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Titolo Biomarkers Predict Progression of Acute Kidney Injury after Cardiac Surgery
Autore Jay L. Koyner,* Amit X. Garg,† Steven G. Coca,‡§ Kyaw Sint,‡§ Heather Thiessen-Philbrook,† Uptal D. Patel,| Michael G. Shlipak,¶ and Chirag R. Parikh,‡§ for the TRIBE-AKI - Consortium *Section of Nephrology, Department of Medicine, University of Chicago, Pritzker School of Medicine, Chicago, Illinois; †Division of Nephrology, Department of Medicine, University of Western Ontario, London, Ontario, Canada; ‡Section of Nephrology, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut; §Clinical Epidemiology Research Center, Veterans Affairs Medical Center, West Haven, Connecticut; |Duke University, School of Medicine, Durham, North Carolina; and ¶Division of General Internal Medicine, San Francisco, Veterans Adminstration Medical Center, University of California, San Francisco, California
Referenza J Am Soc Nephrol 2012; doi: 10.1681/ASN.2011090907

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 clinicaldiagnosis of earlyAKI after cardiac surgery can forecastAKI severity.Biomarkers included urinary IL-18, urinary albumin to creatinine ratio (ACR), and urinary and plasma neutrophil gelatinaseassociated lipocalin (NGAL); eachmeasurement was on the day ofAKI diagnosis in 380 patients who developed at leastAKI Network (AKIN) stage 1AKI. The primary end point (progression ofAKI defined byworsening 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).Eachbiomarker 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.

Data 18.10.2012
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