Development and validation of machine learning models to predict esophagogastric variceal rebleeding risk in HBV-related cirrhosis after endoscopic treatment: a prospective multicenter study.

ABSTRACT:

Background

Rebleeding after initial endoscopic therapy is associated with high mortality in patients with hepatitis B virus (HBV)-related liver cirrhosis complicated by esophagogastric variceal bleeding (EGVB), imposing a substantial public health burden. Spontaneous portosystemic shunts (SPSS), a compensatory mechanism for portal hypertension, are closely associated with disease progression. This study aimed to develop and validate machine learning (ML) models incorporating clinical and imaging features to predict the risk and frequency of rebleeding following initial endoscopic treatment.

Methods

This multicenter prospective study enrolled patients with HBV-related cirrhosis and EGVB treated at Zhongshan Hospital, Fudan University (the development cohort). External validat

SUBMITTER: Zheng L 

PROVIDER: S-EPMC12395071 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature