Predicting acute kidney injury using urinary liver-type fatty-acid binding protein and serum N-terminal pro-B-type natriuretic peptide levels in patients treated at medical cardiac intensive care units

Abstract

Background

The early prediction of acute kidney injury (AKI) can facilitate timely intervention and prevent complications. We aimed to understand the predictive value of urinary liver-type fatty-acid binding protein (L-FABP) levels on admission to medical (non-surgical) cardiac intensive care units (CICUs) for AKI, both independently and in combination with serum N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels.

Methods

We prospectively investigated the predictive value of L-FABP and NT-proBNP for AKI in a large, heterogeneous cohort of patients treated in medical CICUs. Baseline urinary L-FABP and serum NT-proBNP were measured on admission. AKI was diagnosed according to the Kidney Disease: Improving Global Outcomes criteria. We studied 1273 patients (mean age, 68 years), among whom 46% had acute coronary syndromes, 38% had acute decompensated heart failure, 5% had arrhythmia, 3% had pulmonary hypertension, 2% had acute aortic syndrome, 2% had infective endocarditis, and 1% had Takotsubo cardiomyopathy.

Results

Urinary L-FABP levels correlated with serum NT-proBNP levels ( r = 0.17, p < 0.0001). AKI occurred in 224 patients (17.6%), including 48 patients with stage 2 or 3 disease. Patients who developed AKI had higher one-week and 6-month mortality than those who did not develop AKI ( p = 0.0002 and p = 0.003, respectively). In the multivariate logistic analysis, both L-FABP ( p < 0.0001) and NT-proBNP ( p = 0.006) were independently associated with the development of AKI. Adding L-FABP and NT-proBNP to a baseline model that included established risk factors further improved reclassification ( p < 0.001) and discrimination ( p < 0.01) beyond that of the baseline model or any single biomarker individually.

Conclusions

Urinary L-FABP and serum NT-proBNP levels on admission are independent predictors of AKI, and when used in combination, improve early prediction of AKI in patients hospitalized at medical CICUs.