Impact of estimated glucose disposal rate and high-sensitivity C-reactive protein on the risk of new-onset stroke: a nationwide prospective cohort study

Vollständiger Abstract

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Aim: Estimated glucose disposal rate (eGDR), a surrogate marker of insulin resistance, and high-sensitivity C-reactive protein (hsCRP), an inflammatory marker, may be jointly associated with stroke. We investigated the association of combined eGDR and hsCRP exposure with incident stroke and its predictive value among Chinese middle-aged and older adults. Methods: This prospective cohort study used five waves of the China Health and Retirement Longitudinal Study (2011-2020). Participants were stratified into four groups by median eGDR (9.92 mg/kg/min) and hsCRP (1.03 mg/L), with incident stroke as the outcome. Associations were assessed using Kaplan-Meier analysis and multivariable Cox regression. Restricted cubic splines, statistical mediation analysis, and receiver operating characteristic-based evaluations were used to examine dose-response relationships, mediation, and predictive performance, respectively. Results: A total of 815 incident stroke cases (9.11%) were documented during follow-up. The high eGDR plus low hsCRP group showed a 51% lower stroke risk (hazard ratio [HR] = 0.49, 95% confidence interval [CI]: 0.39-0.62) than the low eGDR plus high hsCRP group. The crude stroke event proportions showed a graded trend across the four groups (14.44%, 9.90%, 7.00%, and 4.75%; Log-rank P < 0.001). eGDR had a linear negative correlation with stroke risk, while hsCRP showed a nonlinear positive correlation. In statistical mediation analyses, hsCRP accounted for 6.40% of the association between eGDR and stroke, and eGDR accounted for 4.41% of the association between hsCRP and stroke (both P < 0.001). Conclusion: Joint exposure to eGDR and hsCRP is markedly linked to incident stroke susceptibility in middle-aged and older Chinese adults. Joint evaluation of these routinely measured markers was associated with statistically significant but modest improvements in risk stratification, suggesting a potential, low-cost approach to identifying high-risk individuals that warrants further validation.