Stress hyperglycemia ratio and machine learning model for prediction of all-cause mortality in patients undergoing cardiac surgery.

ABSTRACT:

Background

The stress hyperglycemia ratio (SHR) was developed to reduce the effects of long-term chronic glycemic factors on stress hyperglycemia levels, which was associated with adverse clinical outcomes. This study aims to evaluate the relationship between the postoperative SHR index and all-cause mortality in patients undergoing cardiac surgery.

Methods

Data for this study were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Patients were categorized into four groups based on postoperative SHR index quartiles. The primary outcome was 30-day all-cause mortality, while the secondary outcomes included in-hospital, 90-day and 360-day all-cause mortality. The SHR index was analyzed using quartiles, and Kaplan-Meier curves were generated

SUBMITTER: Pei Y 

PROVIDER: S-EPMC11829518 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature