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

作者：Fuxu Wang, Yu Guo, Yuru Tang, Shuangmei Zhao, Kaige Xuan, Zhi Mao, R. Lu, Rongyao Hou, Xiaoyan Zhu · 发表于：Cardiovascular Diabetology · 年份：2025 · DOI：10.1186/s12933-025-02762-0 · 被引用次数：35 · 研究领域：Hyperglycemia and glycemic control in critically ill and hospitalized patients、Sepsis Diagnosis and Treatment、Diabetes Management and Research

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 evaluation for ASCVD mortality remains unclear. This study examines associations of SHR, GV, and their synergistic effects with mortality in patients with ASCVD across different glucose metabolic states, incorporating machine learning (ML) to identify critical risk factors influencing mortality. METHODS: Patients with ASCVD were screened in the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and stratified into normal glucose regulation (NGR), pre-diabetes mellitus (Pre-DM), and diabetes mellitus (DM) groups based on glucose metabolic status. The primary endpoint was 28-day mortality, with 90-day mortality as the secondary outcome. SHR and GV levels were categorized into tertiles. Associations with mortality were analyzed using Kaplan-Meier(KM) curves, Cox proportional hazards models, restricted cubic splines (RCS), receiver operating characteristic (ROC) curves, landmark analyses, and subgroup analyses. Five ML algorithms were employed for mortality risk prediction, with SHapley Additive exPlanations (SHAP) applied to identify critical predictors. RESULTS: A total of 2807 patients were included, with a median age of 71 years, and 58.78% were male. Overall, 483 (23.14%) and 608 ...