Machine Learning Prediction of Poor Flexion-Extension Outcome After Open Elbow Arthrolysis: Identifying Individual Predisposition Using Clinical and Laboratory Indicators.

ABSTRACT:

Background

Elbow stiffness is a condition that causes mobility dysfunction and severe suffering in patients. Patients with posttraumatic elbow stiffness who undergo open elbow arthrolysis are at risk for poor postoperative flexion-extension outcome, which leads us to suspect that these patients possess a unique "elbow stiffness predisposition."

Purpose

To develop an innovative predictive model that combines clinical and laboratory indicators to forecast poor flexion-extension outcomes after open elbow arthrolysis, thereby interpreting the "elbow stiffness predisposition."

Study design

Cohort study; Level of evidence, 3.

Methods

Patients who underwent open elbow arthrolysis between 2019 and 2022 were selected for model training and validation (n = 254), while th

SUBMITTER: Wang X 

PROVIDER: S-EPMC12717415 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature