Metabolic Syndrome Components and Long-Term Incidence of Cardiovascular Disease in Eastern Mediterranean Region: A 13-Year Population-Based Cohort Study
Why this work is in the frame
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Bibliographic record
Abstract
Background: The risk of cardiovascular events in individuals with metabolic syndrome (MetS) is higher than in general populations. We aimed at assessing the association between cardiovascular disease (CVD) and MetS and at identifying triple components that are the most predictive of future CVD events. Methods: Data on 1387 CVD-free individuals recruited in an ongoing cohort in Isfahan, Iran (ICS) were analyzed. This included serum tests and health and lifestyle questionnaires measured at baseline in 2001, 2007, and 2013. The association between CVD and MetS, irrespective of composing components, was evaluated by using logistic regression. The hazard ratio (HR) of CVD events after MetS diagnosis was calculated for different combinations by using Cox PH regression. Results: The prevalence of MetS was 34.4% at baseline, 19.5% of which was with diabetes. The prevalence of hypertension (blood pressure [BP]) and hyperglycemia (fasting plasma glucose [FPG]) increased over time. Irrespective of composing components, the odds of developing CVD in MetS individuals was higher than in those who did not develop MetS with adjusted odds ratio = 1.76; 95% confidence intervals (CI) = 1.22–2.55. Among the five most prevalent triple combinations, there was a significant association between CVD incidence and high-density lipoprotein + BP + waist circumference combination only with HR = 1.66; 95% CI = 1.04–2.67. Conclusion: Some MetS components are more likely to result in CVD. Identifying the most predictive components could help in the timely initiation of proper interventions rather than waiting for all MetS components or symptoms of CVD.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it