Development and validation of a prediction model for in-hospital mortality in intensive care unit patients with cirrhosis and sepsis: a multicentre retrospective cohort study.

Introduction: This study aimed to develop and validate a novel prediction model for in-hospital mortality among patients with cirrhosis and sepsis admitted to the intensive care unit (ICU). Methods: Data were obtained from three multicentre databases: the Medical Information Mart for Intensive Care IV (MIMIC-IV v3.1), the eICU Collaborative Research Database (eICU-CRD v2.0), and the Shenzhen People's Hospital ICU (SZPH-ICU). The MIMIC-IV cohort was chronologically divided into a training set (2008-2016) and a temporal validation set (2017-2022), whereas the eICU-CRD and SZPH-ICU cohorts were used for external validation. Variable selection was performed using the least absolute shrinkage and selection operator (LASSO) regression. A multivariable logistic regression model was constructed and visualized as a nomogram. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC), Brier score, calibration plots, and decision curve analysis. A web-based calculator was developed to facilitate clinical implementation. Results: A total of 2,052 adult ICU patients with cirrhosis and sepsis from the MIMIC-IV database were included. The training cohort (2008-2016; Conclusions: This validated multivariable prediction model accurately estimates in-hospital mortality in ICU patients with cirrhosis and sepsis, supporting early risk stratification and more efficient allocation of clinical resources.