Association between the stress hyperglycemia ratio and all-cause mortality in patients with hemorrhagic stroke: a...

Research on the associations between the stress hyperglycemia ratio (SHR) and adverse outcomes in patients with hemorrhagic stroke is limited. Therefore, we aimed to investigate the relationship between the SHR and all-cause mortality in patients with hemorrhagic stroke.

Clinical data of patients with hemorrhagic stroke were extracted from the Medical Information Mart for Intensive Care (MIMIC-IV) database. The patients were divided into four groups based on the SHR quartiles. Outcomes including 28-, 90-, and 365-day all-cause mortality were analyzed. Kaplan-Meier curves, Cox proportional hazard regression, and restricted cubic splines were used to investigate the relationships between the SHR and all-cause mortality. A machine learning prediction model integrating SHR was developed to assess its prognostic value for all-cause mortality.

The final analysis cohort consisted of 939 patients. Compared to the lowest SHR quartile, the highest quartile had significantly increased mortality risks at 28 days [hazard ratio (HR) = 4.53, 95% CI: 2.75-7.46; p < 0.001], 90 days (HR = 3.29, 2.19-4.95; p < 0.001), and 365 days (HR = 2.25, 1.60-3.17; p < 0.001). A significant upward trend in mortality risk was observed across ascending SHR quartiles (p-trend < 0.001 for all time points). Restricted cubic spline analysis demonstrated non-linear associations between SHR and all-cause mortality at 28 and 90 days (p-non-linear < 0.05), while the overall trend remained significantly positive. The machine learning models identified SHR as a key predictor, with area under the curves (AUC) of 0.771 (28-day), 0.778 (90-day), and 0.778 (365-day).

This study revealed threshold-dependent associations between the SHR and short- and long-term all-cause mortality in patients with hemorrhagic stroke. The SHR was a reliable predictor for adverse outcomes in patients with hemorrhagic stroke.