The relationship between clinical subtypes, prognosis, and treatment in ICU patients with acute cholangitis using unsupervised machine learning methods.

ABSTRACT:

Background

Acute cholangitis (AC) presents with significant clinical heterogeneity, and existing severity classifications have limited prognostic value in critically ill patients. Subtypes of AC in critically ill patients have not been investigated.

Objective

The study aimed to offer a novel approach to identify clinical subtypes and improve individualized risk assessment and treatment strategies using an unsupervised analysis.

Methods

We conducted a retrospective analysis of ICU patients with AC from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. K-means clustering was applied to 24 routinely available clinical variables from the first 24 h of ICU admission to identify clinical subtypes. The primary outcome was 28-day all-cause mortality. Mul

SUBMITTER: Sheng Y 

PROVIDER: S-EPMC12323092 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature