Multimodal Data-Driven Explainable Prognostic Model for Major Adverse Cardiovascular Events Prediction in Patients With Unstable Angina and Heart Failure With Preserved Ejection Fraction: Multicenter, Cross-Regional Cohort Study.

ABSTRACT:

Background

Heart failure with preserved ejection fraction (HFpEF) and unstable angina (UA) often coexist in clinical practice, constituting a high-risk cardiovascular phenotype with a markedly increased incidence of major adverse cardiovascular events (MACEs). The identification of high-risk patients within this population is crucial for reducing complications, improving outcomes, and guiding clinical decision-making.

Objective

This study aimed to develop and externally validate predictive models based on machine learning algorithms to estimate the risk of MACEs in patients with coexisting UA and HFpEF, and to construct an online risk calculator to support individualized prevention strategies.

Methods

This multicenter cohort study included 4459 patients with both HFpE

SUBMITTER: Wang Y 

PROVIDER: S-EPMC12705130 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature