Canadian Journal of Gastroenterology and Hepatology

Canadian Journal of Gastroenterology and Hepatology / 2015 / Article

Original Article | Open Access

Volume 29 |Article ID 814827 | 8 pages | https://doi.org/10.1155/2015/814827

Risk Factors for Mortality in Patients with Alcoholic Hepatitis and Assessment of Prognostic Models: A Population-Based Study

Received03 Oct 2014
Accepted13 Dec 2014

Abstract

BACKGROUND: Severe alcoholic hepatitis (AH) is associated with a substantial risk for short-term mortality.OBJECTIVES: To identify prognostic factors and validate well-known prognostic models in a Canadian population of patients hospitalized for AH.METHODS: In the present retrospective study, patients hospitalized for AH in Calgary, Alberta, between January 2008 and August 2012 were included. Stepwise logistic regression models identified independent risk factors for 90-day mortality, and the discrimination of prognostic models (Model for End-stage Liver Disease [MELD] and Maddrey discriminant function [DF]) were examined using areas under the ROC curves.RESULTS: A total of 122 patients with AH were hospitalized during the study period; the median age was 49 years (interquartile range [IQR] 42 to 55 years) and 60% were men. Median MELD score and Maddrey DF on admission were 21 (IQR 18 to 24) and 45 (IQR 26 to 62), respectively. Seventy-three percent of patients received corticosteroids and/or pentoxifylline, and the 90-day mortality was 17%. Independent predictors of mortality included older age, female sex, international normalized ratio, MELD score and Maddrey DF (all P<0.05). For discrimination of 90-day mortality, the areas under the ROC curves of the prognostic models (MELD 0.64; Maddrey DF 0.68) were similar (P>0.05). At optimal cut-offs of ≥22 for MELD score and ≥37 for Maddrey DF, both models excluded death with high certainty (negative predictive values 90% and 96%, respectively).CONCLUSIONS: In patients hospitalized for AH, well-known prognostic models can be used to predict 90-day mortality, particularly to identify patients with a low risk for death.

Copyright © 2015 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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