ArticleJournal of medical biochemistry2025
Predicting acute kidney injury in children with sepsis using red blood cell distribution and biomarkers (PCT, IL-6, CRP, and cystatin C).
Article in Journal of medical biochemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- The Prognostic Value of Inflammatory Markers in Paediatric Acute Kidney Injury.Journal of clinical medicine · 2026Article
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Authors and funding
6 authors.
Funding
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Abstract
Background: This study aimed to develop a risk score model for predicting acute kidney injury (AKI) in children with sepsis, using red blood cell distribution width (RDW), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and additional biomarkers (PCT, IL-6, CRP, and cystatin C) based on logistic regression (LR) analysis. Methods: Children treated in the ICU of The First Affiliated Hospital of Xinjiang Medical University from July 2021 to August 2022 were enrolled. The experimental group (Exp) included 155 children with sepsis, while the control group (Ctrl) consisted of 70 children. LR analysis was employed to identify factors associated with AKI risk. The Exp was further divided into two subgroups: the routine group (RG, n=77) and the intervention group (IG, n=78). The IG received intervention based on the risk score model, while the RG received routine treatment. Receiver operating characteristic (ROC) curves were used for diagnostic evaluation. Results: The two groups observed significant differences in white blood cell count (WBC) and RDW levels. The development of AKI in sepsis patients was strongly associated with RDW, APACHE II score, and the biomarkers PCT, IL-6, CRP, and cystatin C. After the intervention, the incidence of AKI and AKI grade 3 significantly decreased, along with lower rates of renal replacement therapy and mortality. Conclusions: The LR-based model integrating RDW, APACHE II score, and biomarkers (PCT, IL-6, CRP, cystatin C) effectively predicts the risk of AKI in children with sepsis, offering a valuable tool for early intervention and improved patient outcomes.
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