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Biomarkers predict progression of acute kidney injury after cardiac surgery.

ABSTRACT: Being able to predict whether AKI will progress could improve monitoring and care, guide patient counseling, and assist with enrollment into trials of AKI treatment. Using samples from the Translational Research Investigating Biomarker Endpoints in AKI study (TRIBE-AKI), we evaluated whether kidney injury biomarkers measured at the time of first clinical diagnosis of early AKI after cardiac surgery can forecast AKI severity. Biomarkers included urinary IL-18, urinary albumin to creatinine ratio (ACR), and urinary and plasma neutrophil gelatinase-associated lipocalin (NGAL); each measurement was on the day of AKI diagnosis in 380 patients who developed at least AKI Network (AKIN) stage 1 AKI. The primary end point (progression of AKI defined by worsening AKIN stage) occurred in 45 (11.8%) patients. Using multivariable logistic regression, we determined the risk of AKI progression. After adjustment for clinical predictors, compared with biomarker values in the lowest two quintiles, the highest quintiles of three biomarkers remained associated with AKI progression: IL-18 (odds ratio=3.0, 95% confidence interval=1.3-7.3), ACR (odds ratio=3.4, 95% confidence interval=1.3-9.1), and plasma NGAL (odds ratio=7.7, 95% confidence interval=2.6-22.5). Each biomarker improved risk classification compared with the clinical model alone, with plasma NGAL performing the best (category-free net reclassification improvement of 0.69, P<0.0001). In conclusion, biomarkers measured on the day of AKI diagnosis improve risk stratification and identify patients at higher risk for progression of AKI and worse patient outcomes.

SUBMITTER: Koyner JL

PROVIDER: S-EPMC3338298 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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Biomarkers predict progression of acute kidney injury after cardiac surgery.

Koyner Jay L JL Garg Amit X AX Coca Steven G SG Sint Kyaw K Thiessen-Philbrook Heather H Patel Uptal D UD Shlipak Michael G MG Parikh Chirag R CR

Journal of the American Society of Nephrology : JASN 20120301 5

Being able to predict whether AKI will progress could improve monitoring and care, guide patient counseling, and assist with enrollment into trials of AKI treatment. Using samples from the Translational Research Investigating Biomarker Endpoints in AKI study (TRIBE-AKI), we evaluated whether kidney injury biomarkers measured at the time of first clinical diagnosis of early AKI after cardiac surgery can forecast AKI severity. Biomarkers included urinary IL-18, urinary albumin to creatinine ratio ...[more]

PMID: 22383693

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Project description:BackgroundCardiac surgery-associated acute kidney injury (AKI) is associated with increased morbidity and mortality. We examined the utility of combining biomarkers of kidney function loss (serum cystatin C) and kidney tubular damage (urine neutrophil gelatinase-associated lipocalin [NGAL] and Kidney Injury Molecule-1 [KIM-1]) for the prediction of post-cardiac surgery AKI.MethodsSingle-center prospective cohort study of 106 adults undergoing coronary artery bypass grafting and/or valve surgery with cardiopulmonary bypass (CPB). Primary outcome was postoperative in-hospital AKI defined by serum creatinine (SCr)-Kidney Disease: Improving Global Outcomes criteria. Biomarkers were measured preoperatively, 6 hours after CPB and on postoperative days (PODs) 1 to 4.ResultsA total of 23 subjects (21.7%) developed AKI. After adjusting for preoperative left ventricular ejection fraction, body mass index >30 kg/m2, and estimated glomerular filtration rate (eGFR) <60 ml/min per 1.73 m2, the combination of peak serum cystatin C and peak urine KIM-1/creatinine (Cr) (6 hours post-CPB to POD 1) above optimal cutoff significantly associated with postoperative AKI (odds ratio [OR]: 5.32; 95% confidence interval [CI]: 1.31-21.67; P = 0.020). This biomarker combination significantly improved the performance of the clinical model for the prediction of postoperative AKI (area under the curve [AUC]: 0.77, 95% CI: 0.65-0.90 for the clinical model alone versus 0.83, 95% CI: 0.73-0.93 for the clinical model with the addition of biomarker data, P = 0.049).ConclusionsCombining biomarkers of postoperative kidney function loss and postoperative kidney tubular damage significantly improved prediction of in-hospital AKI following cardiac surgery. Future large, multicenter studies are warranted to assess whether panels of biomarkers reflecting distinct pathobiology can be used to guide interventions and improve short- and long-term outcomes in patients undergoing cardiac surgery.

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Biomarkers predict progression of acute kidney injury after cardiac surgery.

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Biomarkers predict progression of acute kidney injury after cardiac surgery.

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