Visceral Adipose Tissue, a Potential Risk Factor for Carotid Atherosclerosis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The association between abdominal obesity and atherosclerosis is believed to be due to excess visceral adipose tissue (VAT), which is associated with traditional risk factors. We hypothesized that VAT is an independent risk factor for atherosclerosis. METHODS: Healthy men and women (N=794) matched for ethnicity (aboriginal, Chinese, European, and South Asian) and body mass index range (<25, 25 to 29.9, or > or =30 kg/m(2)) were assessed for VAT (by computed tomography scan), carotid atherosclerosis (by ultrasound), total body fat, cardiovascular risk factors, lifestyle, and demographics. RESULTS: VAT was associated with carotid intima-media thickness (IMT), plaque area, and total area (IMT area and plaque area combined) after adjusting for demographics, family history, smoking, and percent body fat in men and women. In men, VAT was associated with IMT and total area after adjusting for insulin, glucose, homocysteine, blood pressure, and lipids. This association remained significant with IMT after further adjustment for either waist circumference or the waist-to-hip ratio. In women, VAT was no longer associated with IMT or total area after adjusting for risk factors. CONCLUSIONS: VAT is the primary region of adiposity associated with atherosclerosis and likely represents an additional risk factor for carotid atherosclerosis in men. Most but not all of this risk can be reflected clinically by either the waist circumference or waist-hip ratio measures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".