BackgroundNew renal biomarkers measured in urine promise to increase specificity for risk stratification and early diagnosis of acute kidney injury (AKI) but concomitantly may be altered by urine concentration effects and chronic renal insufficiency. This study therefore directly compared the performance of AKI biomarkers in urine and plasma.MethodsThis single-center, prospective cohort study included 110 unselected adults undergoing cardiac surgery with cardiopulmonary bypass between 2009 and 2010. Plasma and/or urine concentrations of creatinine, cystatin C, neutrophil gelatinase-associated lipocalin (NGAL), liver fatty acid-binding protein (L-FABP), kidney injury molecule 1 (KIM1), and albumin as well as 15 additional biomarkers in plasma and urine were measured during the perioperative period. The primary outcome was AKI defined by AKIN serum creatinine criteria within 72 hours after surgery.ResultsBiomarkers in plasma showed markedly better discriminative performance for preoperative risk stratification and early postoperative (within 24h after surgery) detection of AKI than urine biomarkers. Discriminative power of urine biomarkers improved when concentrations were normalized to urinary creatinine, but urine biomarkers had still lower AUC values than plasma biomarkers. Best diagnostic performance 4h after surgery had plasma NGAL (AUC 0.83), cystatin C (0.76), MIG (0.74), and L-FAPB (0.73). Combinations of multiple biomarkers did not improve their diagnostic power. Preoperative clinical scoring systems (EuroSCORE and Cleveland Clinic Foundation Score) predicted the risk for AKI (AUC 0.76 and 0.71) and were not inferior to biomarkers. Preexisting chronic kidney disease limited the diagnostic performance of both plasma and urine biomarkers.ConclusionsIn our cohort plasma biomarkers had higher discriminative power for risk stratification and early diagnosis of AKI than urine biomarkers. For preoperative risk stratification of AKI clinical models showed similar discriminative performance to biomarkers. The discriminative performance of both plasma and urine biomarkers was reduced by preexisting chronic kidney disease.

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IntrRenal biomarkers represent an attractive new diagnostic tool which not only implies early diagnosis of AKI, but provides also information about patients at risk for AKI and prediction of adverse clinical outcome parameters like the need for renal replacement therapy, length of stay in ICU and mortality. Biomarker levels in urine however may be altered by intravascular volume availability and chronic renal insufficiency. ObjectivesThis study directly compared the diagnostic and prognostic performance of biomarkers in urine and plasma. MethodsThis prospective cohort study included 110 unselected adults undergoing cardiac surgery. Plasma and/or urine concentrations of creatinine, cystatin C, neutrophil gelatinase-associated lipocalin (NGAL), liver fatty acid-binding protein (L-FABP), kidney injury molecule 1 (KIM1), and albumin and furthermore a multiplex panel of 15 biomarkers in plasma and urine were measured during the perioperative period. The primary outcome was AKI defined by AKIN criteria. ResultsBiomarkers in plasma showed markedly better predictive and diagnostic performance than their urinary counterparts. Discriminative power of urinary biomarkers improved when concentrations were related to urinary creatinine but still did not achieve AUC values of markers measured in plasma samples. Before surgery plasma IP10 (interferon-γ-induced protein 10, CXCL 10), cystatin C and MIG (monokine induced by interferon-γ, CXCL9) best predicted postoperative AKI (AUC 0.73-0.70). Best diagnostic performance 4h after surgery had NGAL (AUC 0.83), cystatin C (0.76), and MIG (0.74) in plasma. Combination with clinical scores (EuroSCORE and Cleveland Clinic Foundation Score) or combinations of several biomarkers did not significantly improve predictive or diagnostic power of either plasma or urine markers. ConclusionsIn our cohort plasma biomarkers had higher discriminative power to predict and to diagnose AKI than urine biomarkers. Plasma IP10 and NGAL performed best in predicting and diagnosing AKI respectively. Their performance could not be improved by combining with clinical scores or additional biomarkers.