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Abstract Details
Urinary Liver-Type Fatty Acid Binding Protein (L-FABP) in Early Detection and Outcome Prediction of Sepsis-Associated Acute Kidney Injury.
INTRODUCTION: Acute kidney injury (AKI) is one of the most frequent complications in septic shock cases, and has a high mortality rate. The aim of this study was to determine the value of urinary liver-type fatty acid binding protein (L-FABP) in early detection and outcome prediction of AKI in patients with sepsis and septic shock.
METHODS: This prospective cohort study was conducted on patients who presented to the emergency department (ED) with sepsis or septic shock. Urinary L-FABP levels were measured at the time of admission and patients were classified into AKI and non-AKI groups within 7 days according to the KIDGO Criteria. The screening performance characteristics of urinary L-FABP in early detection of AKI within seven days of admission and need for renal replacement therapy (RRT) were calculated and reported.
RESULTS: 212 patients with the mean age of 66.5 ± 16.2 (range 18-99) years were included (60.4% male). 54 (25.5%) patients had sepsis, and septic shock was developed in 158 (74.53%) cases. 143 (67.5%) patients were complicated with AKI. The area under the receiver operating characteristic (ROC) curve (AUC) of urinary L-FABP in early detection of sepsis-associated AKI was 0.94 (95% confidence interval (CI): 0.90 - 0.97), compared to the AUC of 0.64 (95% CI: 0.54-0.74) for serum creatinine. The sensitivity and specificity of urinary L_FABP at its best cutoff point (13.90 μg L-FABP/g Cr) were 89.9% and 86.3%, respectively. The area under the ROC curve of urinary L-FABP in predicting the need for RRT in sepsis-associated AKI patients was 0.74 (95% CI: 0.64-0.85), compared to the AUC of 0.53 (95% CI: 0.41-0.64) for serum creatinine. The sensitivity and specificity of urinary L-FABP at its best cutoff point (22.05 μg L-FABP/g Cr) were 63.6% and 71.4%, respectively.
CONCLUSIONS: It seems that, L-FABP could be considered as a valuable biomarker for early detection and predicting the severity of AKI in septic patients.