A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease.

ABSTRACT:

Background

Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated.

Objectives

To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD.

Methods

From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis < 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cy

SUBMITTER: Raparelli V 

PROVIDER: S-EPMC10449670 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature