Over the last decade there has been considerable progress in the discovery and development of biomarkers of kidney disease, and several have now been evaluated in different clinical settings. Although there is a growing literature on the performance of various biomarkers in clinical studies, there is limited information on how these biomarkers would be utilized by clinicians to manage patients with acute kidney injury (AKI). Recognizing this gap in knowledge, we convened the 10th Acute Dialysis Quality Initiative meeting to review the literature on biomarkers in AKI and their application in clinical practice. We asked an international group of experts to assess four broad areas for biomarker utilization for AKI: risk assessment, diagnosis, and staging; differential diagnosis; prognosis and management; and novel physiological techniques including imaging. This article provides a summary of the key findings and recommendations of the group, to equip clinicians to effectively use biomarkers in AKI.

Background. Early detection of acute tubular necrosis (ATN) could permit implementation of salvage therapies and improve patient outcomes in acute renal failure (ARF). The utility of single and combined measurements of urinary tubular enzymes in predicting ARF in critically ill patients has not been evaluated using the receiver‐operating characteristic (ROC) plot method. Methods. In this prospective pilot study, 26 consecutive critically ill adult patients admitted to the intensive‐care unit were studied. Urine samples were collected twice daily for up to 7 days. ARF was defined as an increase in plasma creatinine of ≥50% and ≥0.15 mmol/l. ROC plot analysis was applied to the tubular marker data to derive optimum cut‐offs for ARF. Results. Four of the 26 study subjects (15.4%) developed ARF. Indexed to urinary creatinine concentration, γ glutamyl transpeptidase (γGT), alkaline phosphatase (AP), N‐acetyl‐glucosaminidase (NAG), and α‐ and π‐glutathione S‐transferase (α‐ and π‐GST) but not lactate dehydrogenase (LDH) were higher in the ARF group on admission (P<0.05). γGT, and α‐ and π‐GST remained elevated at 24 h. The onset of ARF based on changes in plasma creatinine varied from 12 h to 4 days (median 36 h). ROC plot analysis showed that γGT, π‐GST, α‐GST, AP and NAG had excellent discriminating power for ARF (AUC 0.950, 0.929, 0.893, 0.863 and 0.845, respectively). The discriminating strength of creatinine clearance, while lower, was still significant (AUC 0.796). Positive and negative predictive values for ARF on admission were 67/100% for γGT, 67/90% for AP, 60/95% for α‐GST, and 67/100% for π‐GST indices. Positive and negative predictive values for ARF for creatinine clearance ≤23 ml/min were 50 and 91%, respectively. Creatinine clearances tended to be lower in ARF than in non‐ARF patients on admission (P=0.06) and were significantly lower (P=0.008) after 12 h. Plasma urea and fractional sodium excretion were unhelpful. Conclusions. Tubular enzymuria on admission to the ICU is useful in predicting ARF. The cheapness and wide availability of automated assays for γGT and AP suggests that estimation of these enzymes in random urine samples may be particularly useful for identifying patients at high risk of ARF.