ArticlePediatric nephrology (Berlin, Germany)2022
Validation of the STARZ neonatal acute kidney injury risk stratification score.
Article in Pediatric nephrology (Berlin, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
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Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.
- Novel biomarkers for acute kidney injury in high-risk pediatric populations: a systematic review.Renal failure · 2026Pooled it
- Risk factors for acute kidney injury in pediatric intensive care units: a systematic review and meta-analysis.BMC pediatrics · 2026Pooled it
- Time to diagnosis of acute kidney injury and its predictors among outborn neonates in India: a competing-risk analysis of tele-ICU network data (2022-2024).The Lancet regional health. Southeast Asia · 2026Article
- Validation of STARZ scoring in very low birth weight (VLBW) neonates in the United States.Pediatric research · 2026Article
- Efficacy of the STARZ stratification score in determining the risk of acute kidney injury in critically ill neonates.Pediatric nephrology (Berlin, Germany) · 2026Article
- Continuous kidney replacement therapy with CARPEDIEMPediatric nephrology (Berlin, Germany) · 2026Article
- Interpretable machine learning for the early prediction of acute kidney injury in preterm infants in the neonatal intensive care unit.Renal failure · 2025Article
- Development and validation of a nomogram for predicting neonatal acute kidney injury in very low birth weight infants.Maternal health, neonatology and perinatology · 2025Article
- Evidence-based risk stratification for neonatal acute kidney injury: a call to action.Pediatric nephrology (Berlin, Germany) · 2025Article
- Advances in pediatric acute kidney injury detection and prediction: biomarkers and artificial intelligence.World journal of pediatrics : WJP · 2025Article
- Machine learning based clinical decision tool to predict acute kidney injury and survival in therapeutic hypothermia treated neonates.Scientific reports · 2025Article
- Artificial intelligence in early detection and prediction of pediatric/neonatal acute kidney injury: current status and future directions.Pediatric nephrology (Berlin, Germany) · 2024Review
- Use of furosemide in preterm neonates with acute kidney injury is associated with increased mortality: results from the TINKER registry.Pediatric nephrology (Berlin, Germany) · 2024Article
- CARPEDIEM® for continuous kidney replacement therapy in neonates and small infants: a French multicenter retrospective study.Pediatric nephrology (Berlin, Germany) · 2023Article
- STARZ Neonatal AKI Risk Stratification Cut-off Scores for Severe AKI and Need for Dialysis in Neonates.Kidney international reports · 2022Article
- Perspectives: Neonatal acute kidney injury (AKI) in low and middle income countries (LMIC).Frontiers in pediatrics · 2022Article
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Authors and funding
21 authors at 15 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundNeonatal acute kidney injury (AKI) is common in neonatal intensive care units (NICU) and leads to worse outcomes. Stratifying neonates into an "at risk" category allows health care providers to objectively recognize opportunities for improvements in quality of care.
methodsThe "Neonatal AKI Risk Prediction Scoring" was devised as the "STARZ [Sethi, Tibrewal, Agrawal, Raina, waZir]" Score. The STARZ score was derived from our prior multicentre study analysing risk factors for AKI in neonates admitted to the NICU. This tool includes 10 variables with a total score ranging from 0 to 100 and a cut-off score of 31.5. In the present study, the scoring model has been validated in our multicentre cohort of 744 neonates.
resultsIn the validation cohort, this scoring model had sensitivity of 82.1%, specificity 91.7%, positive predictive value 81.2%, negative predictive value 92.2% and accuracy 88.8%. Based on the STARZ cut-off score of ≥ 31.5, an area under the receiver operating characteristic (ROC) curve was observed to be 0.932 (95% CI, 0.910-0.954; p < 0.001) signifying that the discriminative power was high. In the validation cohort, the probability of AKI was less than 20% for scores up to 32, 20-40% for scores between 33 and 36, 40-60% for scores between 37 and 43, 60-80% for scores between 44 and 49, and ≥ 80% for scores ≥ 50.
conclusionsTo promote the survival of susceptible neonates, early detection and prompt interventional measures based on highly evidenced research is vital. The risk of AKI in admitted neonates can be quantitatively determined by the rapid STARZ scoring system. A higher resolution version of the Graphical abstract is available as Supplementary information.
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