Aspirin Alone Versus Dual Antiplatelet Therapy After Transcatheter Aortic Valve Implantation: A Systematic Review and Patient‐Level Meta‐Analysis
Bibliographic record
Abstract
Background In patients undergoing transcatheter aortic valve implantation without an indication for oral anticoagulation, it is unclear whether single or dual antiplatelet therapy (DAPT) is necessary to minimize both the bleeding and thromboembolic risk. In this patient‐level meta‐analysis, we further investigate the effect of aspirin alone compared with DAPT for preventing both thromboembolic and bleeding events after transcatheter aortic valve implantation. Methods and Results We conducted a systematic review of all available randomized controlled trials comparing aspirin with DAPT. In total, 1086 patients were included across 4 eligible trials. The primary outcomes were the composite of all‐cause mortality, major or life‐threatening bleeding, stroke or myocardial