ArticleScientific reports2026
Changes in estimated glucose disposal rate and future stroke risk in individuals with cardiovascular-kidney-metabolic syndrome stages 0-3.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Previous studies have reported an association between estimated glucose disposal rate (eGDR) and stroke in individuals with cardiovascular-kidney-metabolic (CKM) syndrome stages 0–3. However, the association of changes in eGDR with the risk of incident stroke in this population remains unclear. Using data from the China Health and Retirement Longitudinal Study (CHARLS), this study included 3849 participants with CKM syndrome stages 0–3, among whom 285 (7.4%) developed stroke during follow-up from 2015 to 2020. Logistic regression was employed to evaluate the impact of cumulative eGDR (cumeGDR) and clusters of eGDR changes on stroke risk. After adjusting for potential confounders, the risk of incident stroke was significantly higher in participants with persistently moderately low eGDR (Class 2: OR 1.51, 95% CI 1.02–2.26), persistently low eGDR (Class 3: OR 2.11, 95% CI 1.36–3.26), and markedly declining eGDR (Class 4: OR 1.78, 95% CI 1.20–2.66), compared with those with persistently high eGDR (Class 1). Lower cumeGDR levels were independently associated with a higher risk of stroke events. Restricted cubic spline analysis indicated a negative linear relationship between cumeGDR and stroke risk. Receiver operating characteristic (ROC) curve analysis demonstrated that cumeGDR had greater predictive value for stroke than eGDR, and incremental predictive value analysis revealed that incorporating cumeGDR or clusters of eGDR changes into the baseline model provided incremental value for stroke risk prediction. These findings suggest that among individuals with CKM syndrome stages 0–3, persistently low eGDR or markedly declining eGDR was associated with a higher risk of stroke, underscoring the clinical value of dynamic eGDR monitoring for the early identification of individuals at high risk for stroke.
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