Diabetes and male sex are key risk factor correlates of the extent of coronary artery calcification: A Euro-CCAD study
Bibliographic record
Abstract
BACKGROUND AND AIMS: Although much has been written about the conventional cardiovascular risk factor correlates of the extent of coronary artery calcification (CAC), few studies have been carried out on symptomatic patients. This paper assesses the potential ability of risk factors to associate with an increasing CAC score. METHODS: From the European Calcific Coronary Artery Disease (Euro-CCAD) cohort, we retrospectively investigated 6309 symptomatic patients, 62% male, from Denmark, France, Germany, Italy, Spain and the USA. All had conventional cardiovascular risk factor assessment and CT scanning for CAC scoring. RESULTS: Among all patients, male sex (OR = 4.85, p<0.001) and diabetes (OR = 2.36, p<0.001) were the most important risk factors of CAC extent, with age, hypertension, dyslipidemia and smoking also showing a relationship. Among patients with CAC, age, diabetes, hypertension and dyslipidemia were associated with an increasing CAC score in males and females, with diabetes being the strongest dichotomous risk factor (p<0.001 for both). These results were echoed in quantile regression, where diabetes was consistently the most important correlate with CAC extent in every quantile in both males and females. To a lesser extent, hypertension and dyslipidemia were also associated in the high CAC quantiles and the low CAC quantiles respectively. CONCLUSION: In addition to age and male sex in the total population, diabetes is the most important correlate of CAC extent in both sexes.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".