Sex-specific correlates of valvular and arterial calcification burden in patients with moderate aortic stenosis
Bibliographic record
Abstract
INTRODUCTION: There are significant sex differences in the prevalence and severity of cardiac calcifying processes. Women harbour more severe mitral annular calcification (MAC), while men exhibit worse aortic valve (AVC) and coronary artery (CAC) calcification. To better understand these differences, we investigated the correlates of cardiac calcification according to sex. METHODS: , a peak aortic jet velocity >2.0 m/s, or a mean transvalvular gradient >15 mm Hg. Doppler-echocardiography and non-contrast multidetector CT were performed concomitantly to assess AS and cardiac calcifications. RESULTS: , peak aortic jet velocity of 2.78 (2.37-3.68) m/s, and mean gradient of 17.9 (12.8-31.3) mm Hg for the whole cohort. Compared with men, women harboured lower AVC (480 (222-1191) vs 1003 (484-2329) Agatston unit, AU; p<0.0001) and CAC (366 (50-914) vs 618 (167-1357) AU; p=0.007), but more severe MAC (60 (1-887) vs 48 (0-351) AU; p=0.08) and ascending aorta calcification (227 (43-863) vs 142 (7-493) AU; p=0.03). After comprehensive adjustment, sex remained an independent predictor of each cardiac calcification subtype (all p<0.02) except for the ascending aorta (p=0.32). In multivariable analysis, certain variables, like age or bicuspid aortic valve, were associated with the calcification scores in both sexes. Sex-specific predictors of calcification burden were absence of angiotensin receptor blockers (β=-0.26; p=0.007) and renal impairment (β=0.26; p=0.003) for AVC, and bisphosphonates (β=0.20; p=0.05) for CAC in women; coronary artery disease (β=0.25; p=0.001) for AVC, and angiotensin receptor blockers (β=0.19; p=0.02) and calcium/vitamin D (β=0.15; p=0.02) for MAC in men. CONCLUSION: In AS, factors associated with cardiac valvular and arterial calcification differ between sexes, suggesting an important contributory role of sex in the pathophysiology of these calcifying processes.
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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 | 0.000 |
| 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".