Interleukin-6, serum albumin levels, and acute kidney injury jointly predict in-hospital mortality in pediatric COVID-19 patients.

Background: Severe coronavirus disease 2019 (COVID-19) is less common in children; nevertheless, it carries a mortality risk. Accurate prognostic tools for early risk stratification are therefore essential. This study evaluated the predictive capacity of a combination of interleukin-6 (IL-6), serum albumin (ALB), and acute kidney injury (AKI) for in-hospital mortality in this patient group. Methods: A multicenter retrospective cohort study was conducted on pediatric patients with COVID-19 Omicron variant infection hospitalized between December 2021 and January 2022. The patients were stratified into risk groups based on their IL-6 levels, ALB levels, and the presence of AKI. Logistic regression and Cox proportional hazard models were used to evaluate associations between these biomarkers and in-hospital mortality. Results: A total of 119 children (70 males, 49 females) with severe COVID-19 were included in this study. No AKI cases were observed in survivors, whereas 47.1% (8/17) of nonsurvivors had AKI, a statistically significant difference (P<0.001). Univariate logistic regression and multivariate Cox regression analyses identified IL-6, ALB, and creatinine as significant predictors of inpatient mortality [IL-6, hazard ratio (HR): 1.003, 95% confidence interval (CI): 1.001-1.004, P<0.001; ALB, HR: 0.839, 95% CI: 0.761-0.925, P<0.001; creatinine, HR: 1.010, 95% CI: 1.006-1.014, P<0.001]. Receiver operating characteristic (ROC) analysis confirmed IL-6 [cutoff: 83.4 pg/mL, area under the curve (AUC): 0.897, P<0.001] and creatinine (cutoff: 67.05 µmol/L, AUC: 0.885, P<0.001) as strong predictors of mortality. Kaplan-Meier survival analysis showed a significantly higher mortality rate in the high-risk group compared to the medium- and low-risk groups (P<0.001). Conclusions: The combined assessment of IL-6, ALB, and AKI effectively predicts inpatient mortality in pediatric COVID-19 patients, enabling early identification of high-risk cases and supporting stratified clinical management.