72319 | Sex-Related Differences in the Management and Outcomes of Patients Across the Spectrum of Aortic Stenosis
Bibliographic record
Abstract
Background There are conflicting data on sex differences in patients with aortic stenosis (AS). We aimed to investigate sex differences in management and outcomes across the spectrum of outpatients with AS. Methods Between 2016 and 2017, consecutive all‐comer outpatients with mild (peak aortic velocity=2.5–2.9 m/s), moderate (3–3.9 m/s), or severe (≥4 m/s) native AS were included by 117 cardiologists and followed up for 5 years for aortic valve replacement (AVR) and cause of death. Outcomes were compared by sex using inverse probability of treatment weighting adjustment. Results Among the 2704 patients, 1257 (46.5%) were women. Women were more symptomatic (New York Heart Association class ≥2, 67.7% versus 54.6%; P <0.001) and had a higher proportion of severe AS (17.5% versus 14.3%, P =0.02) at inclusion. During follow‐up (median, 5.0 [interquartile range, 3.4–5.5]) years, 993 AVRs (488 surgical and 505 transcatheter) and 1098 deaths occurred. After inverse probability of treatment weight adjustment, women had better survival (adjusted hazard ratio [HR], 0.81 [95% CI, 0.71–0.93]; P =0.003) but similar cardiovascular death ( P =0.99) compared with men. Interestingly, the higher survival in women was observed only in mild AS (adjusted HR, 0.71 [95% CI, 0.56–0.90]; P =0.005). The inverse probability of treatment weight–adjusted cumulative incidence of AVR by AS severity revealed no significant differences between women and men among patients across the AS spectrum. Cumulative incidence of surgical AVR was lower in women than in men ( P =0.02). Conclusions Women had a similar referral rate for AVR (versus men), with a lower proportion undergoing SAVR, allowing similar outcomes between women and men with moderate and severe AS. The lower mortality rate in women was restricted to mild AS presentation.
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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 | 0.005 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".