Risk factors and a Bayesian network model to predict ischemic stroke in patients with dilated cardiomyopathy

ABSTRACT:

Objective

This study aimed to identify risk factors and create a predictive model for ischemic stroke (IS) in patients with dilated cardiomyopathy (DCM) using the Bayesian network (BN) approach.

Materials and methods

We collected clinical data of 634 patients with DCM treated at three referral management centers in Beijing between 2016 and 2021, including 127 with and 507 without IS. The patients were randomly divided into training (441 cases) and test (193 cases) sets at a ratio of 7:3. A BN model was established using the Tabu search algorithm with the training set data and verified with the test set data. The BN and logistic regression models were compared using the area under the receiver operating characteristic curve (AUC).

Results

Multivariate logistic reg

SUBMITTER: Fan Z 

PROVIDER: S-EPMC9683474 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature