Novel Prognostic Model to Predict In-Hospital Mortality in Patients with Liver Cirrhosis.

Authors

Hendra Raharja, Taufik Sungkar, Ilhamd Ilhamd

Published in

Acta medica Indonesiana. Volume 58. Issue 3. Pages 362-368.

Abstract

Liver cirrhosis remains a major global health concern associated with high in-hospital mortality, especially in Southeast Asia. Existing prognostic scores, such as Child-Pugh and albumin-bilirubin scores, exhibit variable accuracy, necessitating simpler and more practical tools. This study aimed to identify independent predictors and to propose a novel prognostic model of in-hospital mortality in hospitalized cirrhosis patients.
This retrospective cohort study included 190 patients with cirrhosis who were admitted to Adam Malik General Hospital, Medan, between 2022 and 2023. Demographic, clinical, and laboratory data were analyzed using univariate and multivariate logistic regression. A prognostic model was derived from significant variables and evaluated using the area under the receiver operating characteristic curve (AUROC) and Hosmer-Lemeshow test.
Of the 190 patients, 79 (41.6%) died during hospitalization. Independent predictors of in-hospital mortality were grade III-IV hepatic encephalopathy (odds ratio [OR] 30.12, 95% confidence interval [CI] 10.71-84.67, p<0.001), serum creatinine (ln-transformed; OR 3.23, 95% CI 1.80-5.79, p<0.001), and international normalized ratio (ln-transformed; OR 17.93, 95% CI 3.54-90.83, p<0.001). The model demonstrated excellent discrimination (AUROC 0.906) and good calibration (Hosmer-Lemeshow p = 0.587).
Severe hepatic encephalopathy, renal dysfunction, and coagulopathy were the strongest predictors of in-hospital mortality among patients with cirrhosis. The model derived from these factors demonstrated reliable accuracy in this retrospective cohort and may support risk stratification in clinical practice. However, prospective multicenter studies are required to confirm the validity and clinical utility of this model before its routine application.

PMID:
42845079
Bibliographic data and abstract were imported from PubMed on 08 Oct 2026.

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