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Acute Kidney Disease and Acute Kidney Injury Biomarkers in Coronary Care Unit Patients

Overview
Journal BMC Nephrol
Publisher Biomed Central
Specialty Nephrology
Date 2020 Jun 4
PMID 32487168
Citations 20
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Abstract

Background: Acute kidney disease (AKD) describes acute or subacute damage and/or loss of kidney function for a duration of between 7 and 90 days after exposure to an acute kidney injury (AKI) initiating event. This study investigated the predictive ability of AKI biomarkers in predicting AKD in coronary care unit (CCU) patients.

Methods: A total of 269 (mean age: 64 years; 202 (75%) men and 67 (25%) women) patients admitted to the CCU of a tertiary care teaching hospital from November 2009 to September 2014 were enrolled. Information considered necessary to evaluate 31 demographic, clinical and laboratory variables (including AKI biomarkers) was prospectively recorded on the first day of CCU admission for post hoc analysis as predictors of AKD. Blood and urinary samples of the enrolled patients were tested for neutrophil gelatinase-associated lipocalin (NGAL), cystatin C (CysC) and interleukin-18 (IL-18).

Results: The overall hospital mortality rate was 4.8%. Of the 269 patients, 128 (47.6%) had AKD. Multivariate logistic regression analysis revealed that age, hemoglobin, ejection fraction and serum IL-18 were independent predictors of AKD. Cumulative survival rates at 5 years of follow-up after hospital discharge differed significantly (p < 0.001) between subgroups of patients diagnosed with AKD (stage 0A, 0C, 1, 2 and 3). The overall 5-year survival rate was 81.8% (220/269). Multivariate Cox proportional hazard analysis revealed that urine NGAL, body weight and hemoglobin level were independent risk factors for 5-year mortality.

Conclusions: This investigation confirmed that AKI biomarkers can predict AKD in CCU patients. Age, hemoglobin, ejection fraction and serum IL-18 were independently associated with developing AKD in the CCU patients, and urine NGAL, body weight and hemoglobin level could predict 5-year survival in these patients.

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