Chronic major Advanced age Diabetes mellitus Cardiovascular disease CKD Chronic minor Hypertension Morbid obesity Hyperbilirubinemia Cerebrovascular accident AIDS Cancer Acute Hypotension High-risk surgery

Background and objectives Disease biomarkers require appropriate clinical context to be used effectively. Combining clinical risk factors, in addition to small changes in serum creatinine, has been proposed to improve the assessment of AKI. This notion was developed in order to identify the risk of AKI early in a patient’s clinical course. We set out to assess the performance of this combination approach. Design, setting, participants, & measurements A secondary analysis of data from a prospective multicenter intensive care unit cohort study (September 2009 to April 2010) was performed. Patients at high risk using this combination approach were defined as an early increase in serum creatinine of 0.1–0.4 mg/dl, depending on number of clinical factors predisposing to AKI. AKI was defined and staged using the Acute Kidney Injury Network criteria. The primary outcome was evolution to severe AKI (Acute Kidney Injury Network stages 2 and 3) within 7 days in the intensive care unit. Results Of 506 patients, 214 (42.2%) patients had early creatinine elevation and were deemed at high risk for AKI. This group was more likely to subsequently develop the primary endpoint (16.4% versus 1.0% [not at high risk], P,0.001). The sensitivity of this grouping for severe AKI was 92%, the specificity was 62%, the positive predictive value was 16%, and the negative predictive value was 99%. After adjustment for Sequential Organ Failure Assessment score, serum creatinine, and hazard tier for AKI, early creatinine elevation remained an independent predictor for severe AKI (adjusted relative risk, 12.86; 95% confidence interval, 3.52 to 46.97). Addition of early creatinine elevation to the best clinicalmodel improved prediction of the primary outcome (area under the receiver operating characteristic curve increased from 0.75 to 0.83, P,0.001). ConclusionCritically ill patients at highAKI risk, based on the combination of clinical factors and early creatinine elevation, are significantly more likely to develop severe AKI. As initially hypothesized, the high-risk combination group methodology can be used to identify patients at low risk for severe AKI in whom AKI biomarker testing may be expected to have low yield. The high risk combination group methodology could potentially allow clinicians to optimize biomarker use. Clin J Am Soc Nephrol 9: 663–672, 2014. doi: 10.2215/CJN.05190513 Introduction AKI is common in critically ill patients; it occurs in 5.5%–36.1% of intensive care unit (ICU) patients (1– 5). The poor outcomes associated with AKI (5–7) remain unacceptable, and one of the reasons for the lack of progress is that current functional kidney diagnostic tests (e.g., serum creatinine [sCr] and urine output) fail to diagnose AKI in a timely fashion (8,9). A substantial amount of research has been conducted to discover and validate new AKI biomarkers (10–12) that could be used to direct therapeutic and supportive interventions before functional decline. These biomarkers have been referred to as the “search for the renal troponin” (8,9,13). However, when any biomarker is used in the wrong clinical context, the biomarker has diminished discriminative capacity. As an example, when troponin is used among critically ill patients outside of the clinical syndrome of cardiac angina, it does not identify acute myocardial infarction well and performs poorly as a biomarker (14,15). Similarly, if we perform daily blood or urine samples for AKI biomarkers in every patient admitted to the ICU without appropriate risk assessment, testing is neither efficient nor cost effective (13). The question at hand is in which at-risk patient should we test AKI biomarkers? The term “renal angina” (RA) has been recently proposed as an empirical clinical concept to better determine which patients are at highest risk for AKI (13). Due to the number of contributing authors, the affiliations are