Gender differences in the presentation and management of patients with severe aortic stenosis at specialist versus primary/secondary care centres: A sub-analysis of the IMPULSE enhanced registry
Bibliographic record
Abstract
BACKGROUND: Management and treatment of severe aortic stenosis (AS) may differ considerably in European countries. To investigate these differences in France, Germany, and the UK, the IMPULSE enhanced registry was established. Previous data revealed differences in how patients were managed in specialist (hub) versus primary/secondary care (satellite) centres. METHODS: The IMPULSE enhanced registry sub-analysis aimed to determine if there were gender-specific differences for patients with severe AS at centres with and without access to intervention. RESULTS: Among the 790 patients, 594 and 196 were recruited at hub and satellite centres, respectively; 44 % of patients were female. In both settings, women were older than men (hubs: 78.7 vs. 76.2, p = 0.007; satellites: 79.8 vs. 75.1, p = 0.002). Symptoms at the presentation were comparable. Males had more often undergone previous cardiac surgery. Females had a smaller left ventricular (LV) outflow tract, smaller LV cavities, and, more often, a preserved ejection fraction (>50 %). There was no gender-based difference in time to intervention. At one year, the cumulative incidence of aortic valve replacement in females was higher than in males in hubs (p = 0.012) but not in satellites (p = 0.600); surgical AVR was more common in males in hubs only (p = 0.008), while transcatheter aortic valve implantation was more common in females in both settings (hubs: p < 0.001; satellites: p = 0.022). One-year survival was comparable in both genders, regardless of setting. CONCLUSIONS: A better understanding of gender-specific differences in patients with severe AS, according to the diagnostic setting, could improve patient stratification and earlier diagnosis.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".