Machine learning-based cardiovascular risk calculator for non-cardiac surgery.

ABSTRACT:

Background

Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least one cardiovascular risk factor. It is estimated that the 30-day mortality is between 0.5% and 2%.The main objective of this study is to develop a traditional machine learning (ML) model that provides a cardiovascular risk score for patients older than 50 years undergoing non-cardiac surgery, calculating the risk from the date of surgery until 30 days post surgery, with specific emphasis on interpretability and explainability of the model's decision-making process.

Methods

The NSQIP 2022 dataset was used to build the model. It consisted of a total of 4 97 011 patients after data cleaning. The primary clinical endpoint was death, myocardial infarction, car

SUBMITTER: Al Khatib N 

PROVIDER: S-EPMC12781980 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature