ArticlePediatric nephrology (Berlin, Germany)2026
Efficacy of the STARZ stratification score in determining the risk of acute kidney injury in critically ill neonates.
Article in Pediatric nephrology (Berlin, Germany), 2026. 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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1 citing paper in PubMed.
- External validation of the STARZ score highlights structural limits of neonatal AKI prediction models.Pediatric nephrology (Berlin, Germany) · 2026Article
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8 authors.
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Abstract
backgroundNeonatal acute kidney injury (AKI) is a frequent and severe complication in critically ill newborns. The STARZ score was originally developed and validated in the Indian population to stratify AKI risk during the first week of hospitalization, with limited validation in other settings. This study aimed to evaluate its predictive performance for AKI and mortality at two timepoints during early Neonatal Intensive Care Unit (NICU) hospitalization and to validate it in our setting.
methodsA prospective cohort study was conducted in the NICU of Guillermo Grant Benavente Hospital, Chile, between August 2023 and April 2024. Neonates ≥ 25 weeks gestational age and ≥ 500 g birth weight were included. The STARZ score was calculated at 12 and 48-72 h post-admission. The analyses included logistic regression, ROC curves, and reliability testing.
resultsOf 113 neonates, 19 (16.8%) developed AKI. AKI was significantly associated with gestational age < 29 weeks and birth weight < 1000 g. The STARZ score demonstrated modest discriminatory capacity for AKI, with an AUC of 0.66 at 12 h and 0.72 at 48-72 h, with no significant differences observed between time points. For mortality, the score yielded an AUC of 0.91.
conclusionsThe STARZ score showed lower predictive performance for AKI than in the original reports, while its association with mortality should be interpreted cautiously, as it may reflect AKI severity. These findings highlight the need to validate and adapt clinical risk scores across settings and develop future tools incorporating early and sensitive biomarkers for improved risk stratification.
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