Optimal antiplatelet and antithrombotic regimen post‐transcatheter aortic valve replacement
Bibliographic record
Abstract
BACKGROUND: There are limited data regarding optimal antiplatelet/antithrombotic therapy following transcatheter aortic valve replacement (TAVR). METHODS: In this single-centre retrospective study including TAVR patients from 2012 to 2020, ischemic and bleeding outcomes were compared between antiplatelet (dual antiplatelet [DAPT] vs. single antiplatelet [SAPT]) and oral anticoagulation (OAC) groups using incidence rate, Kaplan-Meier and Cox proportional hazards analysis. RESULTS: Total 492 patients (mean age 79.7 ± 7.7 years, 53.7% males, 83.5% Caucasian) were included. There was higher incidence of 1-year death or ischemia with DAPT vs. SAPT (23.6 vs. 14.8 per 100 patient-years [PY], incidence rate ratio [IRR] 1.60, 95% confidence interval [CI] 0.97-2.68, p = .05), especially in those without coronary artery disease (23.9 vs. 10.7 per 100 PY, IRR 2.24, 95% CI 1.10-4.47, p = .017). There was significantly higher major bleeding in those on OAC vs. no OAC (15 vs. 8 per 100 PY, IRR 1.87, 95% CI 1.10-3.11, p = .016), especially late (>1-year) bleeding (10.2 vs. 3.6 per 100 PY, IRR 2.81, 95% CI 1.33-5.92, p = .004). In multivariate analysis, DAPT was an independent predictor of death or ischemia (adjusted hazard ratio [aHR] 1.41, 95% CI 1.01-1.96, p = .041). OAC was an independent predictor of major bleeding (aHR 2.32, 95% CI 1.31-4.13, p = .004). CONCLUSIONS: There is signal to harm with routine use of DAPT post-TAVR. There is higher incidence of late bleeding post-TAVR with OAC, suggesting potential role for alternate antithrombotic strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".