mortality. Cancer and pneumonia are systemic diseases that can affect many organ systems. Their partnership can affect many other laboratory parameters besides eosinophilia. It is known from previous studies that LDH and albumin levels predicted 1- month mortality for CAP [16, 17]. In studies conducted on patients with CAP, Nair et al. hyponatremia, Ferreira et al. hypocalcemia has been shown to be poor predictive factors of survival in patients with CAP [18, 19].” Also in our study albumin, LHD and sodium levels were found compatibly as independent predictive for, 30-day mortality.
The first 48 hours are vital for CAP patients [7, 20]. Because starting antibiotic therapy for critical and high-risk patients in this time and invasive / non-invasive procedures are important for survival and in previous studies, this time period has been described as critical for patients [21]. According to the methodology of our study, all patients were hospitalized and given appropriate antibiotics. Necessary clinical interventions were applied to all patients. So, predictive factor analyses are needed to prevent death of hospitalized patients. For this purpose, we analyzed early mortality in our study. Hypotension, which is also included in the definition of shock, is a result expected to predict early mortality, and in our analysis, we found that it is one of the predictors of mortality, similar to the literature. On the other hand, it is known from previous studies that other independent predictors hyponatremia and liver function disorders are related with long-term mortality both for cancer patients and pneumonia [22]. And also in our study, hypocalcemia was found as a predictive factor for early mortality. There are many studies investigating hypercalcemia in cancer patients. However, studies of hypocalcemia are limited [23, 24]. Pneumonia and cancer can cause hypocalcemia in different ways [24]. In the case of hypocalcemia, its clinical manifestation may reach life- threatening levels. Early treatment is a must. Although it is a rare incidence, hypocalcemia’s being detected as predictive in our study may be related with denosumab and bisphosphonate, which are among options of treatment of cancer, gaining importance and increasingly used in recent years. Because these treatments are frequently used in the treatment of paraneoplastic syndromes and/or direct bone metastases in lung cancer patients and one of their most important adverse events is hypocalcemia [25].
Limitations
Our study has some limitations. First, it is retrospective and has a single center design. Second, disease severity scoring could not be done prospectively. Third, although patients were selected carefully, various conditions can affect laboratory markers. Fourth, although microbial factors in the etiology of CAP have similar treatment, survival and laboratory effect, they can show different features. Analysis for the etiological factor could not be performed in this study. Finally, previous studies were often done on patients whose immune system was not suppressed. This situation makes difficult to compare with the articles in the literature. Moreover, it is important that our study is the highest numbered predictive analysis and included comprehensive analysis, study on inpatient pneumonia patients, including only lung cancer patients.
Conclusion
In conclusion, in our comprehensive study with a large patient population, including only lung cancer patients, we found that hypotension, serum albumin level, serum LDH level and serum sodium level, eosinophil count and CURB-65 scoring are potentially predictive factors for 30-day mortality. These predictive factors, which are easily accessible in clinical practice, can be used in disease follow-up and in identifying high-risk patients. Moreover, these predictive factors can lead to further studies for potential therapeutic targets. Multicenter and prospective studies are needed to generalize the results.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin. 2022;72(1):7-33.
2. Youlden DR, Cramb SM, Baade PD. The international epidemiology of lung cancer: Geographical distribution and secular trends. J Thorac Oncol. 2008;3(8):819-31.
3. Murphy SL, Xu J. Kochanek KD. 2012. U.S. Department of health and human services, and national vital statistics reports deaths: Preliminary data for 2010. National Vital Statistics Reports. 2012;60(4):1-52.
4. Mandell LA, Wunderink RG, Anzueto A, Bartlett JG, Campbell GD, Dean NC, et al. Infectious diseases society of America; American thoracic society. Infectious Diseases Society of America/American Thoracic Society consensus guidelines on the management of community-acquired pneumonia in adults. Clin Infect Dis. 2007;44(2):27-72.
5. Perlin E, Bang KM, Shah A, Hursey PD, Whittingham WL, Hashmi K, et al. The impact of pulmonary infections on the survival of lung cancer patients. Cancer. 1990;66(3):593-6.
6. Gonzalez C, Johnson T, Rolston K, Merriman K, Warneke C, Ewans S. Predicting pneumonia mortality using CURB-65, PSI, and patient characteristics in patients presenting to the emergency department of a comprehensive cancer center. Cancer Med. 2014;3(4):962-70.
7. Metlay JP, Waterer GW, Long AC, Anzueto A, Brozek J, Crothers K, et al. Diagnosis and treatment of adults with community-acquired pneumonia. An official clinical practice guideline of the american thoracic society and infectious diseases society of America. Am J Respir Crit Care Med. 2019;200(7):45-67.
8. Lim WS, van der Eerden MM, Laing R, Boersma WG, Karalus N, Town GI, et al. Defining community acquired pneumonia severity on presentation to hospital: An international derivation and validation study. Thorax. 2003;58(5):377-82.
9. Svaton M, Blazek J, Krakorova G, Buresova M, Teufelova Z, Vodicka J, et al. Laboratory parameters are possible prognostic markers in patients with advanced-stage NSCLC Treated with Bevacizumab plus Chemotherapy. J Cancer. 2021;12(19):5753-9.
10. Alavi-Moghaddam M, Bakhshi H, Rezaei B, Khashayar P. Pneumonia severity index compared to CURB-65 in predicting the outcome of community acquired pneumonia among patients referred to an Iranian emergency department: A prospective survey. Braz J Infect Dis. 2013;17(2):179-83.
11. Aliberti S, Brock GN, Peyrani P, Blasi F, Ramirez JA; Community-acquired pneumonia organization. The pneumonia severity index and the CRB-65 in cancer patients with community-acquired pneumonia. Int J Tuberc Lung Dis. 2009;13(12):1550-6.
12. Jeong BH, Koh WJ, Yoo H, Um SW, Suh GY, Chung MP, et al. Performances of prognostic scoring systems in patients with healthcare-associated pneumonia. Clin Infect Dis. 2013;56(5):625-32.
13. Ramirez GA, Yacoub MR, Ripa M, Mannina D, Cariddi A, Saporiti N, et al. Eosinophils from physiology to disease: A comprehensive review. Biomed Res Int. 2018;2018:9095275.
14. Lin Y, Rong J, Zhang Z. Silent existence of eosinopenia in sepsis: A systematic review and meta-analysis. BMC Infect Dis. 2021;21(1):471.
15. Mao Y, Qian Y, Sun X, Li N, Huang H. Eosinopenia predicting long-term mortality in hospitalized acute exacerbation of COPD patients with community-acquired pneumonia-a retrospective analysis. Int J Chron Obstruct Pulmon Dis. 2021;16:3551-9.
16. Liu JL, Xu F, Zhou H, Wu XJ, Shi LX, Lu R, et al. Corrigendum: Expanded CURB-65: A new score system predicts severity of community-acquired pneumonia with superior efficiency. Sci Rep. 2018;8:47005.
17. Viasus D, Garcia-Vidal C, Simonetti A, Manresa F, Dorca J, Gudiol F, et al. Prognostic value of serum albumin levels in hospitalized adults with community-acquired pneumonia. J Infect. 2013;66(5):415-23.
18. Nair V, Niederman MS, Masani N, Fishbane S. Hyponatremia in community-acquired pneumonia. Am J Nephrol. 2007;27(2):184-90.
19. Ferreira GF, Palma LC, Amaral ACKB, Brauer L, Nery B, Park M, et al. “What is the prevalence and clinical relevance of hypocalcemia in sepsis?” Critical Care. 2003;7(3):17.
20. Garcia-Vidal C, Fernández-Sabé N, Carratalà J, Díaz V, Verdaguer R, Dorca J, et al. Early mortality in patients with community-acquired pneumonia: causes and risk factors. Eur Respir J. 2008;32(3):733-9.
21. Rosón B, Carratalà J, Fernández-Sabé N, Tubau F, Manresa F, Gudiol F, et al. Causes and factors associated with early failure in hospitalized patients with community-acquired pneumonia. Arch Intern Med. 2004;164(5):502-8.
22. Albhaisi S, Qayyum R. The association between serum liver enzymes and cancer mortality. Clin Exp Med. 2022;22(1):75-81.
23. Zagzag J, Hu MI, Fisher SB, Perrier ND. Hypercalcemia and cancer: Differential diagnosis and treatment. CA Cancer J Clin. 2018;68(5):377-86.
24. Ferraz Gonçalves JA, Costa T, Rema J, Pinto C, Magalhães M, Esparança A, et al. Hypocalcemia in cancer patients: An exploratory study. Porto Biomed J. 2019;4(4):45.
25. Menshawy A, Mattar O, Abdulkarim A, Kasem S, Nasreldin N, Menshawy E, et al. Denosumab versus bisphosphonates in patients with advanced cancers-related bone metastasis: Systematic review and meta-analysis of randomized controlled trials. Support Care Cancer. 2018;26(4):1029-38.
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The effect of regional and general anaesthesia on cerebral oxygenation in shoulder arthroscopy
Arzu Acikel 1, Ismet Topcu 1, Tulun Ozturk 1, Gonul Tezcan Keles 1, Tackin Ozalp 2
1 Department of Anaesthesiology and Reanimation, 2 Department of Orthopaedics and Traumatology, Faculty of Medicine, Manisa Celal Bayar University, Manisa, Turkey
DOI: 10.4328/ACAM.22076 Received: 2023-12-22 Accepted: 2024-02-12 Published Online: 2024-03-28 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):324-328
Corresponding Author: Arzu Acikel, Department of Anaesthesiology and Reanimation, Faculty of Medicine, Manisa Celal Bayar University, Manisa, Turkey. E-mail: arzuacikel@yahoo.com P: +90 537 208 34 08 Corresponding Author ORCID ID: https://orcid.org/0000-0002-6246-9731
This study was approved by the Ethics Committee of Manisa Celal Bayar University, Faculty of Medicine (Date: 2015-03-05, No: 20478486-112)
Aim: Shoulder arthroscopy in the beach-chair position can negatively affect cerebral perfusion and oxygenation, and thus, neurocognitive function. In this study, we aimed to compare the effects of general and regional anaesthesia (GA and RA, respectively) on cerebral oxygenation in patients undergoing shoulder arthroscopy in the beach-chair position.
Material and Methods: This prospective, randomized study included 60 patients who underwent shoulder arthroscopy in the beach-chair position. Patients were divided into two groups: (1) GA (n = 30), and (2) RA using an interscalene brachial plexus block (ISB; n = 30). All patients were laid supine prior to GA or ISB (T0), and after induction of GA or ISB (T1). Next, patients were placed in the beach-chair position. The right and left cerebral oxygen saturation (NIRS-R, NIRS-L, respectively), peripheral oxygen saturation (SpO2), heart rate (HR), and mean arterial pressure (MAP) values were recorded at T0 and T1, as well as 5 (T2), 10 (T3), 20 (T4), and 30 minutes (T5) after patients were placed in the beach-chair position.
Results: Patient’s clinical characteristics, initial laboratory findings, and perioperative data were similar in both groups. Compared to T0, MAP was significantly lower at T1, T2, T3, and T4 in the GA group. Tukey’s HSD test indicated p<0.05, p<0.0001, p<0.0001, and p<0.001, respectively. Although NIRS-R and NIRS-L values fluctuated substantially, there were no differences between groups at any of the pre-defined time points.
Discussion: ISB in the beach-chair position may better preserve cerebral oxygenation compared to GA.
Keywords: Beach Chair Position, Cerebral Oxygenation, Interscalene Brachial Plexus Block
Introduction
Shoulder arthroscopy is a surgical procedure that can be performed under general or regional anaesthesia (GA and RA, respectively). There are many factors that affect the decision of using GA or RA during shoulder arthroscopy which depend on the patient and physician; however, there is no consensus on the superiority of GA or RA. The preferred ‘gold standard’ during this procedure is an interscalene brachial plexus block (ISB), which is a form of RA [1,2]. Hypotension and bradycardia may develop secondary to anaesthesia during ISB, which are caused by stimulation of the Bezold-Jarisch reflex [1]. Hypotension can occur in patients undergoing regional as well as GA due to the vasodilator effects of anaesthetics, especially after induction [1].
Shoulder arthroscopy is performed with the patient in the beach-chair position, where the patient’s head remains elevated. Hypotension is a common occurrence in these patients, which poses a risk for cerebral perfusion due to both anaesthesia and the beach-chair position [3-5]. Therefore, during shoulder arthroscopy, disruption of cerebral perfusion as a result of different mechanisms (e.g. beach-chair position, general anaesthesia, or ISB application) may affect cerebral oxygenation [6]. Permanent or transient neurological damage has been reported after shoulder surgery in the beach-chair position [7, 8]. Although the incidence rate is low (0.004%), there are reports of serious complications including vision loss, spinal cord injury, and cerebral infarction, which are associated with cerebral hypoperfusion [7-9].
Cerebral oxygenation can be measured continuously and noninvasively using near-infrared spectroscopy (NIRS). In the NIRS method, infrared light reaches the surface of the brain. Optical values of oxyhaemoglobin and deoxyhaemoglobin in the capillary bed are used for non-invasive calculation of the oxygen saturation in cerebral tissue [5]. In this method, two sensors attached to the right and left frontal regions are used to calculate the oxygen saturation of cerebral tissue, which allows for quick and early recognition of cerebral hypoperfusion despite its limitations [5].
Previous data regarding shoulder surgery in a sitting position have revealed that ISB alone is more beneficial in maintenance of the arterial pressure during the procedure compared to ISB combined with general anaesthesia [10]. A correlation between the degree of elevation in the beach chair position and the frequency of the intraoperative cerebral desaturation events, which may further lead to a neurocognitive decline, has been reported in subjects undergoing shoulder arthroscopy [11]. A head-to-head comparison of the ISB and GA in terms of hemodynamic changes and cerebral oxygenation in subjects undergoing shoulder surgery has not been performed yet. Through the evidence derived from previous studies, we hypothesized that ISB would provide a favourable hemodynamic profile and cerebral oxygenation than GA in subjects undergoing shoulder arthroscopy.
The aims of this study were to compare the effects of RA with ISB and GA on (i) cerebral oxygen saturation and (ii) heart rate (HR), mean arterial pressure (MAP), and peripheral oxygen saturation (SpO2) in patients undergoing elective shoulder arthroscopy in the beach-chair position.
Material and Methods
Seventy-one consecutive patients, classified as American Society of Anesthesiologists (ASA) class I-III, between the ages of 18 and 70 who were scheduled for arthroscopic shoulder surgery at the Orthopaedics and Traumatology Clinic between March 2015 and January 2017 were assessed for eligibility. Written informed consents were obtained from all patients. The exclusion criteria were known coronary artery disease and/or ejection fraction below 50%, having intracranial mass, cerebrovascular disease, chronic obstructive pulmonary disease, haemoglobin values below 10 mg/dL, patients who experienced ISB failure and switched from arthroscopic to open surgery. According to the exclusion criteria, patients with known coronary artery disease (n=4), chronic obstructive pulmonary disease (n=2), haemoglobin values below 10 mg/dL (n=1) were not included in the study.
Subjects, who were eligible for the study, were randomly allocated to one of the study groups using computer-generated randomization. Randomization data were printed on charts and were kept inside opaque, sealed envelopes until the anaesthesia staff opened them in the operation theatre. The groups were as follows:
GA group: 30 patients anaesthetized using GA
RA group: 30 patients anaesthetized using ISB
All patients were premedicated with intravenous midazolam (0.03 mg/kg) at least 60 minutes before admission. Heart rate (HR), mean arterial pressure (MAP), peripheral oxygen saturation (SpO2), and end-tidal CO2 (EtCO2) monitoring were performed after admission. For cerebral oxygenation monitoring, NIRS (NONIN-Somanetics, Nonin Medical Inc. Minnesota, MN) probes were placed in the right and left frontal regions and the measured values were recorded. Measurement times are as follows:
T0= Before ISB or induction of GA in the supine position
T1= Before the beach-chair position, but after ISB or induction of GA in the supine position
T2= 5 minutes after being in the beach-chair position
T3= 10 minutes after being in the beach-chair position
T4= 20 minutes after being in the beach-chair position
T5= 30 minutes after being in the beach-chair position
In the GA group, preoxygenation was performed 3 minutes with 100% oxygen in all cases. Following the induction of GA, fentanyl (1-2 μg/kg), propofol (2-3 mg/kg), and rocuronium (0.6 mg/kg) were administered. After endotracheal intubation, mechanical ventilation parameters were adjusted to a controlled tidal volume of 7 ml/kg and EtCO2 value between 30-40 mmHg. Anaesthesia was maintained with remifentanil 0.25-0.5 μg/kg/min intravenous (IV) infusion and 4-6% desflurane in a 50/50% O2/air mixture.
In the RA group, 4 L/min O2 support was continued with a mask, and ISB was applied with ultrasound guidance using an anterior, standard volume technique (20 ml local anaesthetic) with 10 ml 0.5% ropivacaine and 10 ml 2% lidocaine. Intermittent doses of midazolam and fentanyl were administered to patients in this group to maintain conscious sedation. The Ramsay sedation score was maintained at 2-3 on the scale, and motor and sensory block were evaluated using the modified Lovett rating scale and pinprick test, respectively [12, 13]. GA was administered to patients in cases where the block failed, and these patients were subsequently excluded from the study.
In both groups, MAP was maintained above 65 mmHg. If MAP dropped below 65mmHg, patients were treated with ephedrine (5 mg). If low MAP was accompanied by a low heart rate (below 60beats/min), patients were treated with atropine (0.5mg). Decreases of more than 20% in the NIRS-right (NIRS-R) and NIRS-left (NIRS-L) values relative to the basal value (T1) were considered critical. In these instances, the inspired oxygen rate was increased.
After GA induction and ISB application, all patients were placed in the beach-chair position and measurements were performed in 5, 10, 20 and 30th minutes.
Sample size calculation
The power calculation was based on our pilot study with first 20 patients. We used “priori t-test; the difference between the two independent means” for comparison of the difference in the MAPs of the two groups at T1 (RA group: 103 ± 15 mmHg, GA group: 96 ± 8 mmHg; alpha error: 0.05, power: 0.95 effects size: 0.9). Considering the change in MAP as a primary outcome, at least 28 patients were required in each group [14].
Statistical analysis
Data were analysed using the Statistica for Windows® Version 12 (StatSoft Inc., Tulsa, USA) computer software package. Descriptive parameters were expressed as mean ± standard deviation or median ± interquartile range. Parametric variables between groups were compared with Student’s t-tests. One-way repeated measures analysis of variances was used to assess within-group differences over time. The post-hoc Tukey’s honestly significant difference (HSD) test was used to assess group differences at individual time points. P values less than 0.05 were considered statistically significant.
Ethical Approval
This study was approved by the Ethics Committee of Manisa Celal Bayar University, Faculty of Medicine (Date: 2015-03-05, No: 20478486-112).
Results
Of the 60 patients, there were 30 cases in each group. Overall, the mean age was 50.8±14.4 (Range: 19-78). Other clinical patient characteristics, initial laboratory findings, and perioperative data that may have affected the primary outcome of the study were similar between groups and are shown in Table 1. Compared to T0, MAP values were significantly lower at T1, T2, T3, and T4 in the GA group (Tukey’s HSD test, p<0.05, p<0.0001, p<0.0001, and p<0.001, respectively; Figure 1). Compared to T0, HR fluctuated considerably at all time points except for T1 in both groups; however, these changes did not reach statistical significance using post-hoc comparisons (Figure 1). SpO2 measurements were similar at all time points except for T1 where it was significantly lower in the RA compared to the GA group (97.9% vs. 99.5%, respectively; Tukey’s HSD test, p<0.001). Lastly, although the NIRS-R and NIRS-L values fluctuated substantially, post-hoc comparisons revealed no significant changes at any of the time points in any of the groups (Figure 2).
Discussion
In the present study, there was no significant difference in NIRS-R or NIRS-L values between the RA and GA groups. However, the NIRS-R and NIRS-L values were lower in the GA group compared to the RA group after patients were placed in the beach-chair position. Compared to baseline, patients in the GA group had significantly lower MAP values 5, 10, and 20 minutes after being placed in the beach-chair position than patients in the RA group. SpO2 levels did not decrease below 95% in 4 L/min O2 support in any of the RA cases during the operation. SpO2 values were significantly lower in the RA group just prior to the beach-chair position. After the beach-chair position was assumed, the between-group difference disappeared, which may be due to the impact of the sitting position on respiratory dynamics. There was no significant difference in HR between groups at any of the time points.
In this study, ISB was performed with an ultrasound-guided anterior approach using a standard volume technique (20 ml local anaesthetic). In the literature, unilateral diaphragmatic paralysis is observed in almost all ISB applications [15]. The resulting diaphragmatic paralysis causes a decrease in vital capacity (VC), forced expiratory volume at the first second (FEV1), and forced vital capacity (FVC), which affects pulmonary function [16, 17]. Additionally, diaphragmatic paralysis causes hypoxemia, which may affect cerebral oxygenation. Several methods have been compared in the literature to avoid diaphragmatic paralysis. For example, Bergmann and colleagues compared pulmonary function using anterior and posterior approaches in ultrasound-guided ISB in patients undergoing shoulder surgery and found no difference between the two approaches [18]. In a study conducted by Ghodki and colleagues, ultrasound-guided ISB was found to be protective against diaphragmatic paralysis compared to nerve stimulation [19]. Riazi and colleagues compared the ultrasound-guided standard volume technique and the low volume technique and found that almost all patients who underwent the procedure using the standard volume technique had diaphragmatic paralysis [20]. In our study, although ISB was performed under the guidance of ultrasound, we used the standard volume technique. In the RA group, the SpO2 level immediately prior to switching to the beach-chair position was significantly lower than that of the GA group, suggesting that patients had diaphragmatic paralysis. Similarly, NIRS-L and NIRS-R values were lower in RA group compared to GA group before taking the patients to beach-chair position. On the contrary, NIRS-L and NIRS-R values were prominently higher in RA group than GA group at beach-chair position.
The hemodynamic parameters of the patients in the RA group did not show a significant decrease in cerebral oxygenation and were stable compared to the GA group. On the other hand, the MAP values of the GA group were significantly lower than the RA group and cerebral oxygenation decreased after the beach-chair position compared to the baseline value. The hemodynamic data and decrease in cerebral oxygenation after GA induction and transition to the beach-chair position are similar to previous findings [5, 21].
The application of ISB to stimulate the Bernold-Jarish reflex may result in bradycardia and hypotension. As shown in previous studies, decreased cardiac output and hypotension are positively correlated with cerebral oxygenation [5,6]. A decrease in cerebral oxygenation with ISB is to be expected given both the hemodynamic and pulmonary side effects. However, our study shows that GA results in a larger decrease in cerebral oxygenation. Therefore, ISB is the preferred method of anaesthesia for shoulder surgery in patients where cerebral oxygenation is of concern. However, care should be taken in patients with impaired pulmonary function, such as pulmonary diseases and obesity [9]. Janssen and colleagues found no differences in hemodynamic data between GA alone, and GA combined with ISB.1 Since the combination of GA and ISB did not increase hemodynamic side effects relative to GA alone, this suggests that the combination did not cause a decrease in cerebral oxygenation. However, no studies have compared the use of ISB alone to GA for anaesthesia.
In our study, MAP values significantly decreased after GA induction, as well as after the beach-chair position. While the effect of hemodynamic changes in the beach-chair position on cerebral oxygenation was significant in the GA group, this was not observed in the RA group. GA induction often results in a decrease in MAP due to cardiovascular effects, which becomes more pronounced when patients are placed in the beach-chair position.
One limitation of the present study is that the measurements performed by the NIRS method may be influenced by several factors, including the location of the sensors, arterial and venous vascular density around the NIRS sensors, presence of arterio-venous shunts or oedema at sites where the sensors have been placed. Second, the absence of any significant difference in NIRS values between the groups may have been influenced by the enrolment of healthy individuals without severe comorbidities. Therefore, these results cannot be generalized extensively to all subjects undergoing arthroscopic shoulder surgery. Future studies in subjects with atherosclerosis, intracranial mass, cerebrovascular disease, chronic obstructive pulmonary disease, and heart failure are required to address the role of ISB in subjects with comorbid conditions.
Conclusion
In the beach-chair position, ISB did not cause a significant decrease in cerebral oxygenation. Although it did not reach statistical significance, this study showed that cerebral oxygenation was worse in patients who were placed in the beach-chair position under GA than in subjects receiving RA with ISB.
Acknowledgment
The authors would like to acknowledge the support of Dr Güven Olgaç in data analysis.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Janssen H, Stosch Rv, Pöschl R, Büttner B, Bauer M, Hinz JM, et al. Blood pressure response to combined general anaesthesia/interscalene brachial plexus block for outpatient shoulder arthroscopy. BMC Anesthesiol. 2014;14:50.
2. Nisar A, Morris MW, Freeman JV, Cort JM, Rayner PR, Shahane SA. Subacromial bursa block is an effective alternative to interscalene block for postoperative pain control after arthroscopic subacromial decompression: A randomized trial. J Shoulder Elbow Surg. 2008;17:78-84.
3. Jeong H, Lee SH, Jang EA, Chung SS, Lee J, Yoo KY. Haemodynamics and cerebral oxygenation during arthroscopic shoulder surgery in beach chair position under general anaesthesia. Acta Anaesthesiol Scand. 2012;56(7):872-9.
4. Kwak HJ, Lee D, Lee YW, Yu GY, Shinn HK, Kim JY. The intermittent sequential compression device on the lower extremities attenuates the decrease in regional cerebral oxygen saturation during sitting position under sevoflurane anesthesia. J Neurosurg Anesthesiol. 2011;23(1):1-5.
5. Moerman AT, De Hert SG, Jacobs TF, De Wilde LF, Wouters PF. Cerebral oxygen desaturation during beach chair position. Eur J Anaesthesiol. 2012;29(2):82-7.
6. Meng L, Cannesson M, Alexander BS, Yu Z, Kain ZN, Cerussi AE, et al. Effect of phenylephrine and ephedrine bolus treatment on cerebral oxygenation in anaesthetized patients. Br J Anaesth. 2011;107(2):209-17.
7. Bhatti MT, Enneking FK. Visual loss and ophthalmoplegia after shoulder surgery. Anesth Analg. 2003;96(3):899-902.
8. Pohl A, Cullen DJ. Cerebral ischemia during shoulder surgery in the upright position: A case series. J Clin Anesth. 2005;17(6):463-9.
9. Salazar DH, Davis WJ, Ziroğlu N, Garbis NG. Cerebral desaturation events during shoulder arthroscopy in the beach chair position. J Am Acad Orthop Surg Glob Res Rev. 2019;3(8):e007.
10. Ozzeybek D, Oztekin S, Mavioğlu O, Karaege G, Ozkardeşler S, Ozkan M, et al. Comparison of the haemodynamic effects of interscalene block combined with general anaesthesia and interscalene block alone for shoulder surgery. J Int Med Res. 2003;31(5):428-33.
11. Pant S, Bokor DJ, Low AK. Cerebral oxygenation using near-infrared spectroscopy in the beach-chair position during shoulder arthroscopy under general anesthesia. Arthroscopy. 2014;30(11):1520-7.
12. Singh S, Aggarwal A. A randomized controlled double-blinded prospective study of the efficacy of clonidine added to bupivacaine as compared with bupivacaine alone used in supraclavicular brachial plexus block for upper limb surgeries. Indian J Anaesth. 2010;54(6):552-7.
13. Sessler CN, Grap MJ, Ramsay MA. Evaluating and monitoring analgesia and sedation in the intensive care unit. Crit Care. 2008;12:S2.
14. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175-91.
15. Bruce BG, Green A, Blaine TA, Wesner LV. Brachial plexus blocks for upper extremity orthopaedic surgery. J Am Acad Orthop Surg. 2012;20(1):38-47.
16. Palhais N, Brull R, Kern C, Jacot-Guillarmod A, Charmoy A, Farron A, et al. Extrafascial injection for interscalene brachial plexus block reduces respiratory complications compared with a conventional intrafascial injection: A randomized, controlled, double-blind trial. Br J Anaesth. 2016;116(4):531-537.
17. Kurt E, Güzeldemir ME. Interscalene brachial plexus block and pulmonary function. Can J Anaesth. 1999;46(8):808-9.
18. Bergmann L, Martini S, Kesselmeier M, Armbruster W, Notheisen T, Adamzik M, et al. Phrenic nerve block caused by interscalene brachial plexus block: Breathing effects of different sites of injection. BMC Anesthesiol. 2016;16(1):45.
19. Ghodki PS, Singh ND. Incidence of hemidiaphragmatic paresis after peripheral nerve stimulator versus ultrasound guided interscalene brachial plexus block. J Anaesthesiol Clin Pharmacol. 2016;32(2):177-81.
20. Riazi S, Carmichael N, Awad I, Holtby RM, McCartney CJ. Effect of local anaesthetic volume (20 vs 5 ml) on the efficacy and respiratory consequences of ultrasound-guided interscalene brachial plexus block. Br J Anaesth. 2008;101(4):549-56.
21. Lee JH, Min KT, Chun YM, Kim EJ, Choi SH. Effects of beach-chair position and induced hypotension on cerebral oxygen saturation in patients undergoing arthroscopic shoulder surgery. Arthroscopy. 2011;27(7):889-94.
Download attachments: 10.4328.ACAM.22076
Arzu Acikel, Ismet Topcu, Tulun Ozturk, Gonul Tezcan Keles, Tackin Ozalp. The effect of regional and general anaesthesia on cerebral oxygenation in shoulder arthroscopy. Ann Clin Anal Med 2024;15(5):324-328
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Evaluation of the relationship between disease severity and the leptin, adiponectin, and chemerin levels in overweight and obese COVID-19 patients
Gonul Seyda Seydel 1, Inayet Gunturk 2, Cevat Yazıcı 3, Ulas Serkan Topaloglu 4, Esma Eryılmaz Eren 5, Recep Civan Yuksel 6
1 Department of Health Care Services, Nigde Zübeyde Hanım Vocational Faculty of Health Service, Nigde Omer Halisdemir University, Nigde, 2 Department of Midwifery, Zubeyde Hanım Faculty of Health Sciences, Nigde Omer Halisdemir University, Nigde, 3 Department of Medical Biochemistry, Faculty of Medicine, Erciyes University, Kayseri, 4 Department of Internal Medicine, Kayseri City Hospital, Kayseri, 5 Department of Infectious Diseases and Clinical Microbiology, Kayseri City Hospital, Kayseri, 6 Department of Intensive Care, Faculty of Medicine, Erciyes University, Kayseri, Turkey
DOI: 10.4328/ACAM.22078 Received: 2023-12-19 Accepted: 2024-02-12 Published Online: 2024-03-22 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):329-333
Corresponding Author: Gonul Seyda Seydel, Department of Health Care Services, Zübeyde Hanım Vocational Faculty of Health Services, Nigde Omer Halisdemir University, 51240, Nigde Turkey. E-mail: seydaseydel@hotmail.com P: +90 553 351 45 91 Corresponding Author ORCID ID: https://orcid.org/0000-0001-9317-0719
This study was approved by the Ethics Committee of Nigde Omer Halisdemir University (Date: 2021-02-21, No: 23)
Aim: Overweight and obesity are substantial risk factors in the severity of COVID-19 disease. This study aimed to assess the relationship between the disease severity and leptin, adiponectin, and chemerin levels in overweight and obese COVID-19 patients.
Material and Methods: The study involved 60 COVID-19 patients (patient group) and 30 healthy controls with BMI≥25. The patient group was split into two subgroups based on disease severity (30 mild/moderate and 30 severe/critical patients). The levels of leptin, adiponectin, and chemerin in plasma were determined using the ELISA technique.
Results: Our study revealed that leptin levels were considerably increased in both groups of COVID-19 patients compared to the healthy controls, while chemerin levels were decreased. In adiponectin levels, there was no statistically significant difference between the groups.
Discussion: Plasma leptin and chemerin levels are associated with the progression and/or severity of disease in overweight and obese COVID-19 patients.
Keywords: COVID-19, Leptin, Adiponectin, Chemerin, Obesity
Introduction
Coronavirus disease 2019 (COVID-19) is an exceptionally complex disease with a wide variety of clinical manifestations ranging from mild to severe and critical disease [1]. Although the mechanisms underlying the pathophysiology of COVID-19 disease are not yet fully understood, overweight and obesity are acknowledged to considerably contribute to the disease’s severity through a variety of processes. Notably, recent studies have revealed that overweight and obesity are substantial risk factors for hospitalization, intensive care unit (ICU) admission, respiratory failure, and invasive mechanical ventilation (IMV) requirements in COVID-19 patients [2-4].
Obesity represents a state of low-grade inflammation because of the chemoattraction of macrophages and its expansion in the adipose tissue [5, 6]. Adipose tissue secretes a large number of molecules known as adipokines, which are involved in the regulation of many pivotal biological processes, including inflammation and immunity [7]. Dysregulated adipokines synthesis from adipose tissue may contribute to the emergence of the “cytokine storm” that characterized the severe form of COVID-19 and can be presented as a plausible mechanism explaining the influence of obesity on disease severity [5, 6, 8].
Leptin is a pleiotropic hormone, mainly released by white adipose tissue which has significant functions in energy regulation, endocrine, metabolism, and inflammation. In addition to these functions, leptin is a pro-inflammatory adipokine that promotes both innate and adaptive immune responses [3, 4]. Adiponectin is the most prevalent plasma protein and exhibits anti-inflammatory properties. It possesses antioxidant, anti-fibrotic, anti-atherogenic, and anti-apoptotic properties and is engaged in a range of biological processes such as insulin sensitization, glucose regulation, and fatty acid oxidation. It has been reported that adiponectin levels were decreased in metabolic disorders such as diabetes and obesity [9]. Chemerin is a novel adipokine with autocrine, paracrine, and endocrine effects. It modulates energy metabolism, angiogenesis, and adipogenesis, as well as innate and adaptive immunity by functioning as a powerful chemoattractant protein for immune cells. It has also been demonstrated to increase considerably in several inflammatory and metabolic diseases [10, 11].
Given that background, these adipokines may be involved in the relationship between the heightened inflammatory response and dysfunctional adipose tissue in severe COVID-19 disease, albeit their role in the disease is not entirely known. There are few data in the literature on the relationship between the severity of disease and plasma leptin, adiponectin, and chemerin levels, and the findings are contradictory with each other. Hence, the purpose of this study was to evaluate the relationship between the severity of the disease and levels of leptin, adiponectin, and chemerin in overweight and obese COVID-19 patients.
Material and Methods
Study population
This prospective study consisted of 60 patients with RT-PCR-confirmed diagnosis of COVID-19 (patient group) and 30 healthy control (control group), who applied to the Clinic of Infectious Disease, Internal Medicine, and Intensive Care Unit of Kayseri City Hospital, Turkey. The patient group was split into two groups based on the severity of the disease: mild/moderate (n:30) and severe/critical (n:30) [1]. The study inclusion criteria for all the groups were: (1) age ≥ 18 years, and (2) Body Mass Index (BMI) ≥25. The study exclusion criteria for all the groups were: (1) the presence of chronic systemic inflammatory disease, (2) the presence of metabolic disease, (3) the presence of chronic kidney and liver failure, and (4) the presence of malignancy. Demographic characteristics and laboratory parameters of all participants were retrieved from the patient files by the physicians who followed the patients. Laboratory parameters were measured using routine laboratory techniques within 24 hours of admission. BMI was divided into six categories according to WHO classification [12].
Collection of blood samples
5 mL of blood was collected from each participant into EDTA-containing tubes and centrifuged at 1500 g for 10 minutes at 4°C. The plasma samples were kept in aliquots at -80 °C until the enzyme-linked immunosorbent assay (ELISA) analysis was performed.
Plasma leptin, adiponectin, and chemerin analyses
Leptin (USCN, SEA084Hu), adiponectin (USCN, SEA605Hu), and chemerin (USCN, SEA945Hu) levels in plasma were determined using an ELISA kit according to the manufacturer’s instructions. All samples were diluted 1/10, and absorbance values were recorded by reading at 450 nm with a BioTek ELx800 absorbance microplate reader.
Statistics Analyses
Statistical analyses were carried out by using the IBM SPSS Statistics version 23 (IBM Corp, Armonk, NY, USA). Categorical variables were presented as percentages (%) and/or numbers (n). The normality of the distribution of the data was determined with the Shapiro–Wilk test. Data were expressed as mean ± standard deviation (SD) and median [interquartile range (IQR; 25%-75%)] for variables with normal and non-normal distributions, respectively. In the comparison of data between groups, the ANOVA test, followed by the post-hoc test was used for data with normal distribution, and the Kruskal Wallis test, followed by the Mann-Whitney U test was used for non-normal distribution data. The level of statistical significance was defined as p<0.05.
Ethical Approval
This study was approved by the Ethics Committee of Nigde Omer Halisdemir University (Date: 2021-02-21, No: 23).
Results
As shown in Table 1, in the control group, there were 14 (46.7%) males and 16 (53.3%) females; in the mild/moderate patient group, there were 14 (46.7%) males and 16 (53.3%) females; and in the severe/critical group, there were 12 (40%) males and 18 (60%) females. There was no statistically significant difference between the groups in terms of gender (p=0.892), age (p=0.132), and BMI (0.245).
WBC and neutrophil counts were significantly higher in the severe/critical patient group than in the control and the mild/moderate patient group. Lymphocyte levels were significantly higher in the mild/moderate group compared to the control group, and lower in the severe/critical patient group than in the mild/moderate patient group. CRP and AST levels in both patient groups were found to be significantly higher than in the control group. ALT levels were considerably higher in the severe/critical patient group than in the control group. LDH and BUN levels were significantly lower in the mild/moderate group compared to the control group, and higher in the severe/critical patient group than in the mild/moderate patient group (Table 1).
Plasma leptin levels were significantly increased in both COVID-19 patient groups compared to the control group, with the highest levels found in severe/critical patients. There was no statistically significant difference in plasma adiponectin levels between the groups. Chemerin levels were considerably decreased in both patient groups compared to the control group; however, there was no statistically significant difference between the patient groups (Table 2).
Discussion
Adipokines are bioactive molecules that have pleiotropic effects. In recent years, a number of studies have revealed that they play a crucial role in the development of several diseases and in regulating metabolism, inflammation, and immunity. On the other hand, adipokine dysregulation leads to obesity-related diseases. Especially, since the majority of adipokines are elevated in obese individuals and contribute to low-grade inflammation, they are now regarded as important players in inflammation and immunity [7]. However, their role on the development and severity of COVID-19 disease is not yet fully known. Therefore, in this study, we evaluated the relationship between disease severity and leptin, adiponectin, and chemerin levels in COVID-19 patients with overweight and obese.
Leptin, as a pro-inflammatory cytokine, may serve as a link between obesity, metabolism, and inflammatory diseases [4]. Leptin levels reflect the amount of energy stored and were positively associated with fat mass and BMI [7]. Nevertheless, the study results regarding leptin levels in COVID-19 disease are confusing, and it has been reported that COVID-19 patients had increased or decreased leptin levels [13-16]. In our study, we found that plasma leptin levels increased in both patient groups compared to the control group, and their levels increased with the enhanced severity of the disease. Consistent with our results, Wang et al. demonstrated that as compared to healthy controls and mild patients, leptin levels in severe COVID-19 patients are considerably higher and that these increased levels are associated with systemic inflammation, disease severity, and progression. They have also shown that in patients with a BMI >24, the increase of leptin was greater in severe patients compared to mild patients. Additionally, COVID-19 patients with overweight had higher leptin levels, which further activated monocytes, and led to dysregulated or amplified immune responses [13]. Tonon et al. have indicated that patients with COVID-19 pneumonia had increased leptin levels as compared to healthy controls. In addition, leptin has an acceptable discriminatory accuracy for COVID-19 pneumonia in patients with BMI>30 and was related to maximum respiratory support [14]. Similar findings were obtained by Van der Voort et al. who reported that COVID-19 patients had significantly higher levels of serum leptin compared to control patients. Additionally, they also suggested that excessive adipose tissue and elevated levels of leptin in COVID-19 patients can trigger the development of respiratory failure and acute respiratory distress syndrome [15]. All of these findings suggest that increased leptin levels following infection may play a pivotal role in the mechanisms leading to the severe progression of COVID-19, particularly in obese and overweight individuals [5, 13, 15, 16]. On the other hand, contrary to our findings, few studies have also reported that there is no association between leptin and disease severity in COVID-19 [17-19]. Di Filippo et al. reported that there was no significant difference in leptin levels of patients with severe COVID-19 compared to the patients with mild and moderate COVID-19. However, they attributed the discrepancy with the findings of other studies to the fact that they measured leptin shortly after hospitalization, and also noted that leptin levels may increase later in those with an insufficient anti-inflammatory response at the onset of the disease [17].
Adiponectin is an adipokine that has anti-inflammatory properties and it has been shown in various studies that decreased adiponectin levels are associated with metabolic syndrome, obesity, and inflammation [8, 9]. The role of adiponectin in COVID-19 disease is still unclear, and reviewing literature showed that the results of the previous studies on COVID-19 contradict each other [17-21]. Reiterer et al. found that adiponectin levels had significantly decreased in severe COVID-19 patients [20]. Likewise, Kearns et al. reported that patients with COVID-19 ICU with acute respiratory failure were related to decreased adiponectin levels even after adjusting BMI and these decreased adiponectin levels played an essential role in the association between obesity and COVID-19. Furthermore, they also implied that hypoadiponectinemia, which is common in obese patients, may facilitate the increased inflammatory response to the pulmonary capillaries [21]. In contrast to the results described above, we found that there was no significant difference between the groups in terms of adiponectin levels. Similarly, one study conducted by Minuzzi et al. demonstrated that adiponectin levels were not associated with IC requirement or outcome in obese COVID-19 patients [19]. Additionally, it has been reported that there is no relationship between adiponectin levels and disease severity [17, 18]. These observed discrepancies may be due to differences in the patient cohort.
Chemerin is an intriguing adipokine that has gained recognition as a metabolic and immunological process regulator; bridging inflammatory diseases and obesity and its levels are considerably increased in these diseases. Furthermore, it has been also reported that chemerin levels are positively correlated with several inflammatory markers and obesity-related markers [10, 11]. There have been few studies on the levels of chemerin in COVID-19. Nonetheless, like leptin and adiponectin, results regarding levels of chemerin remain debatable [8, 22-25]. Lavis et al. found that plasma chemerin levels were significantly higher in COVID-19 patients compared to healthy controls and correlated with inflammation and disease severity [22]. Similar results have been reported by Hussein et al [23]. Fioravanti et al. implied that tocilizumab, an IL-6 receptor antagonist, can be used in reducing chemerin circulating levels and treatment of severe complications in COVID-19 patients, particularly in obesity, by modulating it [8]. In contrast to these results, our investigation indicated that chemerin levels were significantly decreased in both groups of COVID-19 patients compared to the healthy controls, but were not associated with disease severity. This result is one of the remarkable findings of the present study. In line with our findings, Kukla et al. demonstrated that chemerin levels were considerably decreased in COVID-19 patients compared to healthy controls. They also found no relationship between disease severity and decreased chemerin levels [24]. Sulicka-Grodzicka et al. found that chemerin levels decreased one week following the onset of symptoms in moderate and severe COVID-19 patients and that this decline may be related to an enhanced inflammatory response in patients with more severe infections [25]. These findings do not appear to be compatible with previous research indicating that chemerin has pro-inflammatory properties. Nonetheless, although chemerin is generally known as a pro-inflammatory adipokine, experimental research has revealed that it exhibits pro- or anti-inflammatory effects that vary depending on the tissue and stimulus in which it is activated and various clinical circumstances [10, 11, 22]. Taking into consideration our results, in this study, it was shown that chemerin may also have anti-inflammatory effects and play a role in the pathogenesis of COVID-19. Further studies are needed to determine the role of chemerin.
Conclusion
In conclusion, increased leptin and decreased chemerin levels have been associated with the progression and/or severity of disease in overweight and obese COVID-19 patients. These results support the hypothesis that leptin and chemerin levels play a significant role in the inflammatory process and the mechanisms underlying the exacerbation of COVID-19 after infection in overweight and obese patients. Furthermore, although chemerin is generally known as a pro-inflammatory adipokine, this study also showed that it may possess anti-inflammatory effects.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: This work was supported by the Nigde Omer Halisdemir University Scientific Research Projects Coordination Unit under Project number: SAT 2022/3-BAGEP.
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Baj J, Karakuła-Juchnowicz H, Teresiński G, Buszewicz G, Ciesielka M, Sitarz R, et al. COVID-19: Specific and non-specific clinical manifestations and symptoms: The current state of knowledge. J Clin Med. 2020;9(6):1753.
2. Huang Y, Lu Y, Huang YM, Wang M, Ling W, Sui Y, et al. Obesity in patients with COVID-19: a systematic review and meta-analysis. Metabolism. 2020;113:154378.
3. De Leeuw AJM, Oude Luttikhuis MAM, Wellen AC, Müller C, Calkhoven CF. Obesity and its impact on COVID-19. J Mol Med (Berl). 2021;99(7):899-915.
4. Demeulemeester F, de Punder K, van Heijningen M, van Doesburg F. Obesity as a risk factor for severe COVID-19 and complications: A review. Cells. 2021;17;10(4):933.
5. Maurya R, Sebastian P, Namdeo M, Devender M, Gertler A. COVID-19 severity in obesity: Leptin and inflammatory cytokine interplay in the link between high morbidity and mortality. Front Immunol. 2021;12:649359.
6. Post A, Bakker SJL, Dullaart RPF. Obesity, adipokines and COVID-19. Eur J Clin Invest. 2020;50(8):e13313.
7. Francisco V, Pino J, Gonzalez-Gay MA, Mera A, Lago F, Gómez R, et al. Adipokines and inflammation: is it a question of weight? Br J Pharmacol. 2018;175(10):1569-1579.
8. Fioravanti A, Porcelli B, Terzuoli L, Bacarelli MR, Tenti S, Cheleschi S. Tocilizumab, adipokines and severe complications of COVID-19. Clin Drug Investig. 2020;40(9):891-892.
9. Choi HM, Doss HM, Kim KS. Multifaceted physiological roles of adiponectin in inflammation and diseases. Int J Mol Sci. 2020;21(4):1219.
10. Helfer G, Wu QF. Chemerin: a multifaceted adipokine involved in metabolic disorders. J Endocrinol. 2018;238(2):79-94.
11. Buechler C, Feder S, Haberl EM, Aslanidis C. Chemerin isoforms and activity in obesity. Int J Mol Sci. 2019;20(5):1128.
12. James PT, Leach R, Kalamara E, Shayeghi M. The worldwide obesity epidemic. Obes Res. 2001;9(4):228-233.
13. Wang J, Xu Y, Zhang X, Wang S, Peng Z, Guo J, et al. Leptin correlates with monocytes activation and severe condition in COVID-19 patients. J Leukoc Biol. 2021;110(1):9-20.
14. Tonon F, Di Bella S, Giudici F, Zerbato V, Segat L, Koncan R, et al. Discriminatory value of adiponectin to leptin ratio for COVID-19 pneumonia. Int J Endocrinol. 2022;2022:9908450.
15. Van der Voort PHJ, Moser J, Zandstra DF, Muller Kobold AC, Knoester M, Calkhoven CF, et al. Leptin levels in SARS-CoV-2 infection related respiratory failure: A cross-sectional study and a pathophysiological framework on the role of fat tissue. Heliyon. 2020;6(8):e04696.
16. Perrotta F, Scialò F, Mallardo M, Signoriello G, D’Agnano V, Bianco A, et al. Adiponectin, leptin, and resistin are dysregulated in patients infected by SARS-CoV-2. Int J Mol Sci. 2023;24(2):1131.
17. Di Filippo L, De Lorenzo R, Sciorati C, Capobianco A, Lorè NI, Giustina A, et al. Adiponectin to leptin ratio reflects inflammatory burden and survival in COVID-19. Diabetes Metab. 2021;47(6):101268.
18. Blot M, Masson D, Nguyen M, Bourredjem A, LYMPHONIE Study Group; Binquet C, et al. Are adipokines the missing link between obesity, immune response, and outcomes in severe COVID-19?. Int J Obes. 2021;45(9):2126-2131.
19. Minuzzi LG, Seelaender M, Silva BSA, Cunha EDBB, Deus MC, Vasconcellos FTF, et al. COVID-19 outcome relates with circulating BDNF, according to patient adiposity and age. Front Nutr. 2021;8:784429.
20. Reiterer M, Rajan M, Gómez-Banoy N, Lau JD, Gomez-Escobar LG, Ma L, et al. Hyperglycemia in acute COVID-19 is characterized by insulin resistance and adipose tissue infectivity by SARS-CoV-2. Cell Metab. 2021;33(11):2174-2188.e5.
21. Kearns SM, Ahern KW, Patrie JT, Horton WB, Harris TE, Kadl A. Reduced adiponectin levels in patients with COVID-19 acute respiratory failure: A case-control study. Physiol Rep. 2021;9(7):e14843.
22. Lavis P, Morra S, Orte Cano C, Albayrak N, Corbière V, Olislagers V, et al. Chemerin plasma levels are increased in COVID-19 patients and are an independent risk factor of mortality. Front Immunol. 2022;13:941663.
23. Hussain LJ, Al Ha, Ali RA, Naser FA. Assessment of serum hypoxia-inducible factor-1 and chemerin levels as potential markers of severity in COVID-19 patients. HIV Nursing. 2022;22(2) 993-1000.
24. Kukla M, Menżyk T, Dembiński M, Winiarski M, Garlicki A, Bociąga-Jasik M, et al. Anti-inflammatory adipokines: chemerin, vaspin, omentin concentrations and SARS-CoV-2 outcomes. Sci Rep. 2021;11(1):21514.
25. Sulicka-Grodzicka J, Surdacki A, Surmiak M, Sanak M, Wizner B, Sydor W, et al. Chemerin as a potential marker of resolution of inflammation in COVID-19 infection. Biomedicines.2022;10(10):246.
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Hospital and 1-Year mortality Outcomes in COVID-19 pneumonia
Selvi Askar 1, Muntecep Askar 2, Mehmet Hakan Bilgin 1, Hanifi Yıldız 1, Rasa Beyzaei 3, Sıddık Keskin 4
1 Department of Chest Diseases, Faculty of Medicine, Yuzuncu Yil University, 2 Department of Cardiology, Faculty of Medicine, Van Yuzuncu Yil University, Van Training and Research Hospital, 3 Student, Faculty of Medicine, Van Yuzuncu Yil University, 4 Department of Biostatistics, Faculty of Medicine, Van Yuzuncu Yil University, Van, Turkey
DOI: 10.4328/ACAM.22082 Received: 2023-12-25 Accepted: 2024-02-12 Published Online: 2024-03-23 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):334-338
Corresponding Author: Selvi Askar, Department of Chest Disease, Faculty of Medicine, Yuzuncu Yil University, 65000, Van, Turkey. E-mail: selviasker@gmail.com P: +90 505 251 47 04 Corresponding Author ORCID ID: https://orcid.org/0000-0003-4077-8549
Aim: COVID-19 caused many deaths, and its socioeconomic impact continues. Hospital mortality is generally known, but information on 1-year mortality is limited. This study aimed to measure all-cause mortality rates in hospitalized and 1-year follow-up COVID-19 patients and to evaluate the factors affecting these rates.
Material and Methods: PCR-positive patients’ demographic, clinical, and laboratory characteristics were retrospectively analyzed. Hospitalization duration and mortality data were recorded. Discharged patients’ polyclinic, follow-up, and mortality status within one-year were evaluated.
Results: The study included 201 patients, with a mean age of 63.12±14.5 years, and 59.2% were male. Logistic regression analysis identified several factors affecting hospital mortality, including male gender, smoking, lactate-dehydrogenase, and ferritin. Further analyses indicated that advanced age, low-oxygen saturation, high-sodium levels, low-potassium levels, low-hemoglobin), elevated-white-blood cell count, reduced-platelet count, increased INR and D-Dimer count, and elevated-CRP (C-reactive protein) levels were significant factors influencing hospital mortality. Mortality within 1-year was associated with factors including male gender, diabetes, low-oxygen saturation, elevated-AST levels, elevated-ALT levels, elevated-ferritin levels, and hospitalization length. Those who died within one year were more likely to have been hospitalized in intensive-care unit, required oxygen support, and were smokers.
Discussion: Hospital mortality was associated with impaired laboratory parameters and smoking, whereas 1-year mortality was associated with intensive-care, oxygen requirements, and diabetes.
Keywords: COVID-19, Mortality, Risk Factors, Pneumonia
Introduction
Beginning as an outbreak in December in China, the so-called novel coronavirus 2019 has since spread rapidly worldwide. According to the World Health Organization (WHO), there are no specific drugs or antiviral therapies to treat or prevent the novel coronavirus. Studies show that one-year mortality is in one-third of discharged patients with pneumonia or acute respiratory distress syndrome who survive in the hospital [1,2]. Especially in covid-19 patients developing respiratory failure, there is a risk of mortality even if discharged from the hospital. Studies have shown that advanced age, male gender, comorbid cardiovascular diseases, diabetes, chronic obstructive pulmonary disease (COPD), and malignancies increase hospital mortality [3,]. Considering these premises, it seems reasonable to expect a significant long-term mortality rate after hospitalization in COVID-19 patients; however, little is known about post-discharge mortality, and scientific evidence is still limited[4]. Risk factors predicting this risk should be investigated more extensively. Awareness should be raised among physicians about the predictors of post-discharge mortality, and a follow-up program should be structured for discharged patients. In our study, patients’ in-hospital and 1-year post-discharge mortality evaluations were performed more comprehensively with demographic, clinical, and laboratory data.
Material and Methods
Between May 2020 and July 2020, covid-19 pneumonia patients over the age of 18 who were PCR positive and followed up in the covid-19 pandemic service and intensive care unit of Van Yüzüncü Yıl University Faculty of Medicine Hospital were included in the study. Patient data (demographic, clinical, laboratory, and imaging) were obtained retrospectively from the files and hospital registration system. Patients aged below 18 years, those with negative PCR tests, pregnant women, and those with missing data in their files were excluded from the study. 1st-year survival of discharged patients was recorded by phone or through the system.
Statistical Analysis
Descriptive statistics for continuous variables were expressed as Mean, Standard Deviation, Minimum, and Maximum values, while descriptive statistics for categorical variables were expressed as numbers and percentages. One-way analysis of variance was used to compare group averages in terms of continuous variables. Pearson correlation coefficients were calculated to determine the relationship between these variables. Logistic regression analysis was also performed to determine the effect of categorical variables on survival. The statistical significance level was taken as 5%, and the SPSS (ver: 21) statistical package program was used for calculations.
Ethical Approval
The study was conducted in accordance with ethical rules.
Results
The mean age of the 201 patients in the study was 63.12±14.5 years (59.2% male). 59.2% (n:119) of the patients were hospitalized in non-intensive care units. The most common comorbidities were hypertension (41.3%) and diabetes (25.4%), COPD (21.9%), and asthma (8%). The number of patients who died in the hospital was 61 (30.3%), and the number of patients who died within one year after discharge was 15 (7.5%). According to logistic regression analysis, the factors affecting in-hospital mortality were male gender (OR:34.8 p=0.005), smoking (OR:7.6 p=0.007), lactate dehydrogenase (OR:1.01 p=0.003), and ferritin (OR:1 p=0.002) (Table 1). In additional analyses, high age (p=0.000), low oxygen saturation (p=0.000), high sodium (p=0.021), low potassium (p=0.013), low hemoglobin (p=0.003), elevated white blood cell count (p=0.000), low platelet count (p=0.008), elevated INR and D-Dimer (p=0.000), and elevated CRP (p=0.000) were found to be effective in-hospital mortality (Table 2). The presence of diabetes (OR: 18 p=0.053), low oxygen saturation (OR: 0.78 p=0.046), elevated AST (OR: 0.79 p=0.047), elevated ALT (OR: 1.04 p=0.049), elevated ferritin (OR: 1.007 p=0.013) and length of hospitalization (OR: 1.2 p=0.046) affected mortality within one year after discharge (Table 3). Patients who died within one year were hospitalized in the intensive care unit (p=0,000), received oxygen support (p=0,000), and most of them were smokers (p=0,000). Within one year, the causes of mortality were cardiovascular diseases (n:6), malignancy (n:2), and post-covid respiratory failure (n:6).
Discussion
COVID-19 remains a global problem for which there is no cure. Since there is no cure, controlling risk factors for the accompanying poor prognosis should be prioritized in these patients. Covid-19 is a viral infection, and the picture it creates is similar to pandemics and epidemics that existed in other times. Therefore, studies showing mortality risk factors in viral pneumonia over such a high number of patients will contribute to the literature.
In our study, it was noteworthy that the factors that triggered hospital mortality were primarily male gender, smoking, and laboratory parameters, while in 1-year mortality, intensive care unit hospitalization, oxygen requirement, and the presence of diabetes mellitus were additionally observed. While the overall hospital mortality rate is 5.2%, the mortality rate varies between 30% and 65% in patients who need mechanical ventilation or are hospitalized in the intensive care unit for advanced supportive treatment [5, 6]. Mortality rates changed in the first and second waves of Covid-19 [7].
The mutation of the virus and the ability of the health system to control patients and risk factors may be a factor in this. Our study was conducted during the first wave, and the hospital mortality rate was 30.3% (n:61). Although recent advances in treatment and the availability of vaccines have reduced mortality and morbidity due to COVID-19, the disease was characterized by high mortality in the early stages of the pandemic [8] .In another study, hospital mortality was found to be 31.1%, just like in our study[9].While the hospital mortality rate in our study was the same as in this study, the 1-year mortality rate was 7.5%. In this study, 1-year mortality was 3.3%(12). The higher 1-year mortality rate in our study may be because many patients were hospitalized in the intensive care unit. In the meta-analysis by Ramzi et al., the all-cause mortality rate after discharge, especially in COVID-19, was 7.5%[4].This result was similar to our study. In a study by Herridge et al., the one-year mortality rate was 11% in ARDS survivors [10]. Interestingly, other longitudinal studies of ARDS survivors found advanced age and pre-ICU comorbidities as independent predictors of mortality rather than the severity of disease or ICU factors [11].The results of these studies were similar to our study. The variability in reported mortality rates may be explained by different treatment approaches between countries, differences in the number of beds and healthcare personnel in intensive care units, medical infrastructure, and follow-up periods [12].When the literature is examined, although there are various limitations regarding the results obtained due to the number of patients, differences in study designs, and lack of data, many prognostic factors and conditions affecting mortality have been defined. Our study investigating the factors affecting mortality and morbidity in patients with COVID-19 showed that the age factor was significant, and male gender and the presence of comorbid diseases in 1-year mortality were also associated with a high mortality rate. When the relationship between SARS-CoV-2 and gender was investigated, it was reported that men were more frequently infected than women, and the likelihood of developing Acute Respiratory Distress Syndrome was higher in older men with comorbidities than women [12]. Although there have been animal experiments on patients with ARDS, there is no proven medicine currently in use [13]. A Chinese study found that among those with a disease picture, severe disease, and mortality rates were higher in men, especially in the 50-69 age group [14].In this study, in which data from ten European countries were evaluated, it was found that advanced age and male gender increased mortality. In our study, the mean age of those who died was 69± 13.2 years and p=0000. It was observed that the male gender had a 34 times higher mortality rate. It is thought that the low mortality rate in women may be due to hormonal reasons and immune response differences [15]. In Covid -19 patients, no association was found between hospital survival and one-year survival regarding asthma, COPD and hypertension, while a negative association was found between 1-year survival and diabetes mellitus. In hospital mortality, although not statistically significant, HT was associated with 1.3-fold COPD, 1.5-fold asthma 1.8-fold mortality. A study found that comorbid pathologies such as hypertension, hypercholesterolemia, heart disease, diabetes mellitus, malignancy, chronic obstructive pulmonary disease, chronic kidney disease, and medications used before hospitalization were associated with mortality [16]. Although Alhakak et al. [17] reported that diabetes was associated with mortality in more than 3000 patients, there is no data on 1-year mortality. In studies conducted with more patients in the literature, results were obtained that mortality increased in the presence of diabetes, malignancy, or three or more comorbidities [18]. Many studies show renal dysfunction is associated with poor prognosis and mortality[19].However, our study found no association between renal function and early or late mortality. When the relationship between acute phase reactants and mortality risk was analyzed, mortality risk increased 1-fold for each unit increase in CRP level, 1-fold for each 1 unit increase in ferritin level, 1-fold for each 1 unit decrease in lymphocyte level, and 1-fold for each 1 unit increase in LDH level. D-dimer, a marker of coagulation and inflammation, was found to be significantly higher in the deceased group compared to the survivors in the ANOVA test (p=0.000), but no statistical significance was found in the logistic regression analysis, a 1-fold increase in mortality was observed for each unit increase. Other studies in the literature have concluded that D-dimer and CRP may be important markers in monitoring disease activity [20]. In a meta-analysis, elevated serum CRP, procalcitonin, D-dimer, and ferritin levels were associated with severe disease, high mortality, ARDS, and increased need for intensive care [21]. Our study concluded that LDH, white blood cell, AST, ALT, platelet, D-dimer, CRP, ferritin, and INR levels among inflammatory markers were associated with mortality. In a cohort study by Henry et al., higher ferritin levels were found in patients who died, similar to our study [22]. In a meta-analysis conducted in China, it was emphasized that monitoring ferritin levels may be useful in recognizing patients who may have high mortality [23]. According to a study conducted in Wuhan, it was shown that patients with D-dimer levels higher than 2.0 ng mL-1 had a higher mortality rate than patients with values below 2.0 ng mL-1 [12]. The results prove that COVID-19 infection occurs with a coagulopathy problem that increases mortality characterized by procoagulant factors such as fibrinogen and high D-dimer levels [12]. In our study, similar to the literature, high ferritin and D-dimer levels increased mortality. In addition, low hemoglobin, low O2 saturation, and low electrolytes such as sodium and potassium were also found to be associated with mortality. In another study, hemoglobin levels below 11 g/dl were associated with disease progression in COVID-19 patients[24].A meta-analysis of a 2019 multicenter observational study of risk factors for disease progression in patients with mild to moderate coronavirus disease found results similar to those of our study[25].All assessments were based on hospital mortality. Data on 1-year mortality is limited.
Limitation
Due to the clinical and laboratory heterogeneity among the patient groups we compared, as well as the retrospective nature of our single-center study, it is important to note that our findings may not directly apply to other settings with different populations and case mixes.
Conclusion
Since there is no definitive cure for COVID-19, which poses a serious public health problem on a global scale, identifying the group of patients at risk for poor prognosis from the moment of admission is critical in managing the process. Awareness among physicians about post-discharge mortality predictors can help structure a follow-up program for discharged patients. Covid-19 is a viral infection, and the picture it creates is similar to pandemics and epidemics occurring at other times. Studies showing mortality risk factors in viral pneumonia over such a large number of patients will contribute to the literature.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy region, Italy. JAMA. 2020;323(16):1574–1581.
2. Schmidt M. Clinical characteristics and day-90 outcomes of 4244 critically ill adults with COVID-19: A prospective cohort study. Intensive Care Med. 2020;47(1):60–73.
3. Parohan M, Yaghoubi S, Seraji A, Javanbakht MH, Sarraf P, Djalali M. Risk factors for mortality in patients with Coronavirus disease 2019 (COVID-19) infection: A systematic review and meta-analysis of observational studies. Aging Male. 2020;23(5):1416-24.
4. Ramzi ZS. Hospital readmissions and post-discharge all-cause mortality in COVID-19 recovered patients; A systematic review and meta-analysis. Am J Emerg Med. 2021;51(1):267–279.
5. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med 2020;180(7):934-43.
6. Baud D, Qi X, Nielsen-Saines K, Musso D, Pomar L, Favre G. Real estimates of mortality following COVID-19 infection. Lancet Infect Dis 2020;20(7):773.
7. Meschiari M, Cozzi A, Tonelli R, Bacca E, Menozzi M, Franceschini E, et al. First and second waves among hospitalised patients with COVID-19 with severe pneumonia: A comparison of 28-day mortality over the 1-year pandemic in a tertiary university hospital in Italy. BMJ Open. 2022;12(1):54-69.
8. Chang R, Elhusseiny KM, Yeh YC, Sun WZ. COVID-19 ICU and mechanical ventilation patient characteristics and outcomes-A systematic review and meta-analysis. PloS One 2021;16(2):246-318.
9. Novelli L, Raimondi F, Carioli G, Carabbio A, Papacena S, Biza R, et al. One-year mortality in COVID-19 is associated with patients’ comorbidities rather than pneumonia severity. Respir Med Res. 2022;83(1):1-8.
10. Herridge MS, Cheung AM, Tansey CM, Matte-Martyn A, Diaz-Granados N, Al-Saidi F, et al. One-year outcomes in survivors of the acute respiratory distress syndrome. N Engl J Med. 2003;348(8):683–693.
11. Wang CY, Calfee CS, Paul DW, Janz DR, May AK, Zhuo H, et al. One-year mortality and predictors of death among hospital survivors of acute respiratory distress syndrome. Intensive Care Med. 2014;40(1):388–396.
12. Armstrong RA, Kane AD, Kursumovic E, Oglesby FC, Cook TM. Mortality in patients admitted to intensive care with COVID‐19: An updated systematic review and meta‐analysis of observational studies. Anaesthesia 2021;76(4):537-48.
13. Candaş A, Yucel B, Savaş MN. Proanthocyanidin reduces nitrogen mustard-induced lung injury. Gülhane Tıp Derg. 2008;50(4):267-72.
14. Conti P, Younes A. Coronavirus COV-19/SARS-CoV-2 affects women less than men: Clinical response to viral infection. J Biol Regul Homeost Agents 2020;34(2):339-43.
15. Pradhan A, Olsson PE. Sex differences in severity and mortality from COVID-19: Are males more vulnerable? Biol Sex Differ. 2020;11(1):53.
16. Grasselli G, Greco M, Zanella A, Albano G, Antonelli M,Bellani G, et al. Risk Factors Associated With Mortality Among Patients With COVID-19 in Intensive Care Units in Lombardy, Italy. Intern Med 2020;180(10):1345-55.
17. Alhakak A, Butt JH, Gerds TA, Mogensen MV, Kroll JPalligaard JL, et al. Glycated haemoglobin levels among 3295 hospitalized COVID-19 patients, with and without diabetes, and risk of severe infection, admission to an intensive care unit and all-cause mortality. Diabetes Obes Metab. 2022;24(3):499-510.
18. Ssentongo P, Ssentongo AE, Heilbrunn ES, Ba DM, Chinchilli VM. Association of cardiovascular disease and 10 other pre-existing comorbidities with COVID-19 mortality: A systematic review and meta-analysis. PLoS One. 2020;15(8):1-16.
19. Shao M, Li X, Liu F, Tian T, Luo J, Yang Y. Acute kidney injury is associated with severe infection and fatality in patients with COVID-19: A systematic review and meta-analysis of 40 studies and 24,527 patients. Pharmacol Res. 2020;161(1):105-107.
20. Valerio L, Ferrazzi P, Sacco C, Ruf W, Kucher N, Konstantinides SV, et al. Humanitas COVID-19 Task Force. Course of D-dimer and c-reactive protein levels in survivors and nonsurvivors with COVID-19 pneumonia: a retrospective analysis of 577 patients. ThrombHaemost. 2021;121(1):98-101.
21. Huang I, Pranata R, Lim MA, Oehadian A, Alisjahbana B. C-reactive protein, procalcitonin, D-dimer, and ferritin in severe coronavirus disease-2019: A meta-analysis. Ther Adv Respir Dis. 2020;14(2):1-14.
22. Henry BM, de Oliveira MHS, Benoit S, Plebani M, Lippi G. Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): A meta-analysis. Clin Chem Lab Med 2020;58(7):1021-8.
23. Cheng L, Li H, Li L, Liu C, Yan S, Chen S, et al. Ferritin in the coronavirus disease 2019 (COVID-19): A systematic review and meta-analysis. J Clin Lab Anal 2020;34(10):1-18.
24. Cen Y, Chen X, Shen Y, Zhang XH, Lei Y, Xu C, et al. Risk factors for disease progression in patients with mild to moderate coronavirus disease 2019-a multicenter observational study.Clin Microbiol Infect 2020;26(9):1242.
25. Kowsar R, Rahimi AM, Sroka M., Mansouri A, Sadeghi K, Bonakdar E, et al. Risk of mortality in COVID-19 patients: A meta-and network analysis. Scientific Reports, 2023;13(1):2138.
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Selvi Askar, Muntecep Askar, Mehmet Hakan Bilgin, Hanifi Yıldız, Rasa Beyzaei, Sıddık Keskin. Hospital and 1-Year mortality Outcomes in COVID-19 pneumonia. Ann Clin Anal Med 2024;15(5):334-338
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Evaluation of serum vitamin D levels in pregnant women with gestational diabetes mellitus
Narin Ece Çakmak 1, Burak Çakmak 1, Gül Özel Doğan 1, Alev Atış Aydın 2
1 Department of Obstetrics and Gynecology, 2 Department of Perinatology, Şişli Hamidiye Etfal Research and Training Hospital, İstanbul, Turkey
DOI: 10.4328/ACAM.22096 Received: 2024-01-15 Accepted: 2024-03-05 Published Online: 2024-03-21 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):339-343
Corresponding Author: Narin Ece Çakmak, Department of Obstetrics and Gynecology, Şişli Hamidiye Etfal Research and Training Hospital, 34470, İstanbul, Turkey. E-mail: rol.narinece@gmail.com P: +90 533 380 35 47 Corresponding Author ORCID ID: https://orcid.org/0000-0001-5497-4490
Other Authors ORCID ID: Burak Çakmak, https://orcid.org/0000-0001-8371-6183 . Gül Özel Doğan, https://orcid.org/0000-0001-9555-1128 Alev Atış Aydın, https://orcid.org/0000-0002-8504-5755
This study was approved by the Ethics Committee of Şişli Hamidiye Etfal Training and Research Hospital (Date: 2023-02-07, No: 3797)
Aim: This study aims to examine the association of maternal serum 25- (OH)Vitamin D concentrations with gestational diabetes mellitus.
Material and Methods: This single-centered and prospective study included 60 pregnant patients with a diagnosis of gestational diabetes who applied to our hospital between March 1, 2023, and June 1, 2023, for blood sugar monitoring or delivery. The study aslo included a total of 148 patients including pregnant women without gestational diabetes and female patients of similar age who were not pregnant as the control group. All patients ‘ demographic characteristics, pregnancy information, and medical histories were recorded. 25- (OH)Vitamin D levels were measured in serum samples taken from the patients.
Results: Serum 25-(OH) vitamin D levels were compared between pregnant women with gestational diabetes, pregnant women without gestational diabetes, and non-pregnant female patient groups of the same age. The mean 25-(OH) vitamin D level in the patient group with GDM (10.81±9.24), the mean (10.41±7.49) in the control group without GDM, and the mean in the non-pregnant control group female patients ( 11.56±7.25) (p= 0.203). Based on these results, there was no statistically significant difference between the groups’ 25-(OH) Vitamin D levels. Despite this, vitamin D deficiency was evident in all groups.
Discussion: Vitamin D deficiency is a critical health problem for mothers and newborns. The study investigates the impact of 25-(OH) vitamin D on gestational diabetes (GDM). Despite non-significant differences in vitamin D levels between GDM and healthy pregnant groups, the study highlights the prevalent deficiency across all groups, emphasizing the need for further investigation. In conclusion, the widespread vitamin D deficiency among young women and pregnant individuals calls for continued research to comprehend its implications for GDM.
Keywords: Gestational Diabetes, Vitamin D Deficiency, 25-Hydroxy Vitamin D, Oral Glucose Tolerance Test
Introduction
Gestational Diabetes Mellitus (GDM) is a medical condition affecting pregnant women, characterized by varying degrees of glucose intolerance. This condition poses risks to both the mother and the fetus, regardless of whether it is treated with dietary modifications or insulin therapy and even if it persists after pregnancy. The increasing prevalence of GDM over recent years has raised public health concerns.
Vitamin D is a fat-soluble vitamin critical in several physiological processes, including bone health [1]. However, recent studies suggest that vitamin D deficiency could contribute to the onset and progression of diabetes. Additionally, emerging evidence indicates that vitamin D deficiency could significantly impact the pathogenesis and management of GDM [2].
The present study aims to investigate the potential effects of vitamin D deficiency on GDM by comparing the serum vitamin D levels of GDM patients to those of healthy pregnant and non-pregnant women in the same age group. We also aim to emphasize the importance of routine evaluation of vitamin D levels during pregnancy assessments.
Furthermore, the study aims to identify the significance of preventive measures for GDM during pregnancy. By conducting a comprehensive review of existing literature and assessing current evidence, we hope to provide insights into the potential clinical outcomes associated with vitamin D deficiency in the context of gestational diabetes mellitus.
Material and Methods
Selection and Description of Participants
Our study, conducted between Mar 1, 2023, and Jun 1, 2023, included 60 pregnant patients diagnosed with gestational diabetes mellitus at the Şişli Hamidiye Etfal Training and Research Hospital’s Obstetrics and Gynecology Clinic. Additionally, 88 pregnant individuals without gestational diabetes mellitus, matched for age, and 60 non-pregnant women were selected as the control group to compare serum D vitamin levels. Demographic details such as age, gravidity, parity, week of admission, indication for admission, and BMI were obtained from the hospital’s electronic file system and through detailed patient history.
All participants were provided comprehensive information about the study, and verbal consent was obtained.
Inclusion Criteria
– Pregnant individuals aged 18-40 years.
– İndividuals for whom clear information is accessible through file screening, as well as Oral Glucose Tolerance Test results available between the 24th and 28th weeks of pregnancy.
Control Group Criteria
– Pregnant individuals with normal Oral Glucose Tolerance Test results who were admitted for childbirth or pregnancy follow-up.
– Non-pregnant women aged 18-40 years who visit the hospital’s outpatient clinic.
Exclusion Criteria
– Pregnant individuals aged below 18 or above 40 who are admitted for childbirth or pregnancy follow-up.
– Pregnant individuals who did not undergo the Oral Glucose Tolerance Test between the 24th and 28th weeks of pregnancy.
– Patients with incomplete information in the hospital electronic file system.
– Patients with known diagnosis of diabetes before pregnancy.
– Patients who use medications affecting calcium and vitamin D metabolism during pregnancy (excluding routine prenatal multivitamins).
– Patients with chronic diseases related to thyroid, parathyroid, or kidney.
– Patients with multiple pregnancies.
Technical Information
The study utilized a 75-gram Oral Glucose Tolerance Test for gestational diabetes mellitus diagnosis. Testing appointments were scheduled for patients in their 24-28th weeks of pregnancy. After 12 hours of fasting, blood samples were taken for fasting serum glucose. Subsequently, patients ingested a 75-gram glucose solution, and blood samples were collected at 1 and 2 hours post-ingestion.
OGTT Cut-off Values
Fasting: 92,
1st Hour: 180,
2nd Hour: 153.
Venous blood samples for D vitamin determination were centrifuged and stored at -80°C until analysis. D vitamin levels were measured using a chemiluminescent immunoassay with the Centaur XP (Siemens Healthcare United Kingdom) device. Cutoff values for D vitamin levels were defined as follows:
<12: D vitamin deficiency,
12-20: D vitamin insufficiency,
>20: Adequate D vitamin levels.
Statistics
Statistical analysis was performed using SPSS 15.0 for Windows. Descriptive statistics included counts and percentages for categorical variables and mean, standard deviation, minimum, maximum, and median for numerical variables. Due to the non-normal distribution of numerical variables, the Mann-Whitney U and Kruskal-Wallis tests were used for independent two-group and multiple-group comparisons. Subgroup analyses were conducted using the Mann-Whitney U test with Bonferroni Correction. Proportions in groups were compared using the Chi-square test. ROC Curve analysis was employed for threshold value assessments. The statistical significance level was set at p<0.05.
Ethical Approval
This study was approved by the Ethics Committee of Şişli Hamidiye Etfal Training and Research Hospital (Date: 2023-02-07, No: 3797)
Results
The study included 56 pregnant women diagnosed with gestational diabetes mellitus (GDM), 82 healthy pregnant women, and 58 healthy non-pregnant women, all subjects for comparison based on 25-(OH) D vitamin levels.
The mean age of the GDM group was statistically lower than that of the control group (p=0.037), and the parity number was significantly reduced compared to the control group (p=0.020). The Cesarean section rate in the GDM group was higher than in the control group.
Statistical analysis revealed significant differences in various parameters among the GDM, OGTT normal pregnant, and Control groups. These included age, gravida, parity, abortion numbers, mode of delivery, the week when GDM diagnosis was established, and the week of hospitalization (p=0.001, p=0.028, p=0.018, p=0.016, p=0.009, p=0.033, p=0.009, p<0.001, p<0.001, p<0.001).
The average age of the OGTT normal pregnant group was statistically lower than the GDM and control groups (p=0.002).
Regarding gravida, the GDM group had a significantly higher average than the control group. Parity in the OGTT normal pregnant group was statistically lower than in the control group, and the GDM group’s abortion average was significantly higher than the OGTT normal pregnant group (p=0.021, p=0.009, p=0.005).
The week of OGTT in the GDM group was statistically later than in the OGTT normal group. The week of hospitalization in the GDM group was lower than the OGTT normal pregnant group. OGTT 0-60-120 min blood sugar averages were higher in the GDM group compared to the OGTT normal pregnant group.
No statistically significant differences were found in the average serum D vitamin levels and the ratio of D vitamin <20 among groups (p=0.203, p=0.689). Additionally, no significant differences were observed in vitamin D levels and BMI.
In the OGTT normal pregnant group, the serum D vitamin level showed a very weak positive correlation with the patient’s age and a very weak negative correlation with the week of hospitalization during pregnancy. In the GDM group, a moderately positive correlation was found between OGTT 60 min level and serum D vitamin. In the OGTT normal pregnant group, a very weak negative correlation was observed between the week of prenatal hospitalization and serum D vitamin (p=0.037, p=0.042, p=0.035, p=0.032).
Discussion
Gestational Diabetes (GDM) is a carbohydrate intolerance that begins or is first noticed during pregnancy. In addition to affecting approximately 14% of the entire pregnant population, it is crucial to know maternal and fetal complications and to investigate protective mechanisms that can be prevented. To examine the role of 25-(OH) vitamin D in the pathogenesis of GDM during pregnancy, to identify patients in the risk group, and to improve pregnancy outcomes, we planned to investigate the importance of 25-(OH) vitamin D supplementation and shed light on future studies with the results we found.
Studies conducted in healthy individuals have shown an inverse relationship between serum 25-(OH) Vitamin D level, glucose concentration, and insulin resistance [3]. In the study by Agarval et al., the relationship between serum 25-(OH) Vitamin D levels and insulin resistance was examined in 71 non-diabetic postmenopausal women; there was a negative correlation between insulin resistance (HOMA-IR; homeostasis model assessment of insulin resistance) and 25-(OH) Vitamin D [4]. Additionally, observational studies have found an association between vitamin D levels and Type 2 DM. In a meta-analysis of 21 prospective studies evaluating the relationship between serum 25-(OH) Vitamin D levels and the incidence of type 2 DM, it was stated that there was a negative and positive relationship between serum 25-(OH) Vitamin D and the incidence of Type 2 DM [5].
One of the most critical risk factors for the development of GDM and Type 2 DM is obesity. Obesity has also been associated with hypovitaminosis D. This can be explained by the fact that vitamin D cannot be converted into its active form because it is stored in fat tissue.
In a study evaluating the relationship between serum 25-(OH) Vitamin D levels and insulin resistance in healthy overweight and obese individuals, serum 25-(OH) Vitamin D levels and Body Mass Index (BMI), waist circumference, fasting plasma insülin, and HOMA-IR values are in a negative relationship, and it has been determined that low serum 25-(OH) Vitamin D levels in obese individuals are responsible for insulin resistance or hyperinsulinemia [6]. Our study did not find a statistically significant relationship between the patient and control groups’ vitamin D levels and BMI parameters.
In the study conducted by Lacroix et al., which included 655 pregnant women, 25-(OH) Vitamin D levels were measured in the first trimester, and blood glucose and insulin values were examined in the second trimester. Based on IADPSG criteria, GDM was detected in 8.2% of the participants. Low vitamin D levels in the first trimester were found to be significantly associated with the development of GDM, and vitamin D deficiency was interpreted as an essential factor in the development of GDM [7].
According to the meta-analysis by Zhang et al., pregnant women with maternal GDM had statistically significantly lower vitamin D levels compared to other healthy pregnant women. Still, it was also emphasized that there would be regional differences [8]. Similar to this meta-analysis, studies conducted in healthy individuals in the literature have shown an inverse relationship between serum 25-(OH) Vitamin D level, glucose concentration, and insulin resistance [9]. It has also been shown in further studies that vitamin D has a role in the pathogenesis of diabetes. In a cross-sectional survey of Soheilykhah et al., 24-28. Serum 25-(OH) Vitamin D levels were lower in GDM women than in non-diabetic pregnant women during the gestational weeks [10].
In another study by Clifton-Bligh et al., maternal serum 25-(OH) Vitamin D concentrations measured during GDM screening testing were significantly and inversely associated with fasting glucose. Still, the association of vitamin D with GDM risk was not statistically significant.
Again, as a result of a study conducted by Farrant and colleagues in an Indian population, it was revealed that there was no significant relationship between 25-(OH) Vitamin D concentrations and GDM risk [13]. Our findings are also compatible with these two studies.
In a study conducted by Parildar et al. to evaluate the frequency of vitamin D deficiency in pregnant women and the relationship of vitamin D deficiency with glucose parameters and the incidence of gestational diabetes, 42 pregnant women with GDM and 78 pregnant women without GDM were evaluated. Serum 25-(OH) Vitamin D levels of all individuals were assessed, and serum 25-(OH) Vitamin D level <20 ng/mL was determined as vitamin D deficiency [12]. The prevalence of vitamin D deficiency in the women with GDM and the control group participating in the study was statistically significantly different. In individuals with GDM (n=42), no significant difference was detected between the fasting plasma glucose, fasting insulin, and HbA1c levels of the group with and without vitamin D deficiency.
In a study conducted in the Istanbul region, the average vitamin D level in 44 pregnant women in the first three months of pregnancy was 11.1±3.80 ng/mL. Vitamin D was found below 10 ng/ml in 70.45% of the cases [11].
According to the results of our study, serum vitamin D levels were not different in the three groups (p = 0.203). However, vitamin D levels were found to be deficient in healthy pregnant women (mean±SD; 10.1±7.49 µg/L), gestational diabetic pregnant women (10.81±9.24 µg/L), and healthy young women (11.56±7.25 µg/L), that is, in all groups ( Table 1). 25-(OH) vitamin D level; Deficiency (≤12 µg/L) was found in 71% of pregnant women with GDM, insufficiency (12-20 µg/L) in 13%, and sufficiency (20-32 µg/L) in 14%. Healthy pregnant women: It was found to be deficient in 69%, insufficient in 18%, and at the proficiency level in 12%. Healthy young women were found to be deficient in 62%, inadequate in 26%, and at a sufficient level in 11% (Table 1).
In studies conducted on 559 pregnant women in India and 76 pregnant women in the Czech Republic, vitamin D levels were not found to be different in gestational diabetic pregnant women and healthy pregnant women. In contrast, vitamin D levels were found to be deficient in both groups of pregnant women [11].
Similar to all these results, while we could not find a statistically significant difference in vitamin D levels between the gestational diabetic and the healthy pregnant groups, we detected a high rate of vitamin D deficiency in both groups. In this study, we found vitamin D levels deficient in healthy pregnant women, gestational diabetic pregnant women, and healthy young women, that is, in all groups. This study revealed that vitamin D deficiency is common in our region as well as all over the world and in our country. While severe (≤12 µg/L) vitamin D deficiency is observed in 70% of pregnant women with GDM and healthy pregnant women and in 62% of healthy young women, Vitamin D deficiency (12-20 µg/L) in all groups averaged 19%. The average number of women with adequate vitamin D levels (20-32 µg/L) in all three groups is 12%. In light of these results, we see that vitamin D deficiency is a noticeable problem in both pregnant and non-pregnant women.
Limitation
As a few limitations of our study, serum 25-(OH) Vitamin D concentrations taken in the late trimester may not indicate maternal vitamin D status throughout the entire pregnancy period and, therefore, may be misleading in determining the relationship between the development of GDM and vitamin D status. In addition, another limitation was that we needed more patients and control groups compared to studies on similar subjects.
As a result of this study, we attributed the lack of a significant difference in vitamin D deficiency in patients with and without GDM to the high prevalence of Vitamin D deficiency. We attributed the frequent occurrence of vitamin D deficiency to the geographical characteristics of our country.
Conclusion
As a result, vitamin D deficiency is widespread in young women and all pregnant women. It is associated with many complications, such as preeclampsia, gestational diabetes, premature birth, impaired glucose tolerance, and increased cesarean section rate. Although the importance of multivitamin supplementation during pregnancy is evident, more studies are needed to reveal the relationship between the effect of vitamin D deficiency on the development of gestational diabetes.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Kampmann U, Madsen LR, Skajaa GO, Iversen DS, Moeller N, Ovesen P. Gestational diabetes: A clinical update. World J Diabetes. 2015;6(8):1065-72.
2. McIntyre HD, Catalano P, Zhang C, Desoye G, Mathiesen ER, Damm P. Gestational diabetes mellitus. Nat Rev Dis Primers. 2019,11;5(1):47.
3. Poel YH, Hummel P, Lips P, Stam F, van der Ploeg T, Simsek S. Vitamin D, and gestational diabetes: A systematic review and meta-analysis. Eur J Intern Med. 2012;23(5):465-9.
4. Agarwal N, Mithal A, Kaur P, Dhingra V, Godbole MM, Shukla M. Vitamin D and insulin resistance in postmenopausal Indian women. Indian J Endocrinol Metab. 2014;18(1):89-93.
5. Song Y, Wang L, Pittas AG, Del Gobbo LC, Zhang C, Manson JE, Hu FB. Blood 25-hydroxy vitamin D levels and incident type 2 diabetes: A meta-analysis of prospective studies. Diabetes Care. 2013;36(5):1422-8.
6. De Pergola G, Nitti A, Bartolomeo N, Gesuita A, Giagulli VA, Triggiani V, Guastamacchia E, Silvestris F. Possible role of hyperinsulinemia and insulin resistance in lower vitamin D levels in overweight and obese patients. Biomed Res Int. 2013;2013:921348.
7. Lacroix M, Battista MC, Doyon M, Houde G, Ménard J, Ardilouze JL, Hivert MF, Perron P. Lower vitamin D levels in the first trimester are associated with a higher risk of developing gestational diabetes mellitus. Acta Diabetol. 2014;51(4):609-16.
8. Zhang Y, Gong Y, Xue H, Xiong J, Cheng G. Vitamin D, and gestational diabetes mellitus: A systematic review based on data free of Hawthorne effect. BJOG. 2018;125(7):784-793.
9. Tai K, Need AG, Horowitz M, Chapman IM. Vitamin D, glucose, insulin, and insulin sensitivity. Nutrition. 2008;24(3):279-85.
10. Soheilykhah S, Mojibian M, Rashidi M, Rahimi-Saghand S, Jafari F. Maternal vitamin D status in gestational diabetes mellitus. Nutr Clin Pract. 2010;25(5):524-7.
11. Farrant HJ, Krishnaveni GV, Hill JC, Boucher BJ, Fisher DJ, Noonan K, Osmond C, Veena SR, Fall CH. Vitamin D insufficiency is common in Indian mothers but is not associated with gestational diabetes or variation in newborn size. Eur J Clin Nutr. 2009;63(5):646-52.
12. Parildar H, Dogruk Unal A, Aksan Desteli G, Cigerli O, Guvener Demirag N. Frequency of Vitamin D deficiency in pregnant diabetics at Baskent University Hospital, Istanbul. Pak J Med Sci. 2013;29(1):15-20.
13. Clifton-Bligh RJ, McElduff P, McElduff A. Maternal vitamin D deficiency, ethnicity and gestational diabetes. Diabet Med. 2008;25(6):678-84.
Download attachments: 10.4328.ACAM.22096
Narin Ece Çakmak, Burak Çakmak, Gül Özel Doğan, Alev Atış Aydın. Evaluation of serum vitamin D levels in pregnant women with gestational diabetes mellitus. Ann Clin Anal Med 2024;15(5):339-343
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Examination of the relationship between variants in the gene region encoding soluble epoxy hydrolase enzyme hydrolytic activity and type 2 diabetes
Esma Özmen 1,6, Durmuş Ayan 1, Çağatay Emir Önder 2, Dilara Fatma Akın 3, Burcu Köse 4, İsmail Sarı 5, Cevat Yazıcı 6
1 Department of Biochemistry, Faculty of Medicine, Niğde Ömer Halisdemir University, Niğde, 2 Department of Endocrinology, Ankara Training and Research Hospital, Health Scıences Unıversıty, Ankara, 3 Department of Biology, Faculty of Medicine, Nigde Omer Halisdemir University, Nigde, 4 Department of Biotechnology, Faculty of Science Literature, Nigde Omer Halisdemir University, Nigde, 5 Department of Biochemistry, Faculty of Medicine, Kırklareli University, Kırklareli, 6 Department of Biochemistry, Faculty of Medicine, Erciyes University, Kayseri, Turkey
DOI: 10.4328/ACAM.22100 Received: 2024-01-09 Accepted: 2024-02-29 Published Online: 2024-03-29 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):344-349
Corresponding Author: Esma Ozmen, Department of Medical Biochemistry, Faculty of Medicine, Niğde Ömer Halisdemir University, 51240, Niğde, Turkey. E-mail: ozmenesma07@gmail.com P: +90 530 960 81 03 Corresponding Author ORCID ID: https://orcid.org/0000-0003-3223-6854
Other Authors ORCID ID: Durmuş Ayan, https://orcid.org/0000-0003-2615-8474 . Çağatay Emir Önder, https://orcid.org/0000-0002-0293-2309 . Dilara Fatma Akin, https://orcid.org/0000-0002-0903-0017 . Burcu Köse, https://orcid.org/0000-0003-1068-0196 . İsmail Sari, https://orcid.org/0000-0003-3732-2102 . Cevat Yazici, https://orcid.org/0000-0003-0625-9542
This study was approved by the Ethics Committee of Niğde Ömer Halisdemir University Non-Interventional (Date: 2022-12-22, No: 2022/116)
Aim: Epoxyeicosanoids function as signal mediators in critical biological processes such as platelet aggregation, vasodilation, and anti-inflammation. With all these properties, Epoxyeicosanoids have been associated with many diseases. Metabolism of epoxyeicosanoids is carried out by soluble epoxide hydrolase enzymes, and as a result dihydroxyeicosatrienoic acids, which is a less active form than epoxyeicosanoids, are formed. In our study, SNP/mutation analysis was performed in the gene region responsible for the hydrolase activity of EPHX2, which encodes the soluble epoxide hydrolase enzyme.
Material and Methods: The study consisted of two groups: a healthy group with 30 individuals and a T2DM patient group with 40 individuals. SNP/mutation analysis in the gene region responsible for the hydrolase activity of EPHX2 in both groups was performed by Sanger sequencing using appropriate primers.
Result: A total of 12 mutations were detected in both groups as a result of Sanger sequencing. Two of the 12 detected mutations were missense mutations (p.Asn359Thr and p.Ser412Arg). It was determined that the pathogenic scores of these mutations were close to 1 for Poly-Phen2 and 0-100 for SNAP. In addition, two (c.1058+165C>T and c.1058+146G>A) SNPs were detected in the intron we observed in the T2DM group, which has not been detected and defined before in our study.
Discussion: We believe that the mutations detected in our study, especially those that cause amino acid changes, may cause T2DM susceptibility in healthy individuals and progression of the disease pathogenesis in the T2DM group. We think that the detection of c.1058+165C>T and c.1058+146G>A mutations for the first time in our study will guide the next studies.
Keywords: T2DM, Mutation, sEH, EPHX2
Introduction
Eicosatrienoic acids (EETs), critical signaling molecules in the organism, are derived from arachidonic acid [1, 2] Produced through the Cytochrome P450 (CYP450) pathway, EETs are defined as hyperpolarizing factors derived from the endothelium. Mammals have four EET isomers with distinct biological functions: 5,6-EET, 8,9-EET, 11,12-EET, and 14,15-EET [2–4]. The conversion of EETs to their less active forms, dihydroxyeicosatrienoic acids (DHETs), occurs through a two-step reaction catalyzed by soluble epoxide hydrolases (sEH). Eicosanoids have been identified as influential factors in the development of inflammatory, renal, and cardiovascular diseases. However, studies are scarce regarding the effects of EETs, products of the CYP450 pathway, on the pathogenesis of diabetes mellitus (DM)[5–7]. Considering both Type I diabetes mellitus (T1DM) and Type II diabetes mellitus (T2DM) as diseases developed due to insufficient functional beta-cell mass, we believe that detailed studies elucidating the precise mechanisms of action of potential molecules like EETs, effective in increasing beta-cell mass and/or improving beta-cell function, could pave the way for new strategies in diabetes treatment [5,8]. In this study, to gain a better understanding of the EET metabolism in Type 2 diabetes mellitus (T2DM), the comprehensive screening of de novo mutations and/or single nucleotide polymorphisms (SNPs) in the alpha/beta hydrolase domain responsible for the enzyme’s hydrolytic activity of the EPHX2 gene was aimed through DNA sequence analysis. This thorough examination sought to illuminate the relationship between EPHX2 and T2DM by investigating mutations/SNPs.
Material and Methods
The Formation of Patient and Control Groups
The number of individuals in the groups for the planned sequence analysis was determined using the OSSE (Online Sample Size Estimator) program. The control group consisted of 30 people, and the Type 2 Diabetes Mellitus (T2DM) group (patients) consisted of 40 people.
DNA Isolation from Blood Samples
DNA isolation from samples of the patient and control groups was conducted using the Blood DNA Isolation Kit with Catalog number MG-KDNA-02 (Hibrigen, TR), following the protocol recommended by the manufacturer.
Polymerase Chain Reaction (PCR) and Sanger DNA Sequencing Analysis
The sequence information of the EPHX2 gene was amplified by PCR for 30 cycles using the primers specified in Table 1.The PCR mixture and PCR protocol used for amplification are summarized in Table 1. A PCR cycling program was used for PCR amplification.
Sanger DNA Sequencing and Identification of Potential Mutations/SNPs
The DNA samples isolated from T2DM and control group were subjected to Sanger’s enzymatic method for sequence analysis. The results were visualized as electropherograms using software, and the analysis was conducted with Chromas 2.6.5 Technelsium DNA Sequencing Software.
In-Silico Analysis of Detected Variants for Pathogenic Effects and Evolutionary Analysis Across Species
To determine the potential pathogenicity of the identified mutations, scores provided by the PolyPhen-2(http://genetics.bwh.harvard.edu/pph2/),SNAP (https://www.rostlab.org/services/SNAP/), and the Catalogue Of Somatic Mutations In Cancer (COSMIC) (https://cancer.sanger.ac.uk/cosmic) (23-25) databases, accessible online, were utilized. The likelihood scores were used to determine whether each mutation was benign or pathogenic.
Functional/Pathogenic Effect Analysis of Detected Mutations/SNPs
Variants identified in the EPHX2 gene were assessed for their potential pathogenicity and clinical features using scores provided by the Polymorphism Phenotyping v2 (PolyPhen-2), SIFT, and SNAP databases, both in vivo and in vitro. Additionally, the Mutation Taster application, utilizing a Bayesian classifier to predict the disease potential of a change, was employed. For demonstrating the extent to which potential variants/mutations would affect the three-dimensional configuration of the protein, the SWISS-MODEL, an integrated web-based service dedicated to protein structure homology modeling, was used. STRING database, assessing protein-protein interaction information, was employed for protein-protein interaction analysis by generating different structural homology models for wild type and mutant. This allowed the evaluation of direct (physical) and indirect (functional) relationships among proteins in the pathway where the EPHX2 protein is present.
Statistical Analysis
In our study, statistical analysis was conducted by loading the data into the SPSS 14.0 program. Normality analysis was performed using the Kolmogorov-Smirnov Test. Data showing conformity to normal distribution were analyzed using one-way ANOVA, while data not conforming to normal distribution were analyzed using the Mann-Whitney U test.
Ethical Approval
This study was approved by the Ethics Committee of Niğde Ömer Halisdemir University Non-Interventional (Date: 2022-12-22, No: 2022/116).
Results
Patient Information
The study groups were composed of individuals with similar age and gender characteristics who applied to the Department of Endocrinology and Metabolic Diseases at T.C.S.B. Niğde Ömer Halisdemir University Training and Research Hospital. As shown in Table 2, the control group included a total of 30 individuals, with 13 females and 17 males. The patient group included a total of 40 individuals, with 17 females and 23 males. There was no statistically significant difference in gender between the groups (p > 0.05). The mean age of the control group was determined to be 49.3 ± 1.2, and the mean age of the T2DM group was 61 ± 1.3. It was observed that the age of the T2DM patient group was higher compared to the control group, and this difference was statistically significant (p < 0.05). The average HbA1c was 5.6 ± 0.5 in the control group and 10.7 ± 2.8 in the T2DM group. The elevated HbA1c in the T2DM group was found to be statistically significant. The fasting serum glucose (FSG) levels for the control and T2DM groups were 82.93 ± 2 and 158.7 ± 12.6, respectively. It was observed that the FSG level in the T2DM group was higher than the control group, and this difference was statistically significant (p < 0.05)( Table 2).
Results of Sanger DNA Sequencing Analysis
The obtained PCR amplicons were submitted to the relevant service provider for Sanger DNA sequencing analysis. The capillary system automatic sequencing instrument ABI-3100 Applied Biosystem was utilized for DNA sequencing, and the results were visualized as electropherograms using software programs. The obtained data were analyzed using Chromas 2.6.5 Technelsiyum DNA Sequencing Software. Sequence analysis images for the T2DM and Control groups are respectively presented in Figures 1 and 2.
EPHX2 Analysis
Our study group was formed based on the criteria of the International Diabetes Federation, HbA1c, and fasting blood glucose values, consisting of a control group (n=30) and a T2DM group (n=40). A total of 12 mutations were detected in both groups (Table 3). The characteristic features of the identified mutations are presented in Table 3. Four mutations were observed in the control group, and two missense mutations were identified in the T2DM group. One exon variant was found in both groups, with 3 in the T2DM group and 14 in the control group in intron variants. When analyzed for all mutations, the control group exhibited a statistically significant higher number of mutations compared to the T2DM group.
Results of In-Silico Analysis of Detected Variant Pathogenic Effects and Evolutionary Analysis Across Species
Figure 3. As depicted in A and B, the analysis results from Poly-Phen2 and SNAP Database Programs indicate that 2 missense mutations (EPHX2; p.Asn359Thr, p.Ser412Arg) among the 12 mutations identified in our study have pathogenic scores close to 1 for Poly-Phen2 and within the range of 0-100 for SNAP. Variants with an “affected” feature are predicted to possess pathogenic characteristics and may contribute to susceptibility to the disease. Additionally, the missense mutations identified were analyzed for amino acid sequence conservation across different species using the “Multiple sequence alignment” option within the Poly-Phen2 program. This analysis revealed that the two identified missense mutations altered crucial amino acids that have been conserved throughout evolutionary processes across different species. The location of these mutations, Ser412Arg and Asn359Thr, in the α/β hydrolase domain.
Discussion
In light of the data obtained in our study, our first noteworthy result is the identification of two mutations in the gene sequence responsible for the hydrolase activity of the sEH enzyme encoded by the EPHX2 gene, leading to amino acid changes. Our second finding, which we believe will capture the attention of researchers, is the discovery of two novel mutations in the EPHX2 gene, not previously identified in this study.
The relationship between EET metabolism and diabetes has been predominantly explored in studies focusing on sEH enzyme inhibition. In this study, the gene region responsible for the hydrolase activity of the EPHX2 gene encoding the sEH enzyme was comprehensively screened. A total of 12 mutations were identified in both groups, with 4 occurring in exons and 8 in introns. In our study, two mutations causing amino acid changes in the exon of the domain were identified in both the T2DM and control groups. Previous studies revealed no Ser412Arg (rs13439459) mutation detected in both control and T2DM patient groups. This SNP in exon 13 resulted in the conversion of serine amino acid at position 412 to arginine. Additionally, an Asn359Thr (rs764879647) mutation causing amino acid change, not previously identified, was detected in the control group in our study [9]. In animal models, a missense mutation (RS751141G>A) in the 8th exon of the EPHX2 gene has been identified, leading to a substitution of arginine at position 287 with glycine. This alteration has been demonstrated to result in a significant decrease of approximately 25-58% in in vitro sEH activity compared to the wild-type sEH enzyme [10,11]. This finding is consistent with the proposed impact of decreased sEH activity on EET levels and bioavailability [12]. When examining the possible functional effects of the identified Ser412Arg and Asn359Thr mutations using PolyPhen2, both mutations causing amino acid changes were observed to have a score close to 1, indicating potential deleterious effects. These mutations are located in the C-terminal hydrolase domain of the gene, which encompasses amino acids 235-555, forming a classical α/β hydrolase fold. Consequently, we hypothesize that these mutations may alter the enzyme’s substrate efficiency or hydrolysis mechanism, either enhancing or reducing the enzyme’s activity. Considering that the primary function of sEH enzyme is thought to convert endogenous epoxides (EETs) into biologically inactive DHETs, these mutations are likely to impact EET levels, contributing to the pathogenesis of various diseases in the organism. In our study, we identified a Ser412Arg mutation in both the T2DM and control groups. This mutation leads to the conversion of serine to arginine at position 412 of the enzyme. Additionally, a novel mutation, Asn359Thr, causing an amino acid change, was detected in the control group, which has not been previously reported. As these mutations have not been observed before, their specific impact on the enzyme is currently unknown. To comprehensively understand their effects, it would be appropriate to first investigate the activities of wild-type sEH and mutant sEH enzymes in vitro. Furthermore, we identified two intronic SNPs (c.1058+165C>T and c.1058+146G>A) in the T2DM group, which have not been reported previously. Due to the lack of prior detection, the effects of these SNPs on the enzyme remain uncertain. Comparisons with other studies indicate that the EPHX2 gene region has 13 SNPs in the protein-coding region, with only six (K55R, Cys154Tyr, Arg287Gln, Glu470Gly, Arg103Cys, and Val422Ala) causing amino acid changes. Among these, Arg287Gln, Val422Ala, and Glu470Gly are located in the hydrolase domain of the enzyme [13,14]. Notably, the Arg287Gln variant has been associated with various diseases and demonstrated protective effects. Given the occurrence of Ser412Arg and Asn359Thr mutations in the C-terminal hydrolase domain, where Arg287Gln also resides, it is essential to thoroughly investigate the impact of these mutations on enzyme activity and explore their functional significance through more extensive studies. Moreover, we compared the effects of these variations with a known polymorphism, K55R (9780A>G; Lys55Arg; rs41507953), located in the phosphatase domain. Similar to mutations in the hydrolase domain, the K55R polymorphism has been reported to cause changes in sEH activity. Additionally, the K55R variant, along with Arg287Gln (R287Q) polymorphism and Arg402–403 insertion, has been linked to altered enzyme activity, with K55R causing an increase in sEH activity, while Arg287Gln (R287Q) and Arg402–403 insertion resulted in decreased enzyme activity. Various polymorphisms in the EPHX2 gene, including K55R, Arg103Cys, Cys154Tyr, and Arg287Gln variants, have been shown to exhibit lower phosphatase activity [15] and, in the case of K55R and Cys154Tyr variants, higher hydrolase activity [10]. When examining the possible functional effects of the identified Ser412Arg and Asn359Thr mutations using PolyPhen2, both mutations causing amino acid changes were observed to have a score close to 1, indicating potential deleterious effects. These mutations are located in the C-terminal hydrolase domain of the gene, which encompasses amino acids 235-555, forming a classical α/β hydrolase fold. Consequently, we hypothesize that these mutations may alter the enzyme’s substrate efficiency or hydrolysis mechanism, either enhancing or reducing the enzyme’s activity. Considering that the primary function of sEH enzyme is thought to convert endogenous epoxides (EETs) into biologically inactive DHETs, these mutations are likely to impact EET levels, contributing to the pathogenesis of various diseases in the organism.
In our study, we identified a Ser412Arg mutation in both the T2DM and control groups. This mutation leads to the conversion of serine to arginine at position 412 of the enzyme. Additionally, a novel mutation, Asn359Thr, causing an amino acid change, was detected in the control group, which has not been previously reported. As these mutations have not been observed before, their specific impact on the enzyme is currently unknown. To comprehensively understand their effects, it would be appropriate to first investigate the activities of wild-type sEH and mutant sEH enzymes in vitro. Furthermore, we identified two intronic SNPs (c.1058+165C>T and c.1058+146G>A) in the T2DM group, which have not been reported previously. Due to the lack of prior detection, the effects of these SNPs on the enzyme remain uncertain. Comparisons with other studies indicate that the EPHX2 gene region has 13 SNPs in the protein-coding region, with only six (K55R, Cys154Tyr, Arg287Gln, Glu470Gly, Arg103Cys, and Val422Ala) causing amino acid changes. Among these, Arg287Gln, Val422Ala, and Glu470Gly are located in the hydrolase domain of the enzyme. Notably, the Arg287Gln variant has been associated with various diseases and demonstrated protective effects. Moreover, we compared the effects of these variations with a known polymorphism, K55R (9780A>G; Lys55Arg; rs41507953), located in the phosphatase domain. Similar to mutations in the hydrolase domain, the K55R polymorphism has been reported to cause changes in sEH activity.
Conclusion
In our study, significant mutations/SNPs were identified in the sEH enzyme responsible for the metabolism of important metabolites of the CYP450 pathway, namely EETs. The detailed investigation of the role of these mutations and SNPs in the development of diabetes is evidently warranted. However, the limitation of our study lies in the relatively small population size of both the patient and control groups. Based on the data obtained from this study, future research plans involve conducting a comprehensive mutation/SNP screening in a larger patient population with a high incidence, allowing for an extensive exploration of its impact on enzyme activity. Consequently, the role of the sEH enzyme in diabetes can be thoroughly examined at both the genetic and biochemical levels.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: This work was supported by TUBITAK (The Scientific andTechnological Research Council of Turkey) under grand number 222S679.
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Bosma KJ, Kaiser CE, Kimple ME, Gannon M. Effects of arachidonic acid and its metabolites on functional beta-cell mass. Metabolites. 2022;12(4):342.
2. Harder DR, Rarick KR, Gebremedhin D, Cohen SS. Regulation of cerebral blood flow: Response to cytochrome P450 lipid metabolites. Compr Physiol. 2011;8(2):801-21.
3. Tacconelli S, Patrignani P. Inside epoxyeicosatrienoic acids and cardiovascular disease. Front Pharmacol. 2014;5:239.
4. Imig JD. Epoxides and soluble epoxide hydrolase in cardiovascular physiology. Physiol rev. 2012;92(1):101-30.
5. Grimes D, Watson D. Epoxyeicosatrienoic acids protect pancreatic beta cells against pro-inflammatory cytokine toxicity. Biochem Biophys Res Commun. 2019;520(2):231-6.
6. Falck JR, Manna S, Moltz J, Chacos N, Capdevila J. Epoxyeicosatrienoic acids stimulate glucagon and insulin release from isolated rat pancreatic islets. Biochem Biophys Res Commun. 1983;114(2):743-9.
7. Xu X, Zhao CX, Wang L, Tu L, Fang X, Zheng C, et al. Increased CYP2J3 expression reduces insulin resistance in fructose-treated rats and db/db mice. Diabetes. 2010;59(4):997-1005.
8. Tunaru S, Bonnavion R, Brandenburger I, Preussner J, Thomas D, Scholich K, et al. 20-HETE promotes glucose-stimulated insulin secretion in an autocrine manner through FFAR1. Nat Commun. 2018;9(1):177.
9. Imig JD, Hammock BD. Soluble epoxide hydrolase as a therapeutic target for cardiovascular diseases. Nat Rev Drug Discov. 2009;8(10):794-805.
10. Przybyla-Zawislak BD, Srivastava PK, Vázquez-Matías J, Mohrenweiser HW, Maxwell JE, Hammock BD, et al. Polymorphisms in human soluble epoxide hydrolase. Mol Pharm. 2003;64(2):482-90.
11. Koerner IP, Jacks R, DeBarber AE, Koop D, Mao P, Grant DF, et al. Polymorphisms in the human soluble epoxide hydrolase gene EPHX2 linked to neuronal survival after ischemic injury. J.Neurosci. 2007;27(17):4642-9.
12. Can Demirdöğen B, Miçooğulları Y, Türkanoğlu Özçelik A, Adalı O. Missense genetic polymorphisms of microsomal (EPHX1) and soluble epoxide hydrolase (EPHX2) and their relation to the risk of large artery atherosclerotic ischemic stroke in a Turkish population. Neuropsychiatr Dis Treat. 2021;3251-65.
13. Kramer J, Proschak E. Phosphatase activity of soluble epoxide hydrolase. Prostaglandins Other Lipid Mediat. 2017;133:88-92.
14. Przybyla-Zawislak BD, Srivastava PK, Vázquez-Matías J, Mohrenweiser HW, Maxwell JE, Hammock BD, et al. Polymorphisms in human soluble epoxide hydrolase. Mol Pharmacol. 2003;64(2):482-90.
15. Morisseau C, Hammock BD. Gerry Brooks and epoxide hydrolases: Four decades to a pharmaceutical. Pest Manag Sci. 2008;64(6):594-609.
Download attachments: 10.4328.ACAM.22100
Esma Özmen, Durmuş Ayan, Çağatay Emir Önder, Dilara Fatma Akın, Burcu Köse, İsmail Sarı, Cevat Yazıcı. Examination of the relationship between variants in the gene region encoding soluble epoxy hydrolase enzyme hydrolytic activity and type 2 diabetes. Ann Clin Anal Med 2024;15(5):344-349
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Determination of potential drug-drug interactions with different interaction software programs in elderly patients over 85 in a community pharmacy setting: A cross-sectional study
Harun Kızılay 1, Cengizhan Ceylan 2
1 Department of Pharmacology, 2 Department of Clinical Pharmacy, Faculty of Pharmacy, Selcuk University, Konya, Turkey
DOI: 10.4328/ACAM.22106 Received: 2024-01-13 Accepted: 2024-03-05 Published Online: 2024-04-02 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):350-354
Corresponding Author: Harun Kızılay, Department of Pharmacology, Faculty of Pharmacy, Selcuk University, Konya, Turkey. E-mail: harunkizilay@gmail.com P: +90 532 307 77 41 Corresponding Author ORCID ID: https://orcid.org/0000-0003-3660-0721
Other Author ORCID ID: Cengizhan Ceylan, https://orcid.org/0000-0003-4164-9212
This study was approved by the Local Committee of Selçuk University Faculty of Medicine (Date: 2022-06-22, No: 304008)
Aim: Various potential drug-drug interaction screening software programs or databases have been developed and implemented as decision support tools to assist clinicians. The risk of adverse drug reactions, hospitalization, compliance problems, and potential drug-drug interactions increases with age. Our research aimed to detect potential drug-drug interactions in elderly patients over 85 and compare the software programs used to detect interactions.
Material and Methods: Prescriptions of elderly patients over the age of 85 who received their medications from five different community pharmacies in Konya, Türkiye, in 2022 were retrospectively examined. The software programs Medscape®, Drugs®, Micromedex®, and LexiComp® were used to detect potential drug-drug interactions and reveal common interactions in the patients. The compatibility of the programs was also determined.
Results: A total of 307 patients (43.3% male and 56.7% female) were included in this study. While Micromedex® detected a total of 920 interactions in the total sample, Medscape® detected 1,876, Drugs® detected 1,632, and LexiComp® detected 1,414. However, LexiComp® detected the most contraindications. Regarding the compatibility of the four software programs, Kendall’s W value was calculated as 0.79, and the statistical significance was determined (p <0.05).
Discussion: Medscape®, Drugs®, Micromedex®, and LexiComp® software programs used to detect potential drug-drug interactions in the elderly exhibit high compatibility with each other. It is recommended that clinicians use more than one software program to determine potential drug-drug interactions for rational drug use.
Keywords: Geriatrics, Aged, Drug Interactions, Pharmacy, Aging
Introduction
Drug-drug interactions (DDIs) are defined as situations in which the pharmacological effect of one drug is altered by another when two drugs are used together. The most important reason why drug interactions are common is the use of multiple drugs at the same time [1]. DDIs are a particularly important type of adverse drug event because they can alter drug effectiveness and safety. While DDIs may not always be preventable, they can often be predicted [2, 3]. Actual DDIs are determined from adverse outcomes in patients, whereas potential DDIs (pDDIs) are those identified through analysis of the pharmacokinetic and pharmacodynamic profiles of each drug in use and the identification of potential adverse events resulting from this association. pDDIs may present with adverse outcomes in patients or have no clinical consequence [3-6]. The prevalence of pDDIs in the community pharmacy setting may vary depending on age and disease [7].
Various pDDI screening software programs or databases have been developed and implemented as decision support tools to assist clinicians [8]. These tools frequently report whether pDDIs identified occur due to the pharmacokinetic and/or pharmacodynamic effect, highlight the degree of severity, outline the management of pDDIs and provide reference literature. However, some databases do not include all of these components [9].
Polypharmacy is the use of multiple medications. Although there is no clear definition for polypharmacy, the simultaneous use of five or more drugs is generally accepted [10]. As drug use increases, drug-drug interactions will also increase and adverse drug reactions (ADRs) may be observed accordingly [11].
Old age is defined as age 65 and above. The increase in chronic comorbidities and pharmacokinetic and pharmacodynamic changes with age make elderly patients more sensitive to drug side effects [12]. The risk of ADRs, hospitalization, compliance problems, and pDDIs increases with age [9, 13]. The MULTIPAP Study, conducted on elderly patients treated in Spanish primary care centers, indicated that half of the patients had DDIs at least once. Similarly, a cross-sectional study conducted in Brazil reported that the prevalence of DDIs among elderly patients using multiple medications was around 35%. DDIs constitute a part of ADRs. In fact, it is estimated that 6%–30% of all ADRs in the population are caused by DDIs and are therefore largely preventable. Hence, continuous monitoring of inappropriate prescriptions that may lead to DDIs at the patient and/or population level is an important activity for ADRs prevention [14-17]. Our research aimed to detect pDDIs in elderly patients and compare software programs used to detect interactions.
Material and Methods
Prescriptions of elderly patients over 85 who received their medications from five different community pharmacies in Konya, Türkiye, from January 1 to December 31 2022 were retrospectively examined. Patients’ age, gender, and medication information were recorded, and prescriptions containing medications not covered by the software programs were excluded. The software programs Medscape®, Drugs®, Micromedex®, and LexiComp® were used to detect pDDIs in the patients.
While Medscape® and Drugs® accept free memberships, LexiComp® and Micromedex® accept paid memberships. Interaction classifications of software programs are shown in Figure 1.
Statistical Analyses
By analyzing each pDDI using Kendall’s W values, the link between the prospective pDDI software programs was verified based on the outcomes of severity degrees of interaction. Kendall’s W values range from 0–0.2, which denotes a little agreement, to 0.21–0.40 (fair), 0.41–0.60 (considerable), 0.61–0.80 (significant), and 0.81–1.0 (perfect). IBM SPSS 22.0 was used to conduct the statistical analysis. The threshold of statistical significance was set at p < 0.05.
Ethical Approval
This study was approved by the Ethics Committee of Selçuk University Faculty of Medicine Local Ethics Committee (Date: 2022-06-22, No: E.304008).
Results
A total of 307 patients (43.3% male and 56.7% female) were included in this study. While the average age of male patients was 88.38, it was 88.51 for females. While male patients had an average of 6.44 medications in their prescriptions, this number for females was 6.62. Polypharmacy was detected in the prescriptions of 223 (72.63%). Details are given in Table 1. While Micromedex® detected a total of 920 interactions in the total study sample, Medscape® detected 1,876, Drugs® detected 1,632, and LexiComp® detected 1,414 interactions. While Micromedex® detected 1 contraindicated interaction, Medscape® detected 4 and LexiComp® detected 79 contraindicated interactions. The number of interactions per patient in Micromedex®, Medscape®, Drugs®, and LexiComp® were 2.99, 6.11, 5.31, and 4.6, respectively. Details are given in Table 2. When the compatibility of the four software programs was examined, Kendall’s W was calculated as 0.79, and statistical significance was determined (p < 0.05). The compatibility of the software programs among themselves was also investigated. In the compatibility analysis between Micromedex®, Medscape®, and LexiComp®, Kendall’s W was determined as 0.81 (p < 0.05). When pairwise comparisons were made between programs, the highest score was between Medscape® and Drugs® (Kendall’s W: 0.9, p < 0.05). When Kendall’s W values were examined, it was determined that the software programs were highly compatible with each other. LexiComp® detected that 32.9% of contraindicated interactions were caused by combinations of nonsteroidal anti-inflammatory drugs (NSAIDs). Common contraindicated interactions, as well as their potential effect, details are given Table 3. Metoclopramide/Sertraline was identified as a contraindicated combination in Micromedex® software program. In Medscape®, Clarithromycin/Indapamide, Moxifloxacin/Indapamide, Amisulpride/Olanzapine and Amisulpride/Quetiapine combinations were identified as contraindicated. In the LexiComp® software program, combinations such as Diclofenac/Ketoprofen, Diclofenac/Ketoprofen, Diclofenac/Ketoprofen, Diclofenac/Ketoprofen and Flurbiprofen/Ketoprofen were found to be contraindicated.
Discussion
With age, there is increased physiological changes that may alter the effect of a drug, making the elderly population more prone to ADRs. Therefore, pDDI management is crucial. Clinicians benefit from various software programs for pDDI management. These programs can predict clinically important pDDIs and ADRs. Comparing the differences between such software programs should guide clinicians in predicting critical events [18, 19].
In this research, four frequently used interaction software programs were compared. While Medscape® and Drugs® are free to use, LexiComp® and Micromedex® require paid membership. It is thought that the free-to-use option increases the use of Medscape® and Drugs® in the community pharmacy environment. Most pDDIs were detected in Medscape®. The program with the least interaction was Micromedex®. Medscape® explains an interaction with more than one mechanism, and this is thought to be the reason for the difference. The most contraindications were detected in LexiComp®. It is thought that this is because this software program is provides an extensive list of contraindications, especially regarding NSAID combinations. There is no contraindication warning for the combined use of NSAIDs in other software programs
In a study involving patients aged 65 and over, Liu et al. indicated moderate agreement (weighted kappa = 0.473) between LexiComp® and Micromedex®. Furthermore, LexiComp® detected the most contraindicated interactions [20]. Howeever, the present study found a high difference between LexiComp® and Micromedex® (Kendall’s W = 0.86). In a study conducted in a community pharmacy environment, Sancar et al. determined that Micromedex®, Medscape®, and Drugs® were highly compatible with each other [21]. The present study found a similar result between the three programs (Kendall’s W > 0.80). In Kheshti et al.’s study, which compared five commonly used drug interaction databases (LexiComp®, Micromedex®, iFacts®, Medscape®, and Epocrates®), LexiComp® and Micromedex® were found to be more suitable than other databases for determining clinically important drug interactions [22]. In a study comparing Micromedex®, LexiComp®, and Drugs® for intensive care patients receiving antibiotics, 15% of the interactions detected with Micromedex®, 28.6% of the interactions detected with Medscape®, and 19.8% of the interactions detected with Drugs® were found to be significant [23].
Combinations of NSAIDs are remarkable, especially when contraindicated interactions are examined in LexiComp®. It has been stated that the risk of bleeding increases because of this interaction. Clinicians should be careful when prescribing these combinations in elderly patients. Complications that may develop due to bleeding can turn into life-threatening problems in such patients. Additionally, caution should be exercised when prescribing anticoagulant drugs in the elderly due to the risk of bleeding [24]. Drug interactions should always be considered in patients receiving anticoagulant therapy, especially those with multiple comorbidities, to optimize treatment [25].
Limitation
Conducting this study retrospectively was the most important limiting factor. Hence, limited data were obtained, and the number of drug interactions detected that were clinically significant could not be determined. Multicenter and larger prospective studies are needed to eliminate these limitations.
Conclusion
Interaction programs used to detect pDDIs in elderly patients in the community pharmacy setting demonstrate high compatibility. However, there are some differences in interaction severity among these programs; therefore, it would be appropriate to use a combination of programs when detecting pDDIs.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Palleria C, Di Paolo A, Giofrè C, Caglioti C, Leuizzi G, Siniscalchi A, et al. Pharmacokinetic drug-drug interaction and their implication in clinical management. J Res Med Sci. 2013;18(7):601-10.
2. Juurlink DN, Mamdani M, Kopp A, Laupacis A, Redelmeier DA. Drug-drug interactions among elderly patients hospitalized for drug toxicity. Jama. 2003;289(13):1652-8.
3. Montané E, Arellano AL, Sanz Y, Roca J, Farré M. Drug-related deaths in hospital inpatients: A retrospective cohort study. Br J Clin Pharmacol. 2018;84(3):542-552.
4. Alvim MM, Silva LA, Leite IC, Silvério MS. Adverse events caused by potential drug-drug interactions in an intensive care unit of a teaching hospital. Rev Bras Ter Intensiva. 2015;27(4):353-9.
5. Ganeva M, Gancheva T, Troeva J, Kiriyak N, Hristakieva E. Clinical relevance of drug-drug interactions in hospitalized dermatology patients. Adv Clin Exp Med. 2013;22(4):555-63.
6. Moura CS, Acurcio FA, Belo NO. Drug-drug interactions associated with length of stay and cost of hospitalization. J Pharm Pharm Sci. 2009;12(3):266-72.
7. Dirin MM, Mousavi S, Afshari AR, Tabrizian K, Ashrafi MH. Potential drug-drug interactions in prescriptions dispensed in community and hospital pharmacies in East of Iran. J Res Pharm Pract. 2014;3(3):104-7.
8. Wang H, Shi H, Wang N, Wang Y, Zhang L, Zhao Y, et al. Prevalence of potential drug - drug interactions in the cardiothoracic intensive care unit patients in a Chinese tertiary care teaching hospital. BMC Pharmacol Toxicol. 2022;23(1):39.
9. Roblek T, Vaupotic T, Mrhar A, Lainscak M. Drug-drug interaction software in clinical practice: a systematic review. Eur J Clin Pharmacol. 2015;71(2):131-42.
10. Masnoon N, Shakib S, Kalisch-Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC Geriatr. 2017;17(1):230.
11. Dhalwani NN, Fahami R, Sathanapally H, Seidu S, Davies MJ, Khunti K. Association between polypharmacy and falls in older adults: A longitudinal study from England. BMJ Open. 2017;7(10):e016358.
12. Johnell K, Klarin I. The relationship between number of drugs and potential drug-drug interactions in the elderly: A study of over 600,000 elderly patients from the Swedish Prescribed Drug Register. Drug Saf. 2007;30(10):911-8.
13. Livio F, Marzolini C. Prescribing issues in older adults living with HIV: Thinking beyond drug-drug interactions with antiretroviral drugs. Ther Adv Drug Saf. 2019;10:2042098619880122.
14. Classen DC, Pestotnik SL, Evans RS, Burke JP. Computerized surveillance of adverse drug events in hospital patients. Jama. 1991;266(20):2847-51.
15. Rogero-Blanco E, Del-Cura-González I, Aza-Pascual-Salcedo M, González GB, Terrón-Rodas C, Chimeno-Sánchez S, et al. Drug interactions detected by a computer-assisted prescription system in primary care patients in Spain: MULTIPAP study. Eur J Gen Pract. 2021;27(1):90-96.
16. Santos TRA, Silveira EA, Pereira LV, Provin MP, Lima DM, Amaral RG. Potential drug-drug interactions in older adults: A population-based study. Geriatr Gerontol Int. 2017;17(12):2336-2346.
17. Franceschi M, Scarcelli C, Niro V, Seripa D, Pazienza AM, Pepe G, et al. Prevalence, clinical features and avoidability of adverse drug reactions as cause of admission to a geriatric unit: A prospective study of 1756 patients. Drug Saf. 2008;31(6):545-56.
18. Bektay MY, Seker Z, Eke HK, Turk HM, Izzettin FV. Comparison of different decision support software programs in perspective of potential drug-drug interactions in the oncology clinic. J Oncol Pharm Pract. 2023;29(5):1178-1186.
19. Nightingale G, Pizzi LT, Barlow A, Barlow B, Jacisin T, McGuire M, et al. The prevalence of major drug-drug interactions in older adults with cancer and the role of clinical decision support software. J Geriatr Oncol. 2018;9(5):526-533.
20. Liu Y, Wang J, Gong H, Li C, Wu J, Xia T, et al. Prevalence and associated factors of drug-drug interactions in elderly outpatients in a tertiary care hospital: A cross-sectional study based on three databases. Ann Transl Med. 2023;11(1):17.
21. Sancar M, Kaşik A, Okuyan B, Batuhan S, Izzettin FV. Determination of Potential Drug-Drug Interactions Using Various Software Programs in a Community Pharmacy Setting. Turk J Pharm Sci. 2019;16(1):14-19.
22. Kheshti R, Aalipour M, Namazi S. A comparison of five common drug-drug interaction software programs regarding accuracy and comprehensiveness. J Res Pharm Pract. 2016;5(4):257-263.
23. Emre K, Tecen-Yücel K, Özdemir N, İnkaya AÇ, Bayraktar-Ekincioğlu A, Demirkan K, et al. Yoğun bakım hastalarında antibiyotiklerin diğer ilaçlarla etkileşimlerinin değerlendirilmesi [The Evaluation of Interactions of Antibiotics with Other Drugs in Intensive Care Patients]. Sürekli Tıp Eğitimi Dergisi. 2019;28(6):404-409.
24. Teklay G, Shiferaw N, Legesse B, Bekele ML. Drug-drug interactions and risk of bleeding among inpatients on warfarin therapy: A prospective observational study. Thrombosis journal. 2014;12(1):1-8.
25. Ceylan C, Umar RM, Çattık BN, Bolel F, Şahna M, Koçberber EK. Potential Drug-Drug Interactions in Patients Using Warfarin, Heparin, and Enoxaparin. Avicenna Journal of Pharmaceutical Research. 2021;2(2):60-65.
Download attachments: 10.4328.ACAM.22106
Harun Kızılay, Cengizhan Ceylan. Determination of potential drug-drug interactions with different interaction software programs in elderly patients over 85 in a community pharmacy setting: A cross-sectional study. Ann Clin Anal Med 2024;15(5):350-354
Citations in Google Scholar: Google Scholar
Assessment of timing of hydrocortisone treatment and vasoactive inotrope scores in pediatric septic shock cases
Gülhan Atakul, Selçuk Sinan Çelik, Merve Kökkülünk, Ece Demirbaş, Özlem Saraç Sandal, Utku Karaarslan, Hasan Ağın
Department of Pediatric Intensive Care Unit, Dr. Behçet Uz Children’s Diseases and Surgery Training and Research Hospital, University of Health Sciences İzmir, Turkey
DOI: 10.4328/ACAM.22126 Received: 2024-01-26 Accepted: 2024-03-19 Published Online: 2024-03-28 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):355-359
Corresponding Author: Gülhan Atakul, Department of Pediatric Intensive Care Unit, Dr. Behçet Uz Children’s Diseases and Surgery Training and Research Hospital, University of Health Sciences İzmir, Turkey. E-mail: gulhanatakul@gmail.com P: +90 505 878 00 16 Corresponding Author ORCID ID: https://orcid.org/0000-0002-3832-9691
Other Authors ORCID ID: Selçuk Sinan, https://orcid.org/0000-0002-2208-5549 . Merve Kökkülünk, https://orcid.org/0009-0009-0969-6335 . Ece Demirbaş, https://orcid.org/0009-0004-8872-611X . Özlem Saraç Sandal, https://orcid.org/0000-0003-2684-0625 . Utku Karaarslan, https://orcid.org/0000-0002-3267-6983 . Hasan Ağın, https://orcid.org/0000-0003-3306-8899
This study was approved by the Ethics Committee of Izmir Dr. Behçet Uz Pediatrics and Surgery Training and Research Hospital Clinical Research (Date: 2023-08-20, No: 165)
Aim: We aimed to investigate the relationship between the demographic characteristics of patients with septic shock who received hydrocortisone treatment, and the time of treatment initiation, doses, the relationship with different inotropes, and the relationship with vasoactive inotrope score.
Material and Methods: Our study included critically ill pediatric patients (n=41) while being monitored in the Pediatric Intensive Care Unit. Demographic data, primary diagnoses, systolic/diastolic/mean blood pressure levels, echocardiographic imaging findings (if any), hydrocortisone dosage, time of initiation after the first inotrope, total time of use, vasoactive inotrope scores and mortality status of patients were recorded in the data system and analyzed.
Results: Median (IQR) hydrocortisone infusion time was 36 (43) hours, time of initiation after the first inotrope median (IQR) was 24 (38) hours according to the calculation performed. There was no difference in initiation timing and infusion duration of hydrocortisone treatment between patients who received dopamine, dobutamine, or milrinone and those who did not (p>0.05). There was no correlation between the time after inotrope initiation and the infusion time of hydrocortisone (p=0.217, r2=-0.197). No significant difference was observed between mortality rates within the first 24 hours and at day 7, and the vasoactive inotrope score (p=0.345, p=0.954)
Discussion: Our study evaluated various parameters in patients who received hydrocortisone. If adrenal insufficiency is not previously diagnosed, it may take some time to consider the possibility of catecholamine resistance and decide to initiate hydrocortisone treatment. The definition of catecholamine-resistant septic shock is not clearly defined by a specific time.
Keywords: Pediatric Intensive Care Unit, Vasoactive Inotrop Score, Hydrocortisone, Catecholamine-Resistant Septic Shock
Introduction
Sepsis and septic shock are a significant cause of mortality and morbidity in children [1]. Sepsis is a life-threatening condition resulting from a dysfunctional host response to infection. Death often occurs in the early period (first 48-72 hours) due to resistant shock and multiple organ failure. Therefore, early diagnosis and initiation of appropriate and effective treatment is vital [2]. The treatment for sepsis and septic shock typically involves fluid resuscitation, antibiotics, and inotropes/vasopressors. In cases where septic shock is resistant to vasopressors and fluids, corticosteroids are recommended [3]. The use of glucocorticoid therapy in patients with septic shock has improved since the 1990s [4]. The administration of glucocorticoids in patients with sepsis and septic shock is based on data suggesting that critical illness may lead to a state of absolute or relative adrenal insufficiency, which can contribute to shock. Normal serum cortisol levels range from 5 to 24 mcg/dL with considerable variability depending on the time of day. In critically ill patients, daily variability is lost, and serum cortisol levels increase, reaching levels as high as 40 to 50 mcg/dL. Other aspects of critical illness may significantly alter cortisol metabolism and function. These include decreased cortisol degradation, decreased binding of cortisol to cortisol-binding globulin and albumin, increased glucocorticoid receptor affinity for cortisol, and peripheral conversion of precursors to cortisol. Another proposed mechanism suggests that in critically ill patients, disruption of the hypothalamic-pituitary-adrenal axis, in combination with underlying diseases and various factors, leads to negative changes in cortisol levels and decreased efficacy [5-7].
The initiation of hydrocortisone treatment should be considered in these patients to improve their condition and to prevent mortality due to adrenal insufficiency. Glucocorticoids have long been used as an adjunctive agent in septic shock, and new studies are providing additional information about their mechanism of action [8]. In the current guidelines, this treatment is still presented in the category of low quality weak recommendation [1].
Vasoactive inotrope score is an effective indicator that reflects cardiovascular function by integrating and quantifying the dosage of vasoactive drugs used [9].
In our study, we aimed to investigate the relationship between the demographic characteristics of patients with septic shock who received hydrocortisone treatment, and the time of treatment initiation, doses, the relationship with different inotropes, and the relationship with vasoactive inotrope score.
Material and Methods
The study was designed as a retrospective and observational study. Our study included critically ill patients between the ages of 1 month and 18 years who were diagnosed with septic shock and received hydrocortisone treatment while being monitored in the Pediatric Intensive Care Unit at Health Sciences University Dr. Behçet Uz Pediatrics and Surgery Training and Research Hospital from January 2020 to June 2023. The diagnosis of septic shock was made based on the definition provided in the current Surviving Sepsis Campaign guidelines [1]. Patients were identified through the Hospital Information System by reviewing their diagnosis and medication information. Then, the patients’ files and clinical follow-ups were analyzed. Demographic data, primary diagnoses, systolic/diastolic/average blood pressure levels, echocardiographic imaging findings (if any), hydrocortisone dose, time of initiation after the first inotrope, total time of use, presence of other inotropes and mortality status of patients (N=41) who received hydrocortisone infusion were determined and recorded in the data system. Mortality scores, specifically the Pediatric Risk of Mortality (PRISM IV) and Pediatric Logistic Organ Dysfunction (PELOD) scores, as well as VIS, were calculated based on the inotrope doses administered at the time of initiation of hydrocortisone treatment.
Vasoactive Inotrope Score
The Vasoactive Inotrope Score was calculated using the following formula: VIS = dopamine (μg/kg-min) + dobutamine (μg/kg-min) + 10 × milrinone (μg/kg-min) + 100 × epinephrine (μg/kg-min) + 100 × norepinephrine (μg/kg-min). The values at the time of initiation of hydrocortisone treatment were recorded in the data system [10].
Hydrocortisone protocol
The initial protocol for hydrocortisone treatment in our service starts with a 24-hour intravenous infusion of 50-100 mg/m2/day and is titrated to a maximum dose of 200 mg/m2/day [11, 12]. During this infusion, many hemodynamic parameters are dynamically monitored.
Statistical analysis
Statistical analysis of data was performed by SPSS software (version 22.0, SPSS Inc., Chicago, IL, USA). The distribution of the data was examined and mean standard deviation (SD) was given for normal distribution and median interquartile range (IQR) was given for non-normally distributed data. Independent T test or Mann Whitney U test was used to examine the differences between 2 groups in numerical data. Spearman correlation test was applied for correlation between numerical data.
Ethical Approval
This study was approved by the Ethics Committee of Izmir Dr. Behçet Uz Pediatrics and Surgery Training and Research Hospital Clinical Research (Date: 2023-08-20, No: 165).
Results
A total of 41 patients who were hospitalized in the pediatric intensive care unit and started hydrocortisone treatment because of catecholamine-resistant septic shock were identified. Demographic data, diagnosis, initial vital signs, dose and total usage duration of hydrocortisone, level of lactate, cortisol and mean (±SD) values of some variables are given in Table 1. It was determined that all patients received adrenaline and noradrenaline infusion, 25 (61%) patients received dopamine, 16 (39%) patients received dobutamine and 10 (24.4%) patients received milrinone infusion. There was no difference in initiation timing and infusion duration of hydrocortisone treatment between patients who received dopamine, dobutamine, or milrinone and those who did not. (p>0.05) (Table 2). Since all patients received adrenaline and noradrenaline infusion, these two inotropes were not included in the comparative analysis. There was no correlation between the time after inotrope initiation and the infusion duration of hydrocortisone (p=0.217, r2=-0.197). There was no correlation between the maximum level of hydrocortisone used and ejection fraction measurements (p=0.126, r2=-0.260)
The mortality status of the patients at 24th hour and 7th day were compared with doses and the start time of hydrocortisone, vital signs, and ejection fraction. Hydrocortisone infusion duration was shorter in patients with mortality in the first 24 hours (p<0.05). When the presence of mortality on day 7 was analyzed, patients with mortality had a lower percentage of ejection fraction, but higher baseline diastolic blood pressure values (p<0.05) (Table 3).
No significant difference was observed between mortality rates within the first 24 hours and at day 7, and the vasoactive inotrope score (p=0.345, p=0.954). A weak positive correlation was found between the vasoactive inotrope score and the PELOD score (p=0.029, r2=0.340). Additionally, a moderate positive correlation was observed between the vasoactive inotrope score and the PRISM score (p=0.007, r2=0.418). Furthermore, there was no correlation found between the vasoactive inotrope score and the duration of hydrocortisone infusion, the time elapsed after the initial inotrope administration, the length of hospitalization, or the ejection fraction (p>0,05).
Discussion
Noradrenaline and adrenaline infusions were initiated in all patients who received hydrocortisone. Additional inotropic treatment was required based on the patient’s central venous blood oxygen values, vital signs, and hemodynamic variables. Among these inotropes, it is believed that the high starting dose of hydrocortisone in patients who were not started on dopamine was due to physician preference in the hydrocortisone starting protocol. Additionally, there was no significant difference in the time elapsed between the initiation of the first inotrope and the administration of dopamine, milrinone, and dobutamine infusions in conjunction with adrenaline and noradrenaline infusions. It is important to consider the variability of inotropic and fluid responses in individual patients when evaluating the timing of hydrocortisone initiation. The doses of adrenaline and noradrenaline used in our study were not recorded. However, we did observe that hypotension persisted despite the administration of high doses.
Low ejection fraction during echocardiographic evaluation within the first week after the diagnosis of septic shock was significantly associated with mortality. Septic shock-induced acidosis and vascular compensation mechanisms may have a negative impact on cardiac reserve. The results can be explained as follows: The lower diastolic blood pressure of the patients who survived at the end of the first week does not necessarily indicate inadequate right heart filling volume and perfusion compared to the other group. Mean arterial pressures were maintained within the target range using multiple inotropes and fluid resuscitation in both groups. It is also worth noting that patients who died within the first 24 hours had shorter infusion times, as expected.
In our study, we would like to highlight the timing of the hydrocortisone infusion after the first inotrope. The lack of difference in mortality rates within the first 24 hours and at the end of the 7th day for this parameter suggests that septic shock and other underlying mechanisms may have a greater impact. Early diagnosis, timely initiation of broad-spectrum empirical antibiotic treatment, and aggressive inotropic and fluid therapy may have a greater impact on the mortality of patients with septic shock. This is already emphasized in current guidelines [1].
Prior to hydrocortisone treatment, it is important to consider patients’ cortisol levels. Patients with septic shock exhibit a wide variation in total serum cortisol levels [7]. In a prospective study of 101 sepsis patients, it was reported that the most accurate predictor of adrenal insufficiency (measured by an overnight ACTH stimulation test) was a baseline random cortisol level of 10 microg/dL or less, or a cortisol change of less than 9 microg/dL [13]. Critically ill patients undergo a transition from inactive protein-bound cortisol to physiologically active free cortisol. It has been suggested that free cortisol more accurately reflects hypothalamohypophyseal axis activation in these patients [14]. When retrospectively analyzing our patients, we found median values of total cortisol levels in only 20 patients. Unfortunately, we were unable to measure free cortisol levels. It would have been useful to have control levels to determine the increase in cortisol levels, which were already expected to increase, compared to baseline levels. The analysis should separate the direct effect on the septic shock clinic from the effects of prior treatments, including hydrocortisone. Prospective controlled studies are needed, particularly in the pediatric age group. Additionally, studies have shown that the low dose ACTH stimulation test can increase basal cortisol levels in pediatric patients with septic shock [15].
The vasoactive inotrope score is a tool used to measure the degree of inotrope treatments frequently administered to critically ill patients. Studies have shown a correlation between high VIS and poor prognosis [16]. VIS is primarily utilized for postoperative survival analysis of patients who have undergone cardiac surgery. Gaies et al, found that those with higher VIS within 24 hours of cardiac surgery had an increased risk of death [17].
There are a limited number of reports on the relationship between VIS and the prognosis of septic shock in pediatric patients. Haque et al, categorized pediatric patients with septic shock into a VIS ≤ 20 group and a VIS > 20 group and found that VIS > 20 was an independent risk factor for death in children [18]. The absence of a significant difference between the vasoactive inotrope score and mortality in our study may be due to the small sample size and early mortality. The high median values of the vasoactive inotrope scores of our patients may have contributed to this outcome. Upon analysis, it was determined that the decision to administer hydrocortisone was made during the late period when the VIS scores of the patients were high, which aligns with the SSC guidelines. If adrenal insufficiency is not previously diagnosed, it may take some time to consider the possibility of catecholamine resistance and decide to initiate hydrocortisone treatment. The definition of catecholamine-resistant septic shock is not clearly defined by a specific time.
In this study, we evaluated cases where hydrocortisone infusion was used in combination with inotropes. Recent studies have shown that the early use of intravenous vitamin C, along with corticosteroids and thiamine, is effective in preventing progressive organ dysfunction, including acute kidney injury, and reducing mortality in cases of septic shock and severe sepsis. However, the use of this combination is still controversial [19, 20].
Conclusion
Our study evaluated various parameters in patients who received hydrocortisone. We concluded that the timing of hydrocortisone treatment did not significantly affect mortality rates of vasoactive inotropic scores in pediatric septic shock patients. One of the limitations of our study is that it was planned retrospectively. Additionally, we were not able to measure the patients’ free cortisol levels. Studies on this topic in pediatric intensive care units in our country are limited. In the future, we recommend conducting controlled randomized prospective studies that evaluate free cortisol levels in conjunction with hydrocortisone treatment and the variability of inotrope requirement and mean arterial pressure.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Weiss SL, Peters MJ, Alhazzani W, Agus MSD, Flori HR, Inwald DP, et al. Surviving sepsis campaign international guidelines for the management of septic shock and sepsis-associated organ dysfunction in children. Pediatr Crit Care Med. 2020;21(2):e52-e106.
2. Turner DA, Cheifetz IM. Shock. Nelson textbook of pediatrics, 21st ed. Philadelphia: Elsevier. 2020.p.572-583.
3. Evans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, et al. Surviving sepsis campaign: International guidelines for management of sepsis and septic shock 2021. Crit Care Med. 2021;49:e1063–e1143.
4. Lamberts SW, Bruining HA, de Jong FH. Corticosteroid therapy in severe illness. N Engl J Med. 1997;337(18):1285-1292.
5. Repo JP, Neva MH, Häkkinen K, Pekkanen L, Metso S, Häkkinen AH. Stress hormone response to instrumented elective lumbar spine fusion surgery. J Orthop Surg (Hong Kong). 2023;31(3):10225536231201910.
6. Boonen E, Vervenne H, Meersseman P, Andrew R, Leen M, Declercq PE, et al. Reduced cortisol metabolism during critical illness. N Engl J Med. 2013;368:1477.
7. Cohen J, Smith ML, Deans RV, Pretorius CJ, Ungerer JPJ, Tan T, et al. Serial changes in plasma total cortisol, plasma free cortisol, and tissue cortisol activity in patients with septic shock: an observational study. Shock. 2012;37(1):28-33.
8. Venkatesh B, Cohen J. Hydrocortisone in vasodilatory shock. Critical Care Clinics. 2019;35(2):263-275.
9. Barge-Caballero E, Segovia-Cubero J, González-Vilchez F, Delgado-Jimenez J, Perez-Villa F, et al. Evaluation of the preoperative vasoactive-inotropic score as a predictor of postoperative outcomes in patients undergoing heart transplantation. Int J Cardiol. 2015;185:192-194.
10. Cui Y, Liu J, Zhao J, Feng Z, Long C, Qian X. Predictive effect of vasoactive drug score on acute kidney injury in infants and young children assisted by extracorporeal membrane oxygenation China Medical Herald 2013;10(18):79–81.
11. Davis AL, Carcillo JA, Aneja RK, Deymann JA, Lin CJ, Nguyen TC, et al. American college of critical care medicine clinical practice parameters for hemodynamic support of pediatric and neonatal septic shock. Crit Care Med. 2017;45(6):1061-1093.
12. Shulman DI, Palmert MR, Kemp SF. Lawson Wilkins drug and therapeutics committee. Adrenal insufficiency: Still a cause of morbidity and death in childhood. Pediatrics. 2007;119(2):e484-e494.
13. Annane D, Maxime V, Ibrahim F, Alvarez JC, Abe E, Boudou P. Diagnosis of adrenal insufficiency in severe sepsis and septic shock. Am J Respir Crit Care Med. 2006;174(12):1319-1326.
14. Hamrahian AH, Oseni TS, Arafah BM. Measurements of serum free cortisol in critically ill patients. N Engl J Med. 2004;350(16):1629-1638.
15. Sarthi M, Lodha R, Vivekanandhan S, Arora NK. Adrenal status in children with septic shock using low-dose stimulation test. Pediatr Crit Care Med. 2007;8(1):23-28.
16. Mete EMT, Bastopcu M, Acarel M. 24th hour vasoactive inotrope score is associated with poor outcome in adult cardiac surgery. Rev Assoc Med Bras (1992). 2023;69(5):e20221433.
17. Gaies MG, Jeffries HE, Niebler RA, Pasquali SK, Donohue JE, Yu Sunkyung, et al. Vasoactive-inotropic score is associated with outcome after infant cardiac surgery: An analysis from the pediatric cardiac critical care consortium and virtual PICU system registries. Pediatr Crit Care Med. 2014;15(6):529–537.
18. Haque A, Siddiqui NR, Munir O, Saleem S, Mian A. Association between vasoactive-inotropic score and mortality in pediatric septic shock. Indian Pediatrics. 2015;52(4):311–313.
19. Ragoonanan D, Tran N, Modi V, Nickelsen MP. Unanswered questions on the use of hydrocortisone, ascorbic acid, and thiamine therapy in sepsis and septic shock. Am J Health Syst Pharm. 2022;79(19):1626-1633.
20. Marik PE, Khangoora V, Rivera R, Hooper MH, Catravas J. Hydrocortisone, vitamin C, and thiamine for the treatment of severe sepsis and septic shock: A retrospective before-after study. Chest. 2017;151(6):1229-1238.
Download attachments: 10.4328.ACAM.22126
Gülhan Atakul, Selçuk Sinan Çelik, Merve Kökkülünk, Ece Demirbaş, Özlem Saraç Sandal, Utku Karaarslan, Hasan Ağın. Assessment of timing of hydrocortisone treatment and vasoactive inotrope scores in pediatric septic shock cases. Ann Clin Anal Med 2024;15(5):355-359
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Clinical outcomes of thoracic trauma in pediatric patients: An examination of admissions to the department of thoracic surgery
Mesut Buz 1, Selime Kahraman 2, Attila Özdemir 1, Berk Çimenoğlu 1, Talha Doğruyol 1, Recep Demirhan 1
1 Department of Thoracic Surgery, Kartal Dr. Lütfi Kırdar City Hospital, 2 Department of Thoracic Surgery, Dr. Siyami Ersek Thoracic and Cardiovascular Surgery Training and Research Hospital, Istanbul, Turkey
DOI: 10.4328/ACAM.22135 Received: 2024-02-02 Accepted: 2024-03-19 Published Online: 2024-04-03 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):360-363
Corresponding Author: Mesut Buz, Department of Thoracic Surgery, Kartal Dr. Lütfi Kırdar City Hospital, Istanbul, Turkey. E-mail: mesutbuzmd@gmail.com P: +90 530 402 21 66 Corresponding Author ORCID ID: https://orcid.org/0000-0003-1899-8983
Other Authors ORCID ID: Selime Kahraman, https://orcid.org/0000-0002-0973-9624 . Attila Özdemir, https://orcid.org/0000-0002-4319-1594 . Berk Çimenoğlu, https://orcid.org/0000-0002-9123-8203 Talha Doğruyol, https://orcid.org/0000-0003-0875-8409 . Recep Demirhan, https://orcid.org/0000-0003-4424-5918
This study was approved by the Ethics Committee of Kartal Dr. Lütfi Kırdar City Hospital (Date: 2023-04-27, No: 2023/514/248/15).
Aim: The aim of this study is to examine the demographic characteristics, trauma etiologies, diagnosed pathologies, and treatment methods of pediatric patients aged 10-17 who were admitted to the thoracic surgery department with isolated thoracic trauma.
Material and Methods: This retrospective study encompasses 46 pediatric patients diagnosed with isolated thoracic trauma during the specified period. Demographic information, trauma etiologies, diagnosed pathologies, and treatment methods were collected from the hospital information system. Descriptive statistics were applied for the analysis of data.
Results: The study found that the majority of patients were male (87%) with an average age of 15.5. The leading causes of trauma were penetrating-cutting instrument injuries (39.1%), traffic accidents (26.0%), and bicycle falls (10.9%). The most commonly encountered pathologies were pneumothorax (47.8%) and lung contusion (19.6%). While most patients were adequately treated with medical therapy, 36.9% required tube thoracostomy and 10.9% underwent surgical intervention.
Discussion: The findings reveal the etiological diversity and the wide range of treatment methods in pediatric isolated thoracic traumas. The study underscores the importance of a multidisciplinary approach in the management of pediatric thoracic traumas, indicating that isolated thoracic traumas generally have a good prognosis. However, the frequency of penetrating traumas and the necessity for surgical intervention require careful evaluation and approach in clinical practices.
Keywords: Pediatrics, Pneumothorax, Thoracic Trauma
Introduction
Thoracic trauma ranks among the significant traumatic injuries encountered in childhood, posing a major cause of morbidity and mortality [1]. In children, thoracic trauma commonly results from high-energy impacts, falls, and crush injuries, potentially affecting the respiratory system, cardiovascular system, and other vital organs, thus necessitating rapid and effective intervention. The anatomical and physiological characteristics of the thorax in the pediatric population differentiate the effects of trauma from adults; for instance, the more flexible chest walls and faster respiratory rates in children can increase the risk of post-trauma complications [2]. These differences necessitate age-specific diagnostic and treatment approaches.
