| Title: | 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 |
| Journal: | Cardiovascular Diabetology |
| Published: | 11 Sep 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40936079/ |
| DOI: | https://doi.org/10.1186/s12933-025-02860-z |
| URL: | https://cardiab.biomedcentral.com/counter/pdf/10.1186/s12933-025-02860-z |
Publication 19515
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Abstract
BackgroundInsulin 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 IR, as measured by the estimated glucose disposal rate (eGDR), on the risk of future CVD events in individuals with CKM stages 0-3.MethodsThis study included 325,312 participants from the UK Biobank with CKM stages 0-3. IR was quantified using eGDR, a non-insulin-dependent metric, with lower values indicating greater IR. Participants were stratified into quartiles based on eGDR distribution. The primary outcome was incident CVD, including coronary heart disease, stroke, atrial fibrillation, heart failure, and peripheral artery disease.ResultsIn the CKM 0-3 cohort, eGDR demonstrated the highest predictive value for future CVD events among non-insulin-dependent IR metrics. Incorporating eGDR significantly improved the predictive performance of the PREVENT Cardiovascular Disease Risk Equations (AUC: PREVENT Equations + eGDR 0.743 vs. PREVENT Equations 0.719, p < 0.001). Over a median follow-up of 13.57 years, 48,433 incident CVD cases were identified. The adjusted rates of CVD incidence (95% confidence interval [CI]) across eGDR quartiles (Q1-Q4) were 3.84 (3.62-4.07), 3.82 (3.66-3.98), 3.53 (3.41-3.65), and 3.37 (3.25-3.50) per 1000 person-years. RCS analysis revealed a significant nonlinear association between eGDR and CVD incidence (p for overall < 0.001; p for nonlinear = 0.020), with greater risk reduction at higher eGDR levels. A significant trend toward reduced CVD risk was observed across higher eGDR quartiles, with Q3 and Q4 demonstrating statistically significant reductions relative to Q1 (HR 0.920, 95% CI 0.871-0.971; and 0.883, 95% CI 0.827-0.942, respectively; p for trend < 0.001). Kaplan-Meier analysis further confirmed a graded decrease in CVD risk with increasing eGDR levels (log-rank p < 0.001).ConclusionThis 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.Graphical Abstract</p>
21 Keywords
- Adult
- Aged
- Biological Specimen Banks
- Biomarkers
- Blood Glucose
- Cardio-Renal Syndrome
- Cardiovascular Diseases
- Female
- Humans
- Incidence
- Insulin Resistance
- Male
- Metabolic Syndrome
- Middle Aged
- Predictive Value of Tests
- Prognosis
- Risk Assessment
- Risk Factors
- Time Factors
- UK Biobank
- United Kingdom
6 Authors
- Hao Zhang
- Sizhuang Huang
- Yanwen Fang
- Haihua Zhang
- Weixian Yang
- Mengyue Yu
1 Application
| Application ID | Title |
|---|---|
| 532333 | Multimodal Analysis for Onset, Development, and Identifying Therapeutic Targets in cardiovascular disease combined with chronic inflammatory diseases |
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