Development and validation of a machine learning model for predicting preoperative deep vein thrombosis in elderly hip fracture patients.

ABSTRACT:

Background

Hip fractures in older adults pose a global health challenge. Deep vein thrombosis (DVT) is common, increasing surgical risk, delaying procedures, and causing severe thromboembolic events. It hampers recovery and lowers the quality of life. Prompt risk assessment and intervention are crucial. This study aims to develop and validate a machine learning model to predict DVT before surgery in elderly hip fracture patients, aiming to improve preoperative assessments and streamline clinical care pathways.

Materials and methods

This study employed a retrospective design and included elderly patients who were hospitalized for hip fractures at a university-affiliated hospital between July 2022 and May 2025. A total of 782 patients met the inclusion criteria. The dataset wa

SUBMITTER: Wei X 

PROVIDER: S-EPMC12916597 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature