Validation of STARZ Score for Early Neonatal AKI

Overview

Neonatal acute kidney injury (AKI) is a common complication in the NICU, associated with high morbidity and mortality. Prematurity, low birthweight, sepsis, asphyxia, congenital heart disease, and nephrotoxic drugs are major risk factors. Early diagnosis is challenging as serum creatinine lacks sensitivity. The STARZ score, a composite clinical-laboratory tool, has shown high accuracy for predicting early neonatal AKI. This study aims to validate the STARZ score in neonates admitted to Assiut University Children's Hospital for early identification of AKI and improved clinical outcomes."

Neonatal acute kidney injury (AKI) is a frequent and serious complication in the neonatal intensive care unit (NICU), with incidence rates ranging from 6% to 24% and reaching up to 70% in high-risk populations depending on diagnostic criteria. Prematurity, low birthweight, sepsis, perinatal asphyxia, congenital heart disease, respiratory distress, shock, and exposure to nephrotoxic medications are established risk factors. Neonatal AKI is associated with increased mortality, prolonged hospitalization, and long-term renal complications, including chronic kidney disease. Traditional diagnostic tools, such as serum creatinine, are limited by delayed changes and poor sensitivity in neonates. Risk stratification models offer an opportunity for earlier detection and proactive intervention. The STARZ score is a composite risk assessment tool incorporating clinical and laboratory parameters, and has demonstrated high predictive accuracy in previous studies, with sensitivity above 85% and specificity around 90% for early neonatal AKI. This prospective study at Assiut University Children's Hospital aims to validate the STARZ score for predicting neonatal AKI within the first 7 days of NICU admission. The study will assess its predictive performance compared with conventional criteria, evaluate its role in risk stratification and guiding timely interventions, and examine the potential benefits in terms of cost-effectiveness and healthcare resource utilization.

Conditions