JOURNAL ARTICLE

Improved performance of urinary biomarkers of acute kidney injury in the critically ill by stratification for injury duration and baseline renal function

Zoltán H Endre, John W Pickering, Robert J Walker, Prasad Devarajan, Charles L Edelstein, Joseph V Bonventre, Christopher M Frampton, Michael R Bennett, Qing Ma, Venkata S Sabbisetti, Vishal S Vaidya, Angela M Walcher, Geoffrey M Shaw, Seton J Henderson, Maryam Nejat, John B W Schollum, Peter M George
Kidney International 2011, 79 (10): 1119-30
21307838
To better understand the diagnostic and predictive performance of urinary biomarkers of kidney injury, we evaluated γ-glutamyltranspeptidase (GGT), alkaline phosphatase (AP), neutrophil-gelatinase-associated lipocalin (NGAL), cystatin C (CysC), kidney injury molecule-1 (KIM-1), and interleukin-18 (IL-18) in a prospective observational study of 529 patients in 2 general intensive care units (ICUs). Comparisons were made using the area under the receiver operator characteristic curve (AUC) for diagnosis or prediction of acute kidney injury (AKI), dialysis, or death, and reassessed after patient stratification by baseline renal function (estimated glomerular filtration rate, eGFR) and time after renal insult. On ICU entry, no biomarker had an AUC above 0.7 in the diagnosis or prediction of AKI. Several biomarkers (NGAL, CysC, and IL-18) predicted dialysis (AUC over 0.7), and all except KIM-1 predicted death at 7 days (AUC between 0.61 and 0.69). Performance was improved by stratification for eGFR or time or both. With eGFR <60 ml/min, CysC and KIM-1 had AUCs of 0.69 and 0.73, respectively, within 6 h of injury, and between 12 and 36 h, CysC (0.88), NGAL (0.85), and IL-18 (0.94) had utility. With eGFR >60 ml/min, GGT (0.73), CysC (0.68), and NGAL (0.68) had the highest AUCs within 6 h of injury, and between 6 and 12 h, all AUCs except AP were between 0.68 and 0.78. Beyond 12 h, NGAL (0.71) and KIM-1 (0.66) performed best. Thus, the duration of injury and baseline renal function should be considered in evaluating biomarker performance to diagnose AKI.

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