Combined assessment of stress hyperglycemia ratio and glycemic variability to predict all-cause mortality in critically ill patients with atherosclerotic cardiovascular diseases across different glucose metabolic states: an observational cohort study with machine learning

Combined assessment of stress hyperglycemia ratio and glycemic variability to predict all-cause mortality in critically ill patients with atherosclerotic cardiovascular diseases across different glucose metabolic states: an observational cohort study with machine learning

Abstract Background Stress hyperglycemia ratio (SHR) and glycemic variability (GV) reflect acute glucose elevation and fluctuations, which correlate with adverse outcomes in patients with atherosclerotic cardiovascular disease (ASCVD). However, the prognostic significance of combined SHR-GV evaluati...

Full description

Saved in:
Bibliographic Details
Main Authors: Fuxu Wang, Yu Guo, Yuru Tang, Shuangmei Zhao, Kaige Xuan, Zhi Mao, Ruogu Lu, Rongyao Hou, Xiaoyan Zhu
Format: Article
Language:English
Published: BMC 2025-05-01
Series:Cardiovascular Diabetology
Subjects:
Atherosclerotic cardiovascular disease
Stress hyperglycemia ratio
Glycemic variability
MIMIC-IV database
Machine learning
Online Access:https://doi.org/10.1186/s12933-025-02762-0
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s12933-025-02762-0

Similar Items