A novel glyco-inflammatory healing index for risk prediction after isolated coronary artery bypass grafting: a multicenter retrospective cohort study

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The Glyco-Inflammatory Healing Index (GIHI), calculated as HbA1c × C-reactive protein / albumin, integrates measures of glycemic control, systemic inflammation, and nutritional status. Its association with postoperative outcomes after isolated coronary artery bypass grafting (CABG) has not been fully established, particularly according to diabetes status. We conducted a retrospective, international, multicenter cohort study of 6,262 adults who underwent isolated CABG between 2010 and 2025. Patients were stratified by diabetes status. GIHI was analyzed as a standardized continuous variable and descriptively categorized as high or low based on subgroup medians. The primary outcome was 30-day major adverse cardiovascular events (MACE), defined as all-cause mortality, myocardial infarction, stroke, or repeat revascularization. The secondary outcome was long-term all-cause mortality. Associations were evaluated using Cox regression, Kaplan-Meier analysis, restricted cubic splines, subgroup analyses, and receiver operating characteristic curves. Among 6,262 patients, 2,783 (44.5%) had diabetes. In diabetic patients, higher GIHI was associated with 30-day MACE (adjusted hazard ratio [HR] 1.45, 95% confidence interval [CI] 1.28–1.65), 30-day myocardial infarction (HR 1.27, 95% CI 1.00-1.60), 30-day mortality (HR 2.56, 95% CI 2.06–3.18), and long-term mortality (HR 2.57, 95% CI 2.33–2.83). In non-diabetic patients, GIHI was not associated with 30-day MACE but remained associated with 30-day and long-term mortality. Adding GIHI modestly improved discrimination for 30-day MACE in diabetic patients (AUC 0.65 to 0.69; p < 0.001). Higher GIHI was associated with adverse postoperative outcomes after isolated CABG, particularly in patients with diabetes. These findings suggest GIHI may provide incremental prognostic information, but prospective validation is needed before its routine clinical application.

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