Objectives Background Methods Results Conclusions
Bibliographic record
Abstract
The aim of this study was to examine sex differences in outcome after transcatheter aortic valve replacement (TAVR) with real-world data from 2 large centers in Canada. Transcatheter aortic valve replacement is an effective alternative to surgical valve replacement in symptomatic patients with severe aortic stenosis, but the impact of sex on outcomes remains unclear. The Placement of Aortic Transcatheter Valves (PARTNER) 1A trial demonstrated greater benefit of TAVR over surgery in women, but whether this was due to the poorer surgical outcome of women or better TAVR outcome, compared with men, is unknown. Consecutive patients (n � 641) undergoing TAVR in Vancouver and Quebec City, Canada, were evaluated. Differences in all-cause mortality were examined with Kaplan-Meier estimates, adjusted logistic regression, and proportional hazards models. Women comprised 51.3 % of the cohort. Balloon-expandable valves were used in 97 % of cases, with transapical approach in 51.7 % women and 38.1 % men. Women had more major vascular complications (12.4 % vs. 5.4%, p � 0.003) and borderline significantly more major/life-threatening bleeds (21.6 % vs. 15.8%, p � 0.08). At baseline, women had higher aortic gradients and worse renal function but better ejection fractions. Men had more comorbidities: prior myocardial infarction, prior revascularization, and chronic obstructive pulmonary disease. The adjusted odds ratio for 30-day all-cause mortality favored women, 0.39 (95 % confidence interval: 0.19 to 0.80; p � 0.01), and this
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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.127 | 0.046 |
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".