Risk factors and prediction model for acute ischemic stroke after off-pump coronary artery bypass grafting based on Bayesian network.

ABSTRACT:

Background

This study aimed to identify the risk factors of acute ischemic stroke (AIS) occurring during hospitalization in patients following off-pump coronary artery bypass grafting (OPCABG) and utilize Bayesian network (BN) methods to establish predictive models for this disease.

Methods

Data were collected from the electronic health records of adult patients who underwent OPCABG at Beijing Anzhen Hospital from January 2018 to December 2022. Patients were allocated to the training and test sets in an 8:2 ratio according to the principle of randomness. Subsequently, a BN model was established using the training dataset and validated against the testing dataset. The BN model was developed using a tabu search algorithm. Finally, receiver operating characteristic (ROC) and ca

SUBMITTER: Zou W 

PROVIDER: S-EPMC11577910 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature