Abstract 4138306: Impact of Early Menopause and Hormonal Replacement Therapy on Aortic Stenosis Progressio
Bibliographic record
Abstract
Background: Early menopause is associated with an increased risk of cardiovascular disease and mortality in women. The present study aimed to examine the impact of early menopause and hormonal replacement therapy (HRT) on the progression of aortic stenosis (AS). Methods: Thirty-three postmenopausal women (mean age 65 ± 10 years) with mild or moderate AS prospectively recruited in the PROGRESSA study (NCT01679431) were included in this sub-analysis. All patients underwent multidetector computed tomography and Doppler-echocardiography at least twice during follow-up to assess both anatomic and hemodynamic AS severity, based on aortic valve calcification (AVC), mean pressure gradient (MG), and aortic valve area indexed to body surface area (AVA). Annualized changes in AVC, MG and AVAi were calculated between baseline and the last follow-up. Results: Over a median follow-up of 2 [1-4] years, early menopausal women had a faster progression rate of AVC, MG, and AVAi compared to other women: (100[58-130] vs. 23[2-71] AU/year, p=0.03); (2.37[0.82-3.61] vs. 0.31[0.01-1.78] mmHg/year, p=0.04); and (-0.12[-0.23-0.002] vs. -0.004[-0.07-0.08] cm 2 /m 2 /year, p=0.08) respectively. In multivariate analysis adjusted for age, AS severity at baseline, and comorbidities, early menopause remained significantly associated with faster AVC progression (p=0.003). Moreover, after comprehensive adjustment, women who received HRT (45%) had a slower progression rate of AVC (20[10-42] AU/year vs. 62[2-100], adjusted p=0.04). Conclusion: Early menopause is associated with faster progression of AS, both anatomically and hemodynamically. However, the use of HRT is associated with slower progression of AS. Integrating female-specific risk factors, particularly menopausal history and hormonal therapy status, into the clinical management of AS could enhance patient care.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".