Sex-Specific Outcomes in Patients With Aortic Stenosis and Reduced Ejection Fraction
Bibliographic record
Abstract
BACKGROUND: Women with aortic stenosis (AS) tend to be less referred for aortic valve replacement (AVR) and suffer from higher mortality risk compared to men. It is unknown if this discrepancy between sexes is also observed in the context of reduced left ventricular ejection fraction (LVEF). The objective of this study was to compare the risk of all-cause mortality between women and men with AS and reduced LVEF. METHODS: We conducted a retrospective study of all patients presenting ≥moderate AS and LVEF<50% on echocardiography at the Quebec Heart and Lung Institute (2005-2018). Using governmental registry data, we compared the odds of AVR (surgical and transcatheter) and the risk of all-cause mortality between sexes. Models were adjusted for relevant comorbidities, LVEF, AS severity and AVR as a time-dependent covariable. RESULTS: Our cohort included 827 patients (38% women), aged 75 ± 11 years and with a median LVEF of 37% (quartile interval 30%-44%). After adjustment, women were less likely to undergo AVR (adjusted OR=0.58, p=0.007) and presented a higher mortality risk than men when treated conservatively (sub-distribution adjusted HR=1.39, p=0.02). There was no interaction between sex and AVR with regards to survival (p=0.13). CONCLUSIONS: Among patients with significant AS and reduced LVEF, women were less likely to undergo AVR and suffered from higher mortality risk when treated conservatively, when compared to men with similar AS severity. Both sexes derived similar survival benefit from AVR. Studies are needed to better understand the potential gaps and biases explaining these findings.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".