Abstract 14894: The Impact of Coronary Artery Disease on Cardiovascular Events Differs Between Men and Women in the PARTNER Trials
Bibliographic record
Abstract
Introduction: Among individuals with severe aortic stenosis (AS), there is significant heterogeneity in the burden of coronary artery disease (CAD). Hypothesis: We hypothesize that a greater CAD burden will be associated with increased adverse events after AS treatment. Methods: Patients with severe AS in the PARTNER (Placement of Aortic Transcatheter Valves) 1, 2 and 3 trials and registries were categorized by CAD burden. Clinical characteristics, imaging, treatment, and outcomes were compared between those with obstructive CAD [defined invasively as coronary stenosis ≥50%, prior myocardial infarction (MI) or revascularization] and patients with no or non-obstructive CAD (all stenoses <50% and no prior MI or revascularization). The primary endpoint was cardiovascular (CV) death or heart failure (HF) hospitalization at 2 years. Results: Among 8058 patients with severe AS, 2200 (27.3%) had non-obstructive or no CAD and were more likely to be female (61.2%) with fewer CAD risk factors. Left ventricular (LV) mass index and LV dimensions were smaller and LV ejection fraction was higher among those with non-obstructive or no CAD. TAVR was performed in 72.0% of non-obstructive or no CAD patients and in 81.3% of patients with obstructive CAD (p<0.0001); the remaining patients received SAVR. After adjustment for clinical, imaging, and AS treatment differences, the rate of CV death or HF hospitalization was higher among those with obstructive CAD (HR 1.16, 95% CI: 1.03-1.30, p=0.01). However, there was a significant sex-related difference in the primary outcome particularly between males and females with non-obstructive or no CAD, p interaction =0.003 (Figure). Conclusions: Patients with a greater burden of CAD had worse clinical outcomes after treatment for severe AS. However, there was a significant interaction by sex. Further study is needed to understand the increased CV risk among females compared to males with non-obstructive or no CAD.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".