Glycemic variability and clinical outcomes in ICU patients with ischemic stroke: a multi-database retrospective cohort study

Glycemic variability (GV) is an emerging marker of metabolic stress in critically ill patients, but its prognostic value in ICU patients with ischemic stroke remains unclear. This retrospective cohort study used MIMIC-Ⅳ and eICU databases to assess associations between GV and outcomes in adult ischemic stroke patients. GV metrics—including mean blood glucose (MBG), standard deviation (SD), coefficient of variation (CV), and glucose range—were calculated from all ICU glucose readings. The primary outcome was in-hospital mortality; the secondary outcome was ICU length of stay (LOS). Multivariable regression and XGBoost machine learning were used, with external validation. A total of 418 patients were included (334 survivors, 84 non-survivors). In univariate analyses, non-survivors had significantly lower SD (P = 0.007), CV (P = 0.036), and glucose range (P = 0.038) than survivors, while MBG did not differ significantly (P = 0.132). However, no GV metric remained independently associated with mortality or ICU LOS after multivariable adjustment (P > 0.05). XGBoost models showed moderate predictive performance (AUC = 0.657), with GV metrics contributing moderate feature importance. Subgroup analyses indicated a possible protective association between higher CV and mortality in older or non-hypertensive patients. Findings were consistent across databases (P > 0.6). In ICU patients with ischemic stroke, GV was linked to outcomes in unadjusted analyses but was not an independent predictor after adjustment. GV may aid in risk stratification, though traditional clinical variables remain more predictive.