Incorporation of Biomarkers with the Renal Angina Index for Prediction of Severe AKI in Critically Ill Children

Abstract

Novel AKI biomarkers carry variable performance for prediction of AKI in patients with heterogeneous illness. Until utility is demonstrated in critically ill patients outside of the cardiopulmonary bypass population, AKI biomarkers are unlikely to gain widespread implementation. Operationalization of an AKI risk stratification methodology, termed renal angina, was recently reported to enhance prediction at the time of intensive care unit admission for persistent severe AKI. The renal angina index (RAI) was developed to provide the clinical context to direct AKI biomarker testing. This study tested the hypothesis that incorporation of AKI biomarkers in patients fulfilling renal angina improves the prediction of persistent severe AKI. In a multicenter study of 214 patients admitted to the pediatric intensive care unit with sepsis, the discrimination of plasma neutrophil gelatinase-associated lipocalin (NGAL), matrix metalloproteinase-8 (MMP-8), and neutrophil elastase-2 (Ela-2) were determined individually and in combination with the RAI for severe AKI. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated. Individual biomarkers demonstrated marginal discrimination for severe AKI (area under curve [AUC]: NGAL, 0.72; MMP-8, 0.68; Ela-2, 0.72), inferior to prediction by the clinical model of the RAI (AUC=0.80). Incorporation of each biomarker significantly added to the renal angina model AKI prediction (AUC=0.80, increased to 0.84-0.88; P<0.05 for each). The inclusion of each biomarker with the RAI demonstrated NRI (0.512, 0.428, and 0.545 for NGAL, MMP-8, and Ela-2, respectively; all P<0.03) and IDI (0.075 for Ela-2). The inclusion of both Ela-2 and NGAL with RAI demonstrated an NRI of 0.871 (P<0.001) and an IDI of 0.1 (P=0.01). This study shows that incorporation of AKI biomarkers into the RAI improves discrimination for severe AKI. The RAI optimizes the utility of AKI biomarkers in a heterogeneous, critically ill patient population.