Machine learning-based prediction model for post-ERCP cholangitis in patients with malignant biliary obstruction: a retrospective multicenter study.

ABSTRACT:

Background

Endoscopic retrograde cholangiopancreatography (ERCP) is the preferred palliative treatment for patients with unresectable malignant biliary obstruction (MBO), which can relieve biliary obstruction and prolong survival. Post-ERCP cholangitis (PEC) affects the survival of MBO patients. Early prediction of PEC risk is crucial for developing individualized treatment plans and improving prognosis. Currently, no predictive models exist for clinical practice. This study aims to develop and validate an interpretable machine learning prediction model using multicenter cohorts to predict the risk of PEC.

Methods

We collected data from 2831 unresectable MBO patients who underwent ERCP between January 2011 and December 2023. After screening, data from 1026 patients from the

SUBMITTER: Jin H 

PROVIDER: S-EPMC12287249 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature