Machine learning models and restricted cubic spline were employed to analyze and predict postoperative ischemic stroke in type A aortic dissection patients.

ABSTRACT:

Background

Ischemic stroke remains a devastating postoperative complication in Type A aortic dissection (TAAD) patients, contributing significantly to elevate mortality rates. Identifying reliable predictors for ischemic stroke risk is crucial for implementing timely clinical interventions. This study endeavored to develop and validate a machine learning-based predictive model for ischemic stroke risk stratification in TAAD patients undergoing surgical treatment.

Methods

This retrospective cohort study analyzed 430 TAAD patients who underwent total aortic arch replacement with frozen elephant trunk implantation at Beijing Anzhen Hospital (2015-2021). The cohort was randomly partitioned into training (70%, n = 301) and validation (30%, n = 129) sets. We selected the top 8 out

SUBMITTER: Ma W 

PROVIDER: S-EPMC12801972 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature