A web-based novel prediction model for predicting depression in elderly patients with coronary heart disease: A multicenter retrospective, propensity-score matched study.

ABSTRACT:

Background

Depression is associated with an increased risk of death in patients with coronary heart disease (CHD). This study aimed to explore the factors influencing depression in elderly patients with CHD and to construct a prediction model for early identification of depression in this patient population.

Materials and methods

We used propensity-score matching to identify 1,065 CHD patients aged ≥65 years from four hospitals in Chongqing between January 2015 and December 2021. The patients were divided into a training set (n = 880) and an external validation set (n = 185). Univariate logistic regression, multivariate logistic regression, and least absolute shrinkage and selection operator regression were used to determine the factors influencing depression.

SUBMITTER: Tan J 

PROVIDER: S-EPMC9624295 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature