Combination of Renal Biomarkers Predicts Acute Kidney Injury in Critically Ill Adults

Abstract

Objective: Most studies so far have focused on the performance of individual biomarkers to detect early acute kidney injury (AKI) in the adult intensive care unit (ICU) patients; however, they have not determined the predictive ability of their combinations. The aim of this study was to compare the predictive abilities of plasma neutrophil gelatinase-associated lipocalin (pNGAL), urine neutrophil gelatinase-associated lipocalin (uNGAL), plasma cystatin C (pCysC), serum creatinine (sCr), and their combinations in detecting AKI in an adult general ICU population. Methods: A total of 100 consecutive ICU patients were included in the analysis. AKI was defined according to RIFLE criteria. Biomarker predictive abilities were evaluated by area under the curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: AKI occurred in 36% of patients 7 days post-admission. All three novel biomarkers as well as sCr had moderate predictive abilities for AKI occurrence. The most efficient combinations (pNGAL + sCr and pNGAL + uNGAL + sCr) were selected to participate in the subsequent analyses. Both combinations, when added to a reference clinical model, increased its AUC significantly (0.858, p = 0.04). Their NRI (0.78, p = 0.0002) was equal to that of pNGAL, but higher than that of the other three biomarkers, whereas their IDI was higher than that of any individual biomarker (0.23, p = 0.0001). Both combinations had better specificities, positive likelihood ratios, and positive predictive values than those of any individual biomarker. Conclusion: The biomarker combinations had better predictive characteristics compared with those of each biomarker alone.