Diagnostic and prognostic performance of urinary neutrophil gelatinase-associated lipocalin in patients with cirrhosis and acute kidney injury.

Abstract

Acute kidney injury (AKI) commonly occurs in patients with decompensated cirrhosis. Urinary neutrophil gelatinase-associated lipocalin (uNGAL) could help discriminate between different etiologies of AKI. The aim of this study was to investigate the use of uNGAL in (1) the differential diagnosis of AKI, (2) predicting the response to terlipressin and albumin in patients with hepatorenal syndrome-AKI (HRS-AKI), and (3) predicting in-hospital mortality in patients with AKI. One hundred sixty-two consecutive patients with cirrhosis and AKI were included from 2015 to 2020 and followed until transplant, death, or 90 days. Standard urinary markers and uNGAL were measured. Data on treatment, type, and resolution of AKI were collected. Thirty-five patients (21.6%) had prerenal AKI, 64 (39.5%) HRS-AKI, 27 (16.7%) acute tubular necrosis-AKI (ATN-AKI), and 36 (22.2%) a mixed form of AKI. Mean values of uNGAL were significantly higher in ATN-AKI than in other types of AKI (1162 ng/ml [95% CI 423-2105 ng/ml] vs. 109 ng/ml [95% CI 52-192 ng/ml]; p < 0.001). uNGAL showed a high discrimination ability in predicting ATN-AKI (area under the receiver operating characteristic curve, 0.854; 95% CI 0.767-0.941; p < 0.001). The best-performing threshold was found to be 220 ng/ml (sensitivity, 89%; specificity, 78%). The same threshold was independently associated with a higher risk of nonresponse (adjusted OR [aOR], 6.17; 95% CI 1.41-27.03; p = 0.016). In multivariable analysis (adjusted for age, Model for End-Stage Liver Disease, acute-on-chronic liver failure, leukocytes, and type of AKI), uNGAL was an independent predictor of in-hospital mortality (aOR, 1.74; 95% CI 1.26-2.38; p = 0.001). uNGAL is an adequate biomarker for making a differential diagnosis of AKI in cirrhosis and predicting the response to terlipressin and albumin in patients with HRS-AKI. In addition, it is an independent predictor of in-hospital mortality.