Machine learning-based prediction models to assess 30-day outcomes following intervention for superficial venous incompetence of the lower limbs.

ABSTRACT:

Objective

Treatment of incompetent superficial veins can be associated with postoperative complications and pain, potentially impacting on patients' satisfaction. Early identification of patients at higher risk of complications could help tailor postoperative management. The aim of this study was to develop machine learning models to predict 30-day postoperative outcomes in patients undergoing intervention for superficial venous incompetence.

Methods

A database from a prospective vascular registry (Qualivein) was searched from January 2014 until February 2024 to identify patients who underwent superficial venous intervention in France. Data collected included clinical and procedural characteristics and outcomes (pain, physical ability, postoperative complications) during the

SUBMITTER: Creton O 

PROVIDER: S-EPMC12704062 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature