Insulin resistance assessed by estimated glucose disposal rate predicts cardiovascular disease in early-stage cardiovascular-kidney-metabolic syndrome: a prospective cohort study

Background Insulin resistance (IR) has been recognized as a critical factor in the progression of cardiovascular disease (CVD), yet its association with cardiovascular-kidney-metabolic (CKM) syndrome remains incompletely understood. This study aimed to evaluate the impact of insulin resistance, as measured by the estimated glucose disposal rate (eGDR), on the risk of future CVD events in individuals with CKM stages 0-3. Methods This prospective cohort study included 329,132 participants from the UK Biobank with CKM stages 0-3. Insulin resistance was quantified using eGDR, a non-insulin-dependent metric, with lower values indicating greater insulin resistance. Participants were stratified into quartiles based on eGDR distribution. The primary outcome was incident CVD, including coronary heart disease (CHD), stroke, atrial fibrillation (AF), heart failure (HF), and peripheral artery disease (PAD). Survival analysis and restricted cubic spline (RCS) curves were employed to assess outcomes. Results In the CKM 0-3 cohort, eGDR demonstrated the highest predictive value for future CVD events among non-insulin-dependent insulin resistance metrics, with an area under the curve (AUC) of 0.719 (95% confidence interval [CI]: 0.716–0.721, p<0.001). Incorporating eGDR significantly improved the predictive performance of the PREVENT Cardiovascular Disease Risk Equations (area under the curve [AUC]: PREVENT Equations + eGDR 0.723 vs. PREVENT Equations 0.688, p<0.001). Over a median follow-up of 10.18 years, 44,854 incident CVD cases were identified. The CVD incidence rate was highest in the lowest eGDR quartile (41.86 vs. 19.59 vs. 9.54 vs. 7.84 per 1000 person-years; p<0.001). Multivariable-adjusted RCS analysis revealed a negative linear association between eGDR and CVD incidence (p for overall <0.001; p for nonlinear <0.001). In fully adjusted Cox models, each 1-unit increase in eGDR was associated with a 9.5% reduction in CVD risk (hazard ratio [HR]: 0.905; 95% CI: 0.892–0.919). Compared with the lowest quartile (Q1), participants in higher eGDR quartiles (Q2–Q4) exhibited progressively lower CVD risk (Q2 HR: 0.976, 95% CI: 0.949–1.007; Q3 HR: 0.847, 95% CI: 0.800–0.896; Q4 HR: 0.766, 95% CI: 0.716–0.820; p for trend <0.001). Consistent patterns were observed across individual CVD components. Kaplan-Meier analysis further confirmed a graded increase in CVD risk with declining eGDR levels (log-rank p<0.001). Conclusion This study establishes a strong association between insulin resistance severity and long-term CVD risk in individuals with CKM syndrome stages 0-3. The eGDR, a reliable surrogate marker of IR, independently predicts future CVD events and provides incremental predictive value beyond the PREVENT equations. These findings underscore the clinical utility of eGDR for risk stratification in CKM populations.Figure 1 Figure 2