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Acute kidney injury (AKI) is a common post-cardiac surgery complication and influences patient morbidity and prognosis. This study was designed to identify preoperative candidate urine biomarkers in patients undergoing cardiac surgery.
A prospective cohort study of adults undergoing cardiac surgery at increased risk for AKI at a single hospital between July 2010 and September 2012 was performed. The primary outcome was the development of AKI, defined as an absolute serum creatinine (SCr) level increase ≥ 0.5 mg/dL or a ≥ 50% relative increase within 72 h of surgery. A secondary outcome was development of AKI defined by Kidney Disease Improving Global Outcomes (KDIGO). Urine collected by voiding within 4 h prior to surgery was used for proteomic analysis and confirmatory enzyme linked immunosorbent assays (ELISAs) studies. Biomarkers were tested for AKI-prediction using Cox and Snell R2, area under the receiver operating curve (AUROC), and percent of corrected classifications. To evaluate the added effect of each candidate biomarker on AKI discrimination, receiver operator characteristic (ROC) curves, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were calculated.
Forty-seven of 755 patients met screening criteria including 15 with AKI. Proteomic analysis identified 29 proteins with a significant ≥2-fold change. Confirmatory ELISA measurements of five candidate markers showed urinary complement factor B (CFB) and histidine rich glycoprotein (HRG) concentrations were significantly increased in patients with AKI. By multivariate analysis, NRI, and IDI the addition of CFB and HRG to the standard clinical assessment significantly improved risk prediction for the primary outcome. Only HRG was a significant predictor in the 21 patients with AKI defined by KDIGO criteria.
Pre-operative urine measurement of CFB or HRG significantly enhanced the current post-surgery AKI risk stratification for more restrictive definition of AKI. HRG, but not CFB or clinical risk stratification, predicted AKI defined by KDIGO. The ability of these biomarkers to predict risk for dialysis-requiring AKI or death could not be reliably assessed in our study due to a small number of patients with either outcome.