Epidemiological data suggest that pediatric thoracic trauma cases constitute less than 10% of all pediatric trauma cases [3]. The most common types of thoracic trauma include contusions, rib fractures, pneumothorax, and hemothorax [4]. The management of these injuries varies depending on the child’s age, the severity of the trauma, and the presence of accompanying injuries. Timely and effective management of pediatric thoracic trauma cases is crucial for determining the short and long-term health outcomes of the patient.
The aim of this study is to examine the demographic characteristics, causes of trauma, clinical findings, treatment methods, and clinical outcomes of pediatric patients who presented to the emergency department with thoracic trauma and were subsequently admitted to the thoracic surgery department.
Material and Methods
This study was carried out in the thoracic surgery clinic of a tertiary hospital. All procedures were carried out in accordance with the ethical rules and the principles of the Declaration of Helsinki.
This study encompasses patients who were admitted to the thoracic surgery department due to isolated thoracic trauma between 2012 and 2022. The data included in the study were collected using a retrospective scanning method through the hospital information management system. Detailed records were kept of the patients’ demographic characteristics, the type of trauma, accompanying pathologies, applied surgical and medical treatments, lengths of hospital stay, and mortality rates. Patients with other systemic traumas or those who could not be fully documented medically during the study period were excluded.
All pediatric patients presenting to the emergency department with complaints of thoracic trauma were jointly evaluated at the initial assessment stage by a pediatric surgery specialist and a pediatric emergency medicine physician. Expert opinions from relevant medical disciplines were obtained for the identification and management of accompanying pathologies. Depending on their conditions and clinical needs, diagnostic tests such as thoracic radiography and electrocardiogram were administered to patients. The primary pathological findings necessitating treatment were accepted as the primary diagnosis.
Patients with injuries that could be treated with simple medical interventions were observed for a few hours based on the severity of their condition. Depending on the severity of the injury, those requiring further treatment were admitted to the ward or intensive care units.
Statistical analysis
The statistical analysis of the dataset was performed using SPSS software for Windows (Version 29, Chicago, IL, USA). The analysis process of the study was conducted based on patients’ demographic characteristics, trauma etiologies, diagnosed pathologies, and applied treatment methods. Initially, descriptive statistics were used to summarize patients’ demographic information such as age and gender, along with trauma etiologies and treatment outcomes. For this purpose, mean and standard deviation values were utilized for quantitative data, while percentages were employed to determine the distribution of categorical data. In the analysis, frequency distributions and tables were created to visualize the distribution of trauma etiologies and treatment methods.
Ethical Approval
This study was approved by the Ethics Committee of Kartal Dr. Lütfi Kırdar City Hospital (Date: 2023-04-27, No: 2023/514/248/15).
Results
Of the 46 patients included in the study, 40 were male, and 6 were female, with an average age of 15.5. According to the etiology of the trauma, penetrating-cutting instrument injuries (39.1%) were the most common, followed by traffic accidents (26.0%) and bicycle falls (10.9%). When etiological factors were classified as blunt and penetrating trauma, blunt thoracic traumas were observed at a rate of 47.8%, while penetrating traumas were observed at 52.2%. The etiological causes are summarized in Table 1. At the time of diagnosis, pneumothorax (47.8%) and lung contusion (19.6%) were the two most frequently observed pathologies. Hemothorax, sternum and rib fractures, superficial injuries to the chest wall, and pneumomediastinum were other encountered pathological conditions. Forty (87%) of the patients included in the study were male. Pathologies were observed on the left side in 52.2% of cases.
52.2% of the patients were healed with medical treatment, tube thoracostomy was applied to 17 patients (36.9%), and 5 patients (10.9%) underwent surgery. The surgeries included foreign body removal, rib stabilization, bleeding control, and wedge resection (Table 2).
The average hospital stay was 4 days, and it was found necessary for one patient to be admitted to the intensive care unit. No mortality cases were reported during the study (Table 3).
Discussion
In this study, pediatric patients admitted to the thoracic surgery department due to isolated thoracic trauma were examined. According to the results of the study, the most common causes of trauma were penetrating-cutting instrument injuries, traffic accidents, and bicycle falls, and pneumothorax and lung contusion were among the most common diagnoses. While most patients recovered with medical treatment, some required tube thoracostomy or surgical intervention.
Childhood injuries differ from adult injuries in terms of anatomical differences and the manner in which the injury occurs [5, 6]. Trauma-related deaths rank first among causes of death in children in developed countries. Thoracic traumas are the second leading cause of trauma-related child deaths [7].
The literature reports that 90% of children’s injuries are in the form of blunt trauma, with penetrating injuries seen with increasing frequency. It has been observed that male children are more exposed to trauma [8, 9]. However, in our study, although blunt and penetrating traumas were seen at almost similar rates (%47.8 vs. %52.2), the most common cause was penetrating traumas. Consistent with the literature, our study found that male children were more likely to present with trauma.
In our country, a study conducted in 2012 on children presenting to the emergency department with chest trauma found that motor vehicle accidents and falls were the leading causes of trauma etiology, with an average age of 10 [5]. Another study in 2020 reported that traffic accidents were the most common etiological reason for children visiting the emergency department due to trauma, with an average age of 8.9 [10]. Similarly, a 2016 study identified falls from height as the most frequent etiological cause of childhood traumas, recording an average age of 7.92±5.11 [11]. In our study, the most frequent etiological cause was injuries from penetrating-cutting instruments, with an average age of 15.5. We believe the differences in these studies regarding the average age and the etiological causes might be attributed to geographical variations and seasonal factors. Lung contusion and pneumothorax are the most commonly observed pathologies in thoracic traumas [3]. Pneumothorax was reported in 37% of children experiencing thoracic trauma as isolated pneumothorax and in 11% in conjunction with hemothorax [12]. Hemothorax in childhood is a rare complication of rib fractures, most commonly due to the sharp edges of intrathoracic fractures cutting the diaphragm or pleura [13-15]. In our study, pneumothorax was the most common pathological condition, followed by lung contusion and hemothorax.
In a study on 60 patients with traumatic pneumothorax in children, 34 patients (56.7%) were treated conservatively, while a chest tube was placed in 24 patients (40.0%), thoracotomy was performed on two patients (3.3%), and thoracoscopy on one patient (1.7%) [16]. The most commonly performed surgical intervention in thoracic traumas is tube thoracostomy [5]. In our study, 24 patients (52.2%) were followed up with medical treatment, tube thoracostomy was applied to 17 patients (36.9%), and surgery was performed on 5 patients (10.9%).
Thoracic organ injuries in children are less common than in adults but carry a higher mortality rate [17]. While the mortality rates for isolated chest traumas vary between 4-12%, this rate increases in the presence of accompanying organ injuries [18]. In our study, no complications or mortality were observed.
Limitations
The limitations of this study include potential data deficiencies and recording errors due to its retrospective design. Additionally, generalizing data obtained from a single center may not accurately reflect pediatric thoracic trauma cases in different geographical and socio-economic regions. The limited number of patients in the study makes it difficult to draw definitive conclusions about large-scale epidemiological trends. Lastly, focusing on isolated thoracic trauma cases limits the opportunity to evaluate the effects and management of multiple traumas.
Conclusion
This study examined the etiology, clinical characteristics, and treatment outcomes of isolated thoracic trauma in pediatric patients. According to the results, injuries from penetrating-cutting instruments, traffic accidents, and bicycle falls were identified as the most common causes of trauma. The nearly equal distribution of blunt and penetrating traumas underscores the diversity and complexity in managing pediatric thoracic traumas. Pneumothorax and lung contusion were determined as the most frequently diagnosed pathologies, with most patients successfully recovering with medical treatment. However, the presence of cases requiring tube thoracostomy and surgical intervention highlights the necessity for more aggressive treatment approaches in certain situations.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Pearson EG, Fitzgerald CA, Santore MT. Pediatric thoracic trauma: Current trends. Semin Pediatr Surg. 2017;26(1):36-42.
2. Piastra M, Ferrari V, Morena TC, Picconi E, Conti G. Delayed tension hemothorax after chest trauma in children. Pediatr Pulmonol. 2022;57(7):1818-9.
3. Alemayehu H, Aguayo P. Pediatric blunt thoracic trauma. J Pediatr Intensive Care. 2015;4(1):35-9.
4. Balci AE, Kazez A, Eren S, Ayan E, Ozalp K, Eren MN. Blunt thoracic trauma in children: review of 137 cases. Eur J Cardiothorac Surg. 2004;26(2):387-392.
5. Çevik M, Çavuş UY, Büyükcam F. Acil serviste göğüs travmalı çocuk hastaların geriye dönük incelenmesi [Retrospective examination of pediatric patients with chest trauma in the emergency department]. Kocatepe Medical Journal. 2012;13:63-8.
6. Nakayama DK, Ramenofsky ML, Rowe MI. Chest injuries in childhood. Ann Surg. 1989;210(6):770-5.
7. Delaplain PT, Guner YS, Feaster W, Wallace E, Gibbs D, Gholizadeh M, et al. Prediction of 7-day readmission risk for pediatric trauma patients. J Surg Res. 2020;253:254-61.
8. Schieren M, Wappler F, Wafaisade A, Lefering R, Sakka SG, Kaufmann J, et al. Impact of blunt chest trauma on outcome after traumatic brain injury- a matched-pair analysis of the TraumaRegister DGU®. Scand J Trauma Resusc Emerg Med. 2020;28(1):21.
9. Inci I, Ozcelik C, Nizam O, Eren N, Ozgen G. Penetrating chest injuries in children: A review of 94 cases. J Pediatr Surg. 1996;31(5):673- 6.
10. Atik D, Cander B, Dikmentaş C. Trafik kazası ile gelen pediatrik hastalarda kaza oluş şekilleri ile travma skorlarının değerlendirilmesi [Evaluation of accident modes and trauma scores in pediatric patients with a traffic accident]. Uludağ Üniv Tıp Fak Der. 2020;46(1):47-52.
11. Kılıç S, Taşkınlar H, Bahadır G, İşbir C, Naycı A. Çocuklarda yüksekten düşme sonucu oluşan travmaların değerlendirilmesi [Evaluation of traumas caused by falling from height in children]. Mersin Univ Saglık Bilim Derg. 2016;9(3):131-7.
12. Wesson DE, Cox CS. Thoracic injuries. In: Coran AG, editors. Pediatric Surgery. 7th ed. Philadelphia: Elsevier Inc; 2012.p.271-87.
13. Troxler D, Mayr J. POCUS diagnosis of sternal fractures in children without direct trauma-a case series. Children (Basel). 2022;9(11):1691.
14. Ozel M, Tatliparmak AC, Cetinkaya R, Sizlanan A, Ak R, Yilmaz S. Earthquake-related isolated blunt thoracic trauma patients: A special population study in the emergency department. Am J Emerg Med. 2024;75:148-53.
15. De la Morandiere K. Towards evidence-based emergency medicine: Best BETs from the Manchester Royal Infirmary. BET: Is CT thorax necessary to exclude significant injury in paediatric patients with blunt chest trauma? Emerg Med J. 2015;32(8):660-2.
16. Demir S, Ertürk A, Ertoy A, Öztorun C, Erten EE, Çalışkan D, et al. Çocuklarda travmatik pnömotoraks; bir çocuk travma merkezinin deneyimi [Traumatic pneumothorax in children: Experience of a child trauma center]. Kırıkkale Üni Tıp Derg. 2021;23(2):245-56.
17. Gutierrez IM, Ben-Ishay O, Mooney DP. Pediatric thoracic and abdominal trauma. Minerva Chir. 2013;68(3):263-74.
18. Melek M, Çobanoğlu U. Çocukluk çağı göğüs travmaları ve hemotoraks [Childhood chest trauma and hemothorax]. Van Tıp Derg. 2009;16(4):147-50.
Download attachments: 10.4328.ACAM.22135
Mesut Buz, Selime Kahraman, Attila Özdemir, Berk Çimenoğlu, Talha Doğruyol Recep Demirhan. Clinical outcomes of thoracic trauma in pediatric patients: An examination of admissions to the department of thoracic surgery. Ann Clin Anal Med 2024;15(5):360-363
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The comparison of laporoscopic and open procedures in ventral-incisional hernia repair
Rıdvan Yavuz 1, Fazıl Sağlam 2
1 Department of Gastroenterology Surgery, Antalya Training and Research Hospital, Antalya, 2 Department of General Surgery, Prof Dr Cemil Tascioglu City Hospital, İstanbul, Turkey
DOI: 10.4328/ACAM.22170 Received: 2024-03-07 Accepted: 2024-04-29 Published Online: 2024-04-29 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):364-368
Corresponding Author: Rıdvan Yavuz, Department of Gastroenterology Surgery, Antalya Training and Research Hospital, Antalya, Turkey. E-mail: drridvanyavuz@hotmail.com P: +90 505 261 05 21 Corresponding Author ORCID ID: https://orcid.org/0000-0002-9528-2148
Other Author ORCID ID: Fazıl Sağlam, https://orcid.org/0000-0001-9856-3861
This study was approved by the Ethics Committee of Okmeydanı Training and Research Hospital (Date: 2020-07-13, No: 48670771- 903.99)
Aim: To compare the results of laparoscopic ventral-incisional hernia repair (LVHO) with open surgery.
Materials and Methods: Sixty patients with ventral-incisional hernia underwent hernia repair. Of these patients, 30 (Group 1) underwent LVHO and the other 30 (Group 2) underwent open surgery. The intraperitoneal mesh was used for LVHO and the abdominal on-lay mesh technique was used for open hernia repair. The groups were compared in terms of body mass index (BMI ), anesthesia score values (ASA ), mesh diameter, operative time, hospital stay, visual analog scale (VAS ), recurrence, and complications.
Results: There was no statistically significant difference between the groups in terms of BMI and ASA ( p=0.87, P=0.74). The mean operative time was 80.0 (60-150) minutes in Group 1 and 72.5 (45-160) minutes in Group 2 ( p=0.07). The mean hospital stay was 2.3 days (1-9) in Group 1 and 3.5 days (1-20) in Group 2 (p=0.089). The results of VAS value at 72 hours were statistically different between the groups ( p=0.000). Complications were found in 10 patients (33.3%) in Group 1 and 7 patients (23.3%) in Group 2 ( p=0.567). Recurrence was detected in one case (3.3%) in Group 1 and 4 cases (13.3%) in Group 2 ( p=0.35).
Discussion: LVHO is as effective and safe as open surgery with less postoperative pain.
Keywords: Ventral Hernia, Mesh, Laparoscopy, Open Surgery
Introduction
The incidence of ventral-incisional hernia has been reported to be 2-11% [1]. Ventral-incisional hernia has become one of the most important problems of surgery due to its high incidence and high morbidity rate. Ventral-incisional hernias can be repaired by open surgery or laparoscopic methods. Although recurrence rates of 30-50% have been reported after open ventral hernia repair (AVHO), recurrence rates may decrease to 0-15% when hernia repair is performed with mesh [2]. These rates have decreased to less than 5% thanks to meshes that can be placed into the peritoneum [3]. On the other hand, although the use of mesh in open surgery has decreased the recurrence rate, complications such as wound infection, hematoma and seroma may increase due to extensive tissue dissection [4].
Laparoscopic surgery offers advantages such as minimal tissue trauma, detailed visualization of the mesh and surrounding tissue, and a more comfortable view with the magnification effect of the telescope. However, experience is also required to achieve successful results in laparoscopic operations. Laparoscopic ventral hernia repair (LVHO) was first reported by LeBlanc and Booth in 1993 [5]. In many subsequent studies, hospital stay, post-operative pain and other complication rates were reported to be lower in patients undergoing LVHO [6-8]. Recurrence rates in LVHO have been reported as 0-9% [9]. Therefore, LVHO has become a serious alternative treatment option to open surgery in the treatment of ventral-incisional hernia. However, when the studies are analyzed, it is not possible to make a definite judgment about which method is more successful.
In this study, the results of patients who underwent LVHO and AVHO for ventral-incisional hernia were compared and discussed with the relevant literature.
Material and Methods
Between April 2004 and February 2008, 60 patients who were operated on for ventral incisional hernia in the 3rd General Surgery Clinic of the Ministry of Health Okmeydanı Training and Research Hospital were included in the study. Of these patients, 30 (Group 1) underwent LVHO and the other 30 (Group 2) underwent AVHO. Patients with a hernia defect smaller than 3 cm and patients who underwent emergency surgery were not included in the study. Physical examination, all necessary preoperative tests (complete blood count, biochemistry, bleeding time and hepatitis markers, posterio-anterior chest radiography and electrocardiography) and USG were performed in all patients. Informed consent forms were obtained from all patients. Age, gender, height and weight data of the patients were recorded. Body mass index (BMI) was measured in all patients. Antibiotic prophylaxis was administered to all patients with cefazolin sodium 1 g one hour before induction and 8 hours post-operatively. Venous thrombo-embolism prophylaxis with anti-embolic stockings and low molecular weight heparin was performed in both groups. All Group 1 patients underwent preoperative mechanical bowel cleansing. In Group 2, only recurrent incisional hernia cases underwent mechanical bowel cleansing. Anesthesia score values (ASA) were recorded. Oral fluid intake was started at the 6th postoperative hour and oral food was started in patients who tolerated it. All patients received diclofenac sodium IV twice a day on postoperative days 1 and 2. The drain was removed after the color of the fluid coming from the drain was clear and the flow rate dropped below 50 ml. Analgesia was then provided with oral analgesics. Pain scoring was performed in the postoperative period. For this purpose, a visual analog score (VAS) was used. The patient was asked to choose the number that best describes his/her pain from a scale with numbers from 1 to 10. Postoperative pain values at 24, 48 and 72 hours were recorded. All patients were called for follow-up 1 week after discharge. Follow-up visits were performed at 1, 3 and 12 months postoperatively. Absent patients were called by phone. Ultrasonography (USG) was performed in patients with swelling at the surgical site. Patients with facial defects were considered as recurrence. The groups were compared in terms of BMI, ASA, mesh diameter, operation time, hospitalization time, VAS, recurrence, and complications.
Surgery techniques
Open surgery: Abdominal on-lay mesh technique was applied. Fascia was dissected up to 4-5 cm from the edges of the defect. In patients with primary closure of the fascia defect, polypropylene was approximated continuously with number one sutures. In all cases with primary closure, an on-lay polypropylene mesh was placed on the abdominal fascia without tension. The mesh was individually secured with 3-0 or 2-0 polypropylene sutures.
Laparoscopic surgery: Intraperitoneal mesh technique was applied. Spiral Tacker (Origin Medical Systems, Menlo Park, California) and transfixion suture materials were used for intraperitoneal fixation of the mesh. Suture Passer (W.L.Gore, Flagstaff, AZ) and 2 number 16 intravenous cannulas (Gntrakit®, Medikit®) were used to remove the prolene thread ends from the abdominal wall. The prepared mesh was sutured with polypropylene thread at four corners and tied with two 10 cm long ends. Additional holes were created in the mesh to reduce seroma formation. The corners of the mesh and the corresponding skin were marked with the same type of markings. After the mesh was pushed into the abdomen through a 10 m trocar, it was opened according to the markings. 1-2 m incisions were made on the skin at the marked places. With a suture passer or intravenous cannula inserted into the abdomen from here, the sutures on the edges of the mesh were taken out of the abdomen, passing through the fascia at separate points. The suture knots tied outside were pushed under the skin. The edges of the mesh were fixed to the abdominal wall with spiral titanium staples in single (Figure 1A) and double rows approximately 1 cm apart (Figure 1B). A polydioxanone (PDS) suture was placed in the 10-mm trocar hole with a suture passer and this suture was tied after the intra-abdominal CO2 was drained.
Statistical evaluation
Student-T test was used for comparisons with p>0.05 in Levene’s test (age, BMI, mesh diameter, length of hospitalization, duration of operation); non-parametric Mann-Whitney U test was used for comparisons with p<0.05 in Levene’s test (duration of operation, ASA values, VAS values) Chi-square test was used to compare the complications of the two groups and Fisher’s exact probability test was used to compare the recurrence rates. All tests were two-sided and p<0.05 values were considered significant.
Ethical approval
This study was approved by the Ethics Committee of Okmeydanı Training and Research Hospital (Date: 2020-07-13, No: 48670771- 903.99).
Results
In Group 1, the hernia was located at the umbilical/para/epigastric incision line in 17 cases, midline in 8 cases and peripheral incision line in 5 cases. In Group 2, the hernia was located at the umbilical/para/epigastric incision line in 4 cases, midline in 22 cases and peripheral incision line in 4 cases. Fifteen (25%) patients were female and 45 (75%) were male. The mean age was 54.7 ( 37-73 ) in Group 1 and 59.5 ( 34-75 ) in Group 2 ( p=0.07 ). There was no statistically significant difference in BMI and ASA between both groups ( p=0.87, P=0.74). The mean mesh diameter was 276.0 ( 150-900 ) cm² in Group 1 and 297.5 ( 100-900 ) cm² in Group 2, and this difference was not statistically significant ( p=0.655). The mean operative time was 80.0 (60-150) minutes in Group 1 and 72.5 (45-160) minutes in Group 2 ( p=0.07). The mean hospital stay was 2.3 days (1-9) in Group 1 and 3.5 days (1-20) in Group 2 ( p=0.089). The mean VAS value at 72 hours was 2.56 in Group 1 and 4.43 in Group 2 and the difference between these values was statistically significant ( p=0.000 ) (Table 1). A total of 26 complications were observed in both patient groups. Prolonged ileus was observed in a total of 3 patients, 2 in Group 1 and 1 in Group 2. In all 3 cases, improvement was achieved with conservative treatment and these cases were not considered as real morbidity and were not included in the statistical study. The complications observed in both groups are shown in Table 2. Wound infection was observed in 1 case in Group 1 and in 3 cases in Group 2. Intestinal injury occurred in 1 patient in Group 1. The patient was re-operated on post-op day 4. This small area of injury was approximated as a stoma. Due to intra-abdominal infection, the mesh was removed and the abdomen was left open for 9 days. However, the patient died on the 9th postoperative day due to septic shock. Complications were found in 11 (36.6%) patients in Group 1 and 12 (40%) patients in Group 2. There was no statistically significant difference between the two groups in terms of the number of cases with complications ( p=0.567). Recurrence was detected in one ( 3.3% ) case in Group 1 and 4 ( 13.3% ) cases in Group 2 ( p=0.35 ). The mean follow-up period was 18 ( 6-34 ) months in Group 1 and 21 ( 5-28 ) months in Group 2.
Discussion
In our study, the mean BMI was 30.8 kg/m2 in LVHO patients, while the mean BMI was 30.7 kg/m2 in AVHO patients. There was no statistically significant difference between the two groups in terms of BMI and ASA values. Similarly, Olmi et al. found no difference in BMI and ASA values [7]. The mean BMI of our patients in both groups was >30 kg/m2. This shows that most of our patients were obese. Complications were found in 33.3% and recurrence in 3.3% of the patients who underwent LVHO. In general, obese patients (BMI ≥30 kg/m2 ) are considered poor surgical candidates for ventral hernia repair due to associated co-morbidities, postoperative wound infection and risk of hernia recurrence. Many studies have reported that LVHO can be safely performed in obese patients with ventral-incisional hernia and has low complication rates [10,11]. Moreover, even in patients with morbid obesity, laparoscopic repair of ventral hernias can be performed with minimal morbidity and without recurrence [12]. However, no consensus has yet been reached on this issue. The data we obtained in this study seem to support the feasibility of LVHO in obese patients with ventral-incisional hernia.
Pain is common after vental-incisional hernia repair. There may be early post-operative pain as well as long term persistent pain. Patients may have pain or point tenderness at the transabdominal fixation points after LVHO. In the study by Park et al. [13], prolonged suture site pain after LVHO was reported to be 3.5%, while it was 4% in open repair. In contrast, in the study by Chari et al. [14], persistent suture site pain was not reported in any of the patients. Similar to the results of Chari et al. study, no patient in our study had persistent suture pain. Although there are studies [6, 15, 16] suggesting that LVHO reduces early post-operative pain, studies that do not support this view have also been published [17, 18]. In a study by Parkash et al. [6], patients who underwent LVHO and AVHO were compared in terms of VAS at post-operative 24th, 48th and 72nd hours and VAS values were found to be lower in patients who underwent LVHO. Similarly, in our study, VAS at 72 hours was compared in both groups and was found to be lower in patients who underwent LVHO. These data support the view that LVHO reduces pain in the early post-operative period. In our study, mesh diameters in patients who underwent LVHO were lower than those who underwent open surgery, although not statistically significant. Therefore, we believe that mesh size and the number of laparoscopic staples applied may be effective in the occurrence of post-operative pain.
Many studies have been published showing that the length of hospital stay is shorter in LVHO compared to AVHO [7, 18]. However, there are also studies showing that there is no significant difference between both methods [19, 20]. The duration of hospitalization in patients undergoing LVHO is 1.5-3 days. In our study, the duration of hospitalization in terms of LVHO was consistent with the literature. The mean hospital stay was 2.3 days in patients who underwent LVHO and 3.5 days in patients who underwent AVHO. Although this difference was not statistically significant, there was one day less hospital stay in favor of LVHO and we think that this should be taken into consideration.
There are publications reporting a shorter operation time in patients undergoing LVHO [15, 16, 18], as well as publications reporting no difference between both methods or a longer operation time in patients undergoing LVHO [21, 22]. The data obtained in our study were consistent with the relevant literature and no difference was found between the two groups in terms of operative time. However, the operation time was slightly longer in the LVHO Group. We believe that the presence of adhesions on the abdominal wall in some cases, the prolonged duration of the operations performed while the surgical team was completing the learning curve, and the time it took to place and fix the mesh on the ventral abdominal wall may be effective in this prolongation.
Many studies have reported that LVHO reduces post-operative complications [19, 21]. However, studies showing that there is no difference between LVHO and AVHO have also been published [8]. In our study, complications were found in 33.3% in the LVHO Group and 23.3% in the AVHO Group. There was no significant difference between both groups. In previous studies, bowel injury as a major complication was reported as 1.7-3% [22, 23]. Mortality developed in one (3.3%) of our patients due to septic shock after intestinal injury. Although our data support the view that LVHO reduces post-operative complications, the surgeon should keep in mind that major complications may develop during laparoscopic repair. In this overlooked case, enterotomy was probably due to intraoperative electro cautery burn. To avoid this, we think that sharp dissection using bipolar cautery, scissors and forceps would be more beneficial.
In many studies, no difference was found between LVHO and AVHO in terms of recurrence [ 8, 24 ]. On the other hand, some studies reported low recurrence rates (0-9%) in favor of LVHO [8, 11, 12]. The recurrence rate was 3.3% in the LVHO Group and 13.3% in the AVHO Group. The follow-up period was 18 months in the LVHO Group and 21 months in the AVHO group. In our study, there was no difference between the groups in terms of recurrence. Our study data support the view that there is no difference between LVHO and AVHO in terms of recurrence. Between 66% and 90% of recurrences occur within the first two years [24, 25]. Therefore, we think that our follow-up period is sufficient to evaluate recurrence cases.
The most important limitation of our study is the small number of patients. The fact that the results of our study may change with revisions to be made with the change in medical technologies is another limitation.
Conclusıon
LVHO seems to be as effective and safe as open surgery in patients with ventral-incisional hernia. Postoperative pain may develop less in patients undergoing LVHO compared to open surgery. However, prospective studies involving large patient groups are needed to standardize this method.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Van’t Riet M, de Vos van Steenwijk PJ, Bonthuis F, Marquet RL,Steyerberg EW, Jeekel J, et al. Prevention of adhesion to prostetic mesh: Comparison of barriers using an incisional hernia model. Ann Surg. 2003;237(1):123-128.
2. Young RM, Gustafson R, Dinsmore RC. Sepramesh vs. Dualmesh for abdominal wall hernia repairs in a rabbit model. Curr Surg. 2004;61(1):77-79.
3. Millikan KW. Incisional hernia repair. Surg Clin North Am. 2003;83(5):1223-34.
4. Cox TC, Blair LJ, Huntington CR, Colavita PD, Prasad T, Lincourt AE. The cost of preventable comorbidities on wound complications in open ventral hernia repair. J Surg Res. 2016;206(1):214-222.
5. Olmi S, Millo P, Piccoli M, Garulli G,Nardi MJ, Pecchini F. Laparoscopic treatment of incisional and ventral hernia. JSLS. 2021;25(2).
6. Parakash KS, Dumbre R, Phalgune D. A comparative prospective study of laparoscopic and open-mesh repair for ventral hernia. Indian Journal of Surgery. 2020;82(4):465-471.
7. Olmi S, Scaini A, Cesana GC, Erba L, Croce E. Laparoscopic versus open incisional hernia repair: An open randomized controlled study. Surg Endosc. 2007;21(4):555-9.
8. Çelik Y, Erbil OA. İnsizyonel herni cerrahisinde açık ve laparoskopik yöntemin karşılaştırılması tek merkez deneyimi [Comparison of open and laparoscopic methods in incisional hernia surgery a single center experience]: Anatolian Clinic the Journal of Medical Sciences. 2019;24(1):67-71.
9. Heniford BT, Park A, Ramshaw BJ, Voeller G. Laparoscopic ventral and incisional hernia repair in 407 patients. J Am Coll Surg. 2000;190(6):645–50.
10. Johna S. Laparoscopic incisional hernia repair in obese patients. JSLS. 2005;9(1):47.
11. Palanivelu PR, Siddhartha B, Kumar SS , Parthasarathi R, Cumar B, Palanivelu C. Morbid obesity with ventral hernia: is concomitant bariatric surgery with laparoscopic ventral hernia mesh repair the best approach? An experience of over 150 cases. Surg Obes and Relat Dis. 2019;15(7):1098-1103.
12. Birgisson G, Park AE, Mastrangelo MJ, Witzke DB, Chu UB. Obesity and laparoscopic repair of ventral hernias. Surg Endosc. 2001;15(12):1419-22.
13. Sajid MS, Khawaja AH, Sayegh M, Baig MK. A systematic review comparing single-incision versus multi-incision laparoscopic surgery for inguinal hernia repair with mesh. Int J Surg. 2016;29:25-35.
14. Chari R, Chari V, Eisenstat M,Chung R. A case controlled study o laparoscopic incisional hernia repair. Surg Endosc. 2000;14(2):117–9.
15. Navarra G, Musolino C, DeMarco ML, Bartolotta M, Barbera A, Centorrino T. Retromuscular sutured incisional hernia repair: A randomized controlled trial to compare open and laparoscopic approach. Surg Laparosc Endosc Percutan Tech. 2007;17(2):86-90.
16. Olmi S, Scaini A, Cesana GC, Erba L, Croce E. Laparoscopic versus open incisional hernia repair: A randomized control trial. ANZ J Surg. 2008;78:903–6.
17. Eker HH, Hansson ME,Buunen M, Janssen MC, Pierik RE, Hop WC, Bonjer HJ, et al. Laparoscopic vs. open incisional hernia repair a randomized clinical trial. JAMA Surg. 2013;148(3):259-63.
18. Misra MC, Bansal VK, Kulkarni MP, Pawar DK. Comparison of laparoscopic andopen repair of incisional and primary ventral hernia: Results of a prospective randomized study. Surg Endosc. 2006;20(12):1839-1845.
19. Itani KM, Hur K, Kim LT, Anthony T, Berger DH, Reda D, et al. Comparison of laparoscopic and open repair with mesh for the treatment of ventral incisional hernia: A randomized trial. Arch Surg. 2010;145(4):322–8.
20. Bingener J, Buck L, Richards M, Michalek J, Schwesinger W, Sirinek K. Long-term outcomes in laparoscopic vsopen ventral hernia repair. Arch Surg. 2007;142(6):562–7.
21. Barbaros U, Asoglu O, Seven R, Erbil Y, Dinccag A, Deveci U. The comparison of laparoscopic and open ventral hernia repairs: A prospective randomized study. Hernia. 2007;11(1):51-56.23.
22. McGreevy JM, Goodney PP, Birkmeyer CM, Finlayson SR, Laycock WS, Birkmeyer JD. A prospective study comparing the complication rates between laparoscopic and open ventral hernia repairs. Surg Endosc. 2003;17(11):1778-1780.
23. Heniford BT, Park A, Ramshaw BJ, Voeller G. Laparoscopic repair of ventral hernias: Nine years’ experience with 850 cosecutive hernias. Ann Surg. 2003;238(3):391-400.
24. Haapaniemi S, Nordin P, Itani KM, Pointner R,Granderath FA, Sarr MG. Prevention and Treatment. In: Schumpelick V, Fitzgibbons, editors. Present state of failure rates (clinical studies and epidemiological database, short- and long-term. 2nd ed. Berlin Springer-Verlag: Recurrent Hernia; 2007.p.3-25.
25. Sharath JG, Upendra KK, Manangi M, Madhu KP, Arun BJ, Niranjan N. Incisional hernia: Incidence, clinical profile, risk factors and prevention. Inter Surg J. 2016;3(3):1292-1295.
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Rıdvan Yavuz, Fazıl Sağlam. The comparison of laporoscopic and open procedures in ventral-incisional hernia repair. Ann Clin Anal Med 2024;15(5):364-368
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The role of hemogram parameters in predicting the severity of preeclampsia
Mulaim Sizer 1, Nurullah Peker 2, Reyhan Gündüz 2, Mehmet Sıddık Evsen 2, Nebahat Sunar 2, Hamdin Günsel 1
1 Department of Obstetrics and Gynecology, Batman Training and Research Hospital, Batman, 2 Department of Obstetrics and Gynecology, Faculty of Medicine, Dicle University, Diyarbakır, Turkey
DOI: 10.4328/ACAM.22173 Received: 2024-03-08 Accepted: 2024-04-19 Published Online: 2024-04-29 Printed: 2024-05-01 Ann Clin Anal Med 2024;15(5):369-372
Corresponding Author: Mulaim Sizer, Department of Obstetrics and Gynecology, Batman Training and Research Hospital, Batman, Turkey. E-mail: mulayimsizer@hotmail.com P: +90 506 856 42 85 Corresponding Author ORCID ID: https://orcid.org/0000-0003-4864-7287
Other Authors ORCID ID: Nurullah Peker, https://orcid.org/0000-0002-3285-9990 . Reyhan Gündüz, https://orcid.org/0000-0001-8468-7038 . Mehmet Sıddık Evsen, https://orcid.org/0000-0002-1680-907X . Nebahat Sunar, https://orcid.org/0000-0002-5404-1241 . Hamdin Günsel, https://orcid.org/0000-0001-5963-1147
This study was approved by the Ethics Committee of the local University Faculty of Medicine Non-Invasive Clinical Research (Date: 2020-07-16, No: 246)
Aim: The purpose of this study was to examine the significance of hemogram parameters in predicting preeclampsia and/or preeclampsia severity in patients with pre-diagnosis of preeclampsia.
Material and Methods: The study was retrospective and comprised 198 patients with preeclampsia, 158 with severe preeclampsia and 40 with non-severe preeclampsia, as well as 126 pregnant women who had a healthy pregnancy as the control group. From the hemogram parameters, platelet count (PLT), neutrophil count, mean platelet volume (MPV), mean erythrocyte volume (MCV), leukocyte count and neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (TLR) and platelet/neutrophil ratio (TNR) were calculated. The pregnant women included in the study were compared in terms of these parameters.
Results: While there was no statistically significant difference between the groups in the statistical analysis of MCV, MPV, NLR, and TNO, which are the parameters studied in PE groups with and without severe features, a statistically significant difference was found in these parameters between the control group and the preeclampsia group. At the TNO 35,1250 cut-off value, the sensitivity was 83.8 %, the specificity was 41.3 %, the positive predictive value was 69.17 %, and the negative predictive value was 61.90 %, and it was found that this value predicted the presence of PE as 69%.
Discussion: In this study, we discovered that MPV, MCV, TNO, and NLO levels differed significantly between the PE and control groups. However, the sensitivity and specificity rates of these parametria in the detection of preeclampsia are far below significant values.
Keywords: Hemogram, MCV, MPV, NLR, PLR, PNR, Preeclampsia
Introduction
Preeclampsia (PE) is a disorder in which a previously known normotensive pregnant woman develops new-onset hypertension with severe end-organ dysfunction signs or symptoms in the absence of proteinuria or new-onset hypertension with proteinuria after 20 weeks of gestation [1, 2]. According to a comprehensive review, PE complicated 4.6 % of all pregnancies [3]. Although there are risk factors for PE such as nulliparity, history of PE in a previous pregnancy, age over 40 or under 18, family history of PE, chronic hypertension, chronic kidney disease, autoimmune disease (such as antiphospholipid syndrome, systemic lupus erythematosus), vascular disease, Diabetes Mellitus (DM) (pregestational DM or gestational DM), multiple pregnancies, obesity, black race, hydrops fetalis, the basic causes of this disease have not been clearly clarified yet despite many studies. Studies examining the association between markers of systemic inflammation, which may be easily obtained via a complete blood count (hemogram), and various diseases have recently received a lot of interest [4-9].
In this study, platelet count (PLT), neutrophil count, leukocyte count, mean platelet volume (MPV), mean erythrocyte volume (MCV) in the hemogram examination taken from the patients at the time of admission and neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (TLR), platelet/neutrophil ratio (TNR), which are called systemic inflammatory response markers, obtained by the ratio of some of these parameters were taken into account. It was intended to assess the role of the analyzed parameters in predicting preeclampsia or the severity of preeclampsia.
Material and Methods
A total of 198 pregnant women with preeclampsia (Pe group), 158 with severe preeclampsia and 40 with non-severe preeclampsia (Pe group), who applied to the Gynecology and Obstetrics Clinic of local University Medical Faculty Hospital between January 2018 and December 2019, were included in the study by retrospectively scanning their files. The 2019 ACOG guidelines were based on the diagnosis of preeclampsia and the classification of preeclamptic patients as having severe or non-severe characteristics [1]. Pregnant women with any infection detected, with diagnoses such as DM, chronic hypertension, chronic lung, kidney and heart disease and chronic drug use, multiple pregnancies, developing chorioamnionitis, malignancy, hospitalized in our clinic with the diagnosis of PE and followed up with eclampsia or HELLP (Hemolysis , Elevated Liver Enzymes, Lowered Platelet), and patients who came to our clinic with full cervical dilation under emergency conditions and gave birth before hemogram could be examined, or patients who gave birth in another center and were sent to our clinic because of PE development in the postpartum period were not included in the study. The control group consisted of 126 pregnant women who had a healthy pregnancy.
Hemogram samples were collected from patients prior to any surgical intervention or medicinal therapy. To compare groups, mean platelet volume (MPV), mean red cell volume (MCV), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (TLR) and platelet/neutrophil ratio (TNR) were measured. Hemogram parameters were also studied and calculated in the Sysmex XN – 1000 (Japan) model.
Statistical Package for Social Sciences (SPSS) for Windows 21 (IBM SPSS Inc., Chicago, IL) statistical package program was used for the statistical evaluation of the research data.
Categorical variables were shown as numbers and percentages, whereas measured variables were provided as mean standard deviation (SD), minimum maximum (min-max), or median (25-75 percentile) (%). The Shapiro-Wilk test was used to determine whether the data conformed to the normal distribution. Mann Whitney U test was utilized in the analysis of measurement variables. The chi-square test was performed in the analysis of categorical data. The hypotheses were two-sided, and a p<0.05 was considered statistically significant. To determine the distinctness of the hemogram parameters measured in the process of determining the presence or severity of preeclampsia, ROC (Receiver-operation characteristic) analysis was performed.
Ethical Approval
This study was approved by the Ethics Committee of the local University Faculty of Medicine Non-Invasive Clinical Research (Date: 2020-07-16, No: 246).
Results
The study comprised 324 pregnant women, 126 of whom were in the control group and 198 of whom were PE patients. Pregnant women with preeclampsia were divided into two groups: those with non-severe preeclampsia (n=40) and those with severe preeclampsia (n=158).
In terms of maternal age at birth, gravida, parity abortion, and the number of survivors, there was no significant difference between the two groups (p>0.05).
In terms of fetal weight, fetal height, 1st and 5th minute APGAR scores, and the gestational week at the time of birth, there was a significant difference between the two groups (p0.001).
A statistically significant difference in MCV, MPV, NLR, and TNO was found between the two groups, and the comparison of laboratory values is given in Table 1.
Below is the ROC curve and analysis for MCV, MPV, TLR, NLR, and TNO levels in the preeclampsia and control groups.
The sensitivity was 59.1 %, the specificity was 52.4 %, the positive predictive value was 66.10 %, and the negative predictive value was 44.90 % for MCV 84.4(fL). The MCV 84.4(fL) cut-off value was found to predict the occurrence of PE 56.6 %. (p<0.045).
The sensitivity was 65.0 %, the specificity was 40.5 %, the positive predictive value was 63.05 %, and the negative predictive value was % for MPV 9.81(fL). MPV ≥9.81(fL cutoff value predicted the presence of PE was 57.4%(p<0.024).
For NLR ≥3,2313, sensitivity was 69.7%, specificity 45.2%, positive predictive value 66.67% and negative predictive value 48.72%. NLR ≥3,2313 cutoff value predicted the presence of PE was found to be 63.1% (p<0.001).
TNR ≤35,1250 had a sensitivity of 83.8 %, a specificity of 41.3 %, a positive predictive value of 69.17 %, and a negative predictive value of 61.90 %. TNO ≤35,1250 cut-off value predicted the presence of PE was found to be 69.0% (p<0.001).
When the laboratory parameters of the non-severe PE group and the severe PE group were compared, no statistically significant difference in any parameter was identified (Table 3).
Discussion
Preeclampsia is a progressive condition that endangers both the mother’s and the baby’s health. Although the exact etiology is unknown, new research suggests that preeclampsia is connected with increased inflammation and aberrant immunological responses [10]. Early detection of low-cost and easily accessible measures may aid in the treatment of preeclampsia and difficult pregnancy outcomes. Systemic inflammatory indicators are hemogram parameters that can be examined in practically any health clinic. In this study, MPV, MCV, TNO, and NLR were found to be significant in predicting preeclampsia. Simultaneously, TNO was found to be a greater predictor of preeclampsia than NLR, MPV, and MCV. While Elgari et al. showed [11] that MCV was considerably greater in the PE group compared to the control group in one of the studies exploring the association between preeclampsia and MCV, Kanat-Pektaş et al. [12] observed no statistically significant difference in MCV between the two groups. In both studies, the reason for this difference was not emphasized. When the association between MPV and PE is explored, it is discovered that the MPV value in the PE group is much higher than in the control group [13]. In conclusion, when similar research is reviewed further, it is clear that MCV and MPV are higher in the PE group [12, 14]. MCV and MPV levels were observed to be considerably higher in the PE group compared to the control group in our study. Elgari et al. found that the mean MCV in the PE group was 86 ± 6.2 fL (p<0.001), while the mean MCV in the control group was 83 ± 8.1 fL [11]. Although the MCV value was greater in the PE group compared to the control group in the study by Kanat-Pektaş et al., no statistical difference was detected between the two groups [12]. In both studies, no comment was made on the cause of MCV elevation. In another study, it has been reported that MCV is increased in preeclampsia [14].
There are many studies in the literature examining the relationship between NLR and preeclampsia because the Neutrophil/Lymphocyte Ratio is shown as an easily accessible marker showing the prognosis of systemic inflammation and some diseases, and increased systemic inflammatory response is considered in your PE etiopathogenesis. Although there is no clear consensus between NLR and PE in studies, most investigations show that NLR values in PE are much greater than in the control group [15-17]. This appears to be consistent with the concept of systemic inflammatory response in the pathophysiology of PE. NLR was significantly higher in the PE group in this study, but there was no significant difference between the severe PE group and the non-severe PE group.
TLR, like other systemic inflammatory indicators, has been assumed to be a predictor of the existence and severity of PE, however, despite inconsistent data to yet, the trend is that there is no difference in TLR between PE and the control group [18, 19]. Similarly, no significant change in TLR was found between the PE and control groups in our investigation.
There are very few studies that examine TNO to predict the existence or severity of preeclampsia, and in our investigation, the TNO value was considerably lower in the PE group compared to the control group. At the TNO 35,1250 cut-off value, the sensitivity was 83.8 %, the specificity was 41.3 %, the positive predictive value was 69.17 %, and the negative predictive value was 61.90 %, and it was found that this value predicted the presence of PE as 69% .
To summarize, preeclampsia is a major cause of neonatal and maternal death. Early detection and treatment will lower fetal-maternal morbidity and mortality rates dramatically. In this study, we discovered that MPV, MCV, TNO, and NLO levels differed significantly between the PE and control groups. However, the sensitivity and specificity rates of these parametria in the detection of preeclampsia are far below significant values. Furthermore, it was decided that multicenter studies with bigger patient populations are required to evaluate whether they can be used alone in diagnosing and forecasting the severity of preeclampsia.
Acknowledgment
We would like to thank Assoc. Prof. Dr. Erhan Okuyan for his contribution to this article.
Scientific Responsibility Statement
The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.
Animal and Human Rights Statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or compareable ethical standards.
Funding: None
Conflict of Interest
The authors declare that there is no conflict of interest.
References
1. Croke L. Gestational hypertension and preeclampsia: A practice bulletin from ACOG. Am Fam Physician. 2019;100(10):649-50.
2. Magee LA, Pels A, Helewa M, Rey E, Von Dadelszen P. Canadian Hypertensive Disorders of Pregnancy Working Group. Diagnosis, evaluation, and management of the hypertensive disorders of pregnancy: Executive summary. J Obstet Gynaecol Can. 2014;36(5):416-41.
3. Abalos E, Cuesta C, Grosso AL, Chou D, Say L. Global and regional estimates of preeclampsia and eclampsia: A systematic review. Eur J Obstet Gynecol Reprod Biol. 2013;170(1):1-7.
4. Ha ET, Yee A, Peterson SJ, Kobayashi Y, Sacchi T, Parikh M, et al. Neutrophil-to-lymphocyte ratio and prognosis in patients undergoing percutaneous coronary intervention for acute coronary syndrome. Cardiovasc Revasc Med. 2024;60:29-34.
5. Sizer B, Yılmaz Ü, Kınış V. Comparison of patients with malignant or benign laryngeal lesions and healthy indivduals in terms of haematological inflammatory parameters. Int J Clin Pract. 2021;75(7):e14236.
6. Celikbilek M, Dogan S, Ozbakır O, Zararsız G, Kücük H, Gürsoy S, et al. Neutrophil-lymphocyte ratio as a predictor of disease severity in ulcerative colitis. J Clin Lab Anal. 2013;27(1):72-6.
7. Sizer E, Balca Y, Bulut M, Çobanoğlu T. A retrospective cohort study of the change in inflammatory parameters in childhood schizophrenia and bipolar disorder from childhood to adulthood: Neuroinflammation in schizophrenia and bipolar disorder. J Surg Med. 2022;6(6):605-9.
8. Peker N, Ege S, Bademkiran MH, Aydin E, Karacor T, Obut M, et al. Can clomiphene citrate resistance be predicted by RDW-CV levels in infertile women with PCOS?. Niger J Clin Pract. 2019;22(11):1463-6.
9. Sizer B, Yılmaz Ü, Topçu İ. Relationship of Parotid Gland Masses with Systemic Inflammatory Parameters. Journal of Medical Clinics. 2020;3(2):77-83.
10. Elgari MM, Khabour OF, Alhag SM. Correlations between changes in hematological indices of mothers with preeclampsia and umbilical cord blood of newborns. Clin Exp Hypertens. 2019;41(1):58-61.
11. Kanat-Pektas M, Yesildager U, Tuncer N, Arioz DT, Nadirgil-Koken G, Yilmazer M. Could mean platelet volume in late first trimester of pregnancy predict intrauterine growth restriction and pre-eclampsia?. J Obstet Gynaecol Res. 2014;40(7):1840-5.
12. Heilmann L, Rath W, Pollow K. Hemorheological changes in women with severe preeclampsia. Clin Hemorheol Microcirc. 2004;31(1):49-58.
13. Avcıoğlu SN, Sezer SD, Altınkaya SÖ, Küçük M, Ömürlü İK, Yüksel H. Erythrocyte indices in patients with preeclampsia. Meandros Med Dent J. 2015;16(2):35-42.
14. Mannaerts D, Heyvaert S, De Cordt C, Macken C, Loos C, Jacquemyn Y. Are neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and/or mean platelet volume (MPV) clinically useful as predictive parameters for preeclampsia? J Matern Fetal Neonatal Med. 2019;32(9):1412-9.
15. Oylumlu M, Ozler A, Yildiz A, Oylumlu M, Acet H, Polat N, et al. New inflammatory markers in pre-eclampsia: Echocardiographic epicardial fat thickness and neutrophil to lymphocyte ratio. Clin Exp Hypertens. 2014;36(7):503-7.
16. Tamer LH, Aykanat Y, Gökdağlı Sığır F, Olmuşçelik O, Özdemir S. Status of neutrophil-lymphocyte ratio and 25-hydroxyvitamin D in preeclampsia and preterm birth. Perinatal Journal. 2017;25(3):91–6.
17. Kirbas A, Ersoy AO, Daglar K, Dikici T, Biberoglu EH, Kirbas O, et al. Prediction of preeclampsia by first trimester combined test and simple complete blood count parameters. J Clin Diagn Res. 2015;9(11):20-3.
18. Yavuzcan A, Cağlar M, Ustün Y, Dilbaz S, Ozdemir I, Yildiz E, et al. Mean platelet volume, neutrophil-lymphocyte ratio and platelet-lymphocyte ratio in severe preeclampsia. Ginekol Pol. 2014;85(3):197-203.
19. Bektaş O, Bektaş K, Taşın C. The role of systemic inflammatory indexes in predicting preeclampsia and its severity. Perinatal Journal. 2019;27(2):62-7.
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Mulaim Sizer, Nurullah Peker, Reyhan Gündüz, Mehmet Sıddık Evsen, Nebahat Sunar, Hamdin Günsel. The role of hemogram parameters in predicting the severity of preeclampsia. Ann Clin Anal Med 2024;15(5):369-372
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