Sex Differences in Associations of Arterial Compliance With Coronary Artery Plaque and Calcification Burden
Bibliographic record
Abstract
Background Coronary artery disease is a leading killer of women. Arterial stiffness predicts myocardial infarction, and postmenopausal women have lower arterial compliance ( AC ) than men. We hypothesized that lower AC would be associated with greater burden of coronary artery plaque and calcification, and that these associations would be stronger in women than men. Methods and Results We evaluated 3639 consecutive adults without coronary artery disease history who had coronary computed tomography between 2006 and 2014. Coronary artery calcification was calculated using the Agatston method. Plaque extent was assessed by the number of arterial segments with visible plaque divided by the number of visualized segments ×100 (percent plaque score). Indexed AC was calculated as stroke volume index/central pulse pressure. We used step‐wise multivariable linear regression to assess associations of log indexed AC with log (percent plaque score+1) and log (coronary artery calcification+1). Sex‐specific models were performed if the interaction sex× AC was significant. Mean age was 57±11 years, 53% were men, and 71% were hypertensive. Interaction term sex× AC was significant for both models ( P =0.008 for percent plaque score and 0.022 for coronary artery calcification). Lower indexed AC was associated with higher percent plaque score and coronary artery calcification in women (β± SE : −0.231±0.113, P =0.042 and −0.334±0.166, P =0.044, respectively), but not in men (β± SE : −0.062±0.104, P =0.551 and 0.114±0.173, P =0.510, respectively). Conclusions Lower AC is associated with greater burden of coronary artery plaque and calcification in women, but not in men. Our findings highlight low AC as a correlate of more‐advanced coronary artery disease and as a potential link to the worse cardiovascular outcomes in women.
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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 | 0.001 | 0.000 |
| 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".