Risk prediction for severe acute kidney injury by integration of urine output, glomerular filtration, and urinary cell cycle arrest biomarkers.

Background: Frequent assessment of urine output (UO), serum creatinine (sCr) and urinary cell cycle arrest biomarkers (CCAB) may improve acute kidney injury (AKI) prediction.

Objective: To study the performance of UO, short term sCr changes and urinary CCAB to predict severe AKI.

Methods: We measured 6 hours of UO, 6-hourly sCr changes, and urinary CCABs in all critically ill patients with cardiovascular or respiratory failure or early signs of renal stress between February and October 2018. We studied the association of such measurements, and their combination, with the development of AKI Stage 2 or 3 of the Kidney Disease: Improving Global Outcomes (KDIGO) definition at 12 hours. We evaluated predictive performance with logistic regression, area under the receiver operating characteristic (AUROC) curve, and net reclassification indices. We computed an optimal cut-off value for each biomarker.

Results: We assessed 622 patients and, as per the exclusion criteria, we enrolled 105 critically ill patients. After 12 hours of enrolment, AKI occurred in 32 patients (30%). UO, sCr change over 6 hours and CCABs were significantly associated with severe AKI at 12 hours, with all variables achieving an AUROC > 0.7 after adjustment. Combination of any of the two or three variables achieved an AUROC > 0.7 for subsequent severe AKI at 12 hours. The optimal predictive high specificity cut-off values were ≤ 0.4 mL/kg/h for UO, variation of +15 μmol/L over 6 hours in sCr, and ≥ 1.5 (ng/mL)/1000 for CCABs.

Conclusion: In this prospective study, an integrative approach using UO, short term sCr change and/or urinary CCABs showed a satisfactory performance for the prediction of severe AKI development at 12 hours.