Stratifying the Risk of Cardiovascular Disease in Obstructive Sleep Apnea Using Machine Learning.

ABSTRACT:

Objectives/hypothesis

Obstructive sleep apnea (OSA) is associated with higher risk of morbidity and mortality related to cardiovascular disease (CVD). Due to overlapping clinical risk factors, identifying high-risk patients with OSA who are likely to develop CVD remains challenging. We aimed to identify baseline clinical factors associated with the future development of CVD in patients with OSA.

Study design

Retrospective analysis of prospectively collected data.

Methods

We performed a retrospective analysis of 967 adults aged 45 to 84 years and enrolled in the Multi-Ethnic Study of Atherosclerosis. Six machine learning models were created using baseline clinical factors initially identified by stepwise variable selection. The performance of these models for the predi

SUBMITTER: Gourishetti SC 

PROVIDER: S-EPMC8671206 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature