The incremental value of angiographic features for predicting recurrent cardiovascular events: Insights from the Duke Databank for Cardiovascular Disease.

ABSTRACT:

Background and aims

Identifying patient subgroups with cardiovascular disease (CVD) at highest risk for recurrent events remains challenging. Angiographic features may provide incremental value in risk prediction beyond clinical characteristics.

Methods

We included all cardiac catheterization patients from the Duke Databank for Cardiovascular Disease with significant coronary artery disease (CAD; 07/01/2007-12/31/2012) and an outpatient follow-up visit with a primary care physician or cardiologist in the same health system within 3 months post-catheterization. Follow-up occurred for 3 years for the primary major adverse cardiovascular event endpoint (time to all-cause death, myocardial infarction [MI], or stroke). A multivariable model to predict recurrent events was develop

SUBMITTER: Nanna MG 

PROVIDER: S-EPMC8221430 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature