The effect of the HALP score on clinical course and prognosis in acute kidney injury

Abstract

AimDialysis-requiring acute kidney injury is a critical condition associated with considerable morbidity and mortality. The HALP score, which integrates hematologic and nutritional parameters, has been proposed as an indicator of inflammatory and nutritional status. However, its prognostic significance in patients with AKI remains uncertain. This study aimed to investigate the association between the HALP score and clinical outcomes, including in-hospital mortality and renal prognosis, in patients with dialysis-requiring AKI. MethodsA total of 134 patients were retrospectively analyzed. Clinical, demographic, and laboratory data at admission and discharge were recorded. Multivariable logistic regression was used to identify independent predictors of mortality, and ordinal logistic regression was performed to assess renal outcome severity among survivors. Receiver operating characteristic (ROC) analysis was conducted to evaluate model performance. ResultsOf the patients, 58 (43.3%) died during hospitalization. Patients in the mortality group were older and had fewer hemodialysis sessions. Albumin levels were significantly lower in the mortality group at both time points (P < .001). In multivariable analysis, albumin was an independent predictor of mortality in both admission (OR:0.885, P < .001) and discharge models (OR:0.799, P < .001). Age was also independently associated with mortality, while the number of hemodialysis sessions was inversely associated with mortality (P = .017). HALP score was not significantly associated with outcomes (P > .05). The discharge model showed superior performance (AUC:0.88 vs 0.77). ConclusionAlbumin and age are strong predictors of mortality, whereas the HALP score has limited prognostic value in AKI. Dynamic clinical parameters provide superior prognostic information.

Keywords

Introduction

Acute kidney injury (AKI) represents a complex and rapidly evolving clinical syndrome that contributes substantially to patient morbidity and mortality. It is estimated that AKI affects approximately 13.3 million individuals worldwide each year, with the majority of cases occurring in developing regions.^1,2
The diagnosis of AKI is based on a rapid decline in renal function, typically identified by rising serum creatinine levels or reduced urine output over a defined period.³ Although the causal relationship between AKI and mortality is multifactorial and not fully understood, it is associated with a considerable number of deaths annually.⁴ The clinical course of AKI varies widely depending on the underlying cause and clinical context, and both its severity and duration play a critical role in determining patient outcomes. In addition, AKI is now recognized as a condition with potential long-term complications, including progression to chronic kidney disease (CKD) and, in some cases, permanent renal replacement therapy.⁵ Therefore, early identification of high-risk patients is crucial for improving both short- and long-term outcomes.
The hemoglobin, albumin, lymphocyte, and platelet (HALP) score is a composite index reflecting both nutritional and inflammatory status. First described in 2015, the HALP score has been explored as a prognostic indicator in various clinical settings.⁶ However, its prognostic utility remains inconsistent across different patient populations, particularly outside oncological settings. Evidence regarding the role of the HALP score in AKI remains limited. Özderya et al. reported that lower HALP scores were associated with the development of post-contrast AKI and mortality in patients undergoing endovascular abdominal aortic aneurysm repair.⁷ However, the generalizability of these findings to broader AKI populations, especially those requiring dialysis, is uncertain.
Due to the limited and conflicting evidence, further investigation is required to clarify its prognostic significance in AKI. Therefore, this study aimed to evaluate the association between HALP scores measured at admission and discharge and clinical outcomes, including in-hospital mortality and renal prognosis, in patients with dialysis-requiring AKI.

Materials and Methods

Study Design and Patient Selection This study was conducted as a retrospective observational study. The hospital electronic medical record system was screened to identify 1,448 adult patients diagnosed with acute kidney injury (AKI) who underwent hemodialysis between January 2015 and May 2025 at the Nephrology Department of Kırıkkale University. After removal of repeated admissions, individual medical records were reviewed. Patients who did not meet the inclusion criteria, met one or more exclusion criteria, or had incomplete medical records were excluded. A total of 134 patients were included in the final analysis. The inclusion criteria were as follows: being 18 years of age or older, having a diagnosis of AKI according to KDIGO criteria, and having complete blood count (CBC) and biochemistry data obtained at the time of hospital admission. Exclusion criteria included patients with a concurrent diagnosis of malignancy, those receiving active immunosuppressive therapy, and patients with incomplete medical records. Ethical Approval The study was approved by the Ethics Committee of Kırıkkale University Faculty of Medicine, Non-Interventional Clinical Research Ethics Committee (Date: 28 May 2025, Decision No: 2025.05.40). At the end of the clinical cours Statistical Analysis All statistical analyses were performed using IBM SPSS Statistics for Windows, Version 22.0 (IBM Corp., Armonk, NY, USA). Continuous variables were expressed as mean ± standard deviation (SD) or median (interquartile range, IQR), as appropriate, and categorical variables were presented as number and percentage. Normality of continuous variables was assessed using the Kolmogorov–Smirnov and Shapiro–Wilk tests. Comparisons between survivors and non-survivors were performed using the independent samples t-test for normally distributed continuous variables and the Mann–Whitney U test for non-normally distributed variables. Categorical variables were compared using the chi-square test or Fisher’s exact test, as appropriate. To identify independent predictors of in-hospital mortality, multivariable logistic regression analysis was performed. Variables considered clinically relevant or found to be significant in univariable analyses were entered into the regression model. Odds ratios (ORs) with 95% confidence intervals (CIs) were reported. Among surviving patients, factors associated with renal outcome severity at discharge were evaluated using ordinal logistic regression analysis. Renal outcome was classified into three ordered categories: no chronic kidney disease, chronic kidney disease without hemodialysis, and chronic kidney disease with hemodialysis. Odds ratios with 95% confidence intervals were calculated. The discriminative performance of the admission and discharge mortality models was assessed using receiver operating characteristic (ROC) curve analysis, and the area under the curve (AUC) was calculated for each model. A two-sided P value of <0.05 was considered statistically significant. Reporting Guidelines This study was reported according to the STROBE guidelines.

