Insulin resistance assessed by estimated glucose disposal rate predicts cardiovascular disease in stages 0–3 of cardiovascular-kidney-metabolic syndrome: a UK biobank cohort study
Authors' conclusion
This study establishes a strong association between IR 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.
Study context
- Population
- UK Biobank participants with cardiovascular-kidney-metabolic (CKM) syndrome stages 0–348,433 incident cardiovascular disease (CVD) cases
- Participants
- 325,312 participants
- Exposure
- Estimated glucose disposal rate (eGDR) quartiles Q2–Q4 vs Q1
- Outcome
- Incident CVD (coronary heart disease, stroke, AF, HF, peripheral artery disease)
- Follow-up
- Median 13.57 years
Methodological detailsUK Biobank, eGDR quartiles
- UK Biobank
- eGDR quartiles
Main finding
As reported in the abstract
- Significant nonlinear association between eGDR and CVD incidence (RCS), greater risk reduction at higher eGDR
- p for overall < 0.001; p for nonlinear = 0.020
- Graded decrease in CVD risk with increasing eGDR (Kaplan-Meier)
- log-rank p < 0.001
Observational data: associations, not effects.
Further findings
Predictive performance (AUC) of PREVENT equations with vs without eGDR
- AUC PREVENT Equations + eGDR vs PREVENT Equations
- 0.743 vs. 0.719, p < 0.001
- eGDR had the highest predictive value for future CVD among non-insulin-dependent insulin resistance (IR) metrics
Parts of this Brief are withheld: the automatic checks could not confirm them against the abstract.
Original publication
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