Abstract 17973: Clinical Markers Associated With Subclinical Atherosclerosis in Otherwise Apparently Healthy Young Adults
Bibliographic record
Abstract
Introduction: Traditional risk factors are poor predictors of cardiovascular events in younger adults. Considering the long silent evolution of atherosclerosis beginning in younger adulthood before the appearance of clinical events at a more advanced age, a simple tool to predict early atherosclerosis in young adults would be desirable to guide primordial prevention. An altered cardiometabolic profile is associated with increased cardiovascular disease in older adults independent from traditional risk factors, but the value of this profile in an otherwise healthy young adult population is unknown. Hypothesis: Cardiometabolic risk markers would be associated with early atherosclerosis in young adults despite the absence of traditional risk factors. Methods: Healthy young adults (18-35 years) devoid of cardiovascular risk factors (diabetes, smoking, hypertension, dyslipidemia) and obesity were prospectively enrolled. Anthropometric measurements, ECG, lipid profile, fasting blood glucose, blood pressure and high-resolution carotid artery MRI were realized. Results: Although the 240 participants (25.8 years, SEM=0.29, 48% women) were at low risk for atherosclerosis, we identified atherosclerosis in 72.6% of men and 64.7% of women (p=0.19). Males had greater atherosclerosis burden vs. females (carotid wall volume [CWV]: 1817 mm3/48mm, SEM=29.7 vs. 1579 mm3/48mm, SEM=21.2; p<0.0001). By multivariate analysis, atherosclerosis burden was associated with fasting blood glucose (p=0.01), BMI (p=0.01), and waist circumference (p<0.001), the latter having the strongest correlation with atherosclerosis burden (r=0.41, p<0.0001). ROC analyses established cutoffs for waist circumference identifying greater atherosclerosis burden in apparently healthy young adults. Conclusion: A simple low-cost office-based tool, waist circumference measurement improves prediction of early atherosclerosis in otherwise apparently healthy young adults.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".