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.