Results

Baseline Clinical, Demographic, and Laboratory Characteristics A total of 134 patients were included in the study, of whom 76 survived and 58 died during hospitalization (Figure 1). As shown in Supplementary Table 1, patients in the mortality group were significantly older than those who survived (77.13 ± 14.79 vs 70.56 ± 14.38 years, P = .012). The number of hemodialysis sessions was significantly lower in the mortality group (3.22 ± 3.07 vs 4.25 ± 5.25, P = .048). There was no significant difference between groups in terms of sex distribution (P = .662). At admission, albumin levels were significantly lower in the mortality group (P < .001). No significant differences were observed between groups in terms of hemoglobin, lymphocyte count, platelet count, or HALP score (P > .05). In the final in-hospital laboratory measurements, albumin levels remained significantly lower in the mortality group (P < .001). In addition, platelet counts were significantly lower in the mortality group (P = .037). No significant differences were observed in other parameters (P > .05). According to the multivariable logistic regression analysis presented in Supplementary Table 2, albumin level was identified as an independent predictor of in-hospital mortality in the admission model (OR: 0.885, 95% CI: 0.825–0.948, P < .001). Age was also independently associated with mortality (P = .032). In the discharge model, albumin remained an independent predictor (OR: 0.799, 95% CI: 0.725–0.879, P < .001). Age (P = .004), the number of hemodialysis sessions (P = .017), and lymphocyte count (P = .049) were also independently associated with mortality, whereas the remaining variables were not statistically significant (P > .05). ROC curve analysis (Figure 2) showed that the admission model had an AUC of 0.77, whereas the discharge model demonstrated a higher discriminative performance with an AUC of 0.88. As shown in Supplementary Table 3, in the ordinal logistic regression analysis evaluating factors associated with renal outcomes among surviving patients, age was the only variable independently associated with the severity of renal progression (OR: 1.030, 95% CI: 1.002–1.060, P = .039). Sex and admission laboratory parameters were not found to be statistically significant (P > .05).

Discussion

In the present study, we evaluated the prognostic value of the HALP score in patients with dialysis-requiring acute kidney injury (AKI). The main findings of our study are that albumin level and age were independent predictors of in-hospital mortality, whereas the HALP score did not demonstrate significant prognostic value. In addition, dynamic clinical parameters obtained during the clinical course showed better predictive performance than admission-based measurements.
The HALP score has been proposed as a composite marker reflecting both nutritional and inflammatory status and has been associated with prognosis in various malignancies and chronic conditions.^8-11 However, its prognostic utility has not been consistently demonstrated across different clinical settings. In our study, the HALP score was not significantly associated with mortality, renal outcomes, or other clinical parameters. These findings suggest that the prognostic value of the HALP score may be limited in acute and heterogeneous conditions such as AKI.
Previous studies have reported associations between low HALP scores and increased mortality or adverse outcomes in chronic diseases and oncological populations.^6,9,12,13 Similarly, Özderya et al. reported that lower HALP scores were associated with post-contrast AKI and mortality in patients undergoing endovascular aneurysm repair.⁷ In contrast, our findings did not support a significant relationship between HALP score and clinical outcomes. This discrepancy may be explained by differences in patient populations, as AKI represents a rapidly evolving and multifactorial condition in which laboratory parameters can change significantly over a short period of time.
One of the most important findings of our study is the strong association between albumin levels and in-hospital mortality. Albumin, as a marker of both nutritional status and systemic inflammation, remained an independent predictor in both admission and discharge models.¹⁴ Moreover, the stronger predictive value observed in the discharge model highlights the importance of dynamic monitoring during the clinical course. These findings are consistent with previous studies demonstrating the prognostic significance of hypoalbuminemia in critically ill patients.^15,16
The comparison between admission and discharge models further emphasizes the importance of dynamic clinical assessment. The discharge model demonstrated superior discriminative performance (AUC: 0.88 vs 0.77), suggesting that changes occurring during hospitalization provide more accurate prognostic information than baseline measurements alone. This finding supports the concept that static composite indices such as the HALP score may be less informative than dynamic clinical parameters in acute conditions.
In addition, age was identified as the only independent predictor of renal progression among surviving patients. This finding may reflect the impact of biological aging on renal reserve and recovery capacity.^17-19 The absence of a significant association between admission laboratory parameters and renal outcomes further supports the notion that baseline inflammatory or nutritional markers may not adequately capture long-term renal prognosis in AKI.

Limitations

Our study has several limitations. First, its retrospective and single-center design limits the generalizability of the findings. Second, the HALP score was evaluated only at admission and discharge, and intermediate changes were not assessed. Third, potential confounding factors affecting HALP components were not fully controlled.

Conclusion

In conclusion, our findings suggest that the HALP score has limited prognostic value in patients with dialysis-requiring AKI. In contrast, albumin level and age are strong predictors of mortality, and dynamic clinical parameters provide superior prognostic information compared to admission-based indices. Further large-scale, prospective studies are needed to better define the role of composite inflammatory markers in acute kidney injury.

Declarations

References

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