Sex Differences in Aortic Valve Calcification Measured by Multidetector Computed Tomography in Aortic Stenosis
Bibliographic record
Abstract
BACKGROUND: Aortic valve calcification (AVC) is the intrinsic mechanism of valvular obstruction leading to aortic stenosis (AS) and is measurable by multidetector computed tomography. The link between sex and AS is controversial and that with AVC is unknown. METHODS AND RESULTS: We prospectively performed multidetector computed tomography in 665 patients with AS (aortic valve area, 1.05±0.35 cm(2); mean gradient, 39±19 mm Hg) to measure AVC and to assess the impact of sex on the AVC-AS severity link in men and women. AS severity was comparable between women and men (peak aortic jet velocity: 4.05±0.99 versus 3.93±0.91 m/s, P=0.11; aortic valve area index: 0.55±0.20 versus 0.56±0.18 cm(2)/m(2); P=0.46). Conversely, AVC load was lower in women versus men (1703±1321 versus 2694±1628 arbitrary units; P<0.0001) even after adjustment for their smaller body surface area or aortic annular area (both P<0.0001). Thus, odds of high-AVC load were much greater in men than in women (odds ratio, 5.07; P<0.0001). Although AVC showed good associations with hemodynamic AS severity in men and women (all r>0.67; P<0.0001), for any level of AS severity measured by peak aortic jet velocity or aortic valve area index, AVC load, absolute or indexed, was higher in men versus women (all P≤0.01). CONCLUSIONS: In this large AS population, women incurred similar AS severity than men for lower AVC loads, even after indexing for their smaller body size. Hence, the relationship between valvular calcification process and AS severity differs in women and men, warranting further pathophysiological inquiry. For AS severity diagnostic purposes, interpretation of AVC load should be different in men and in women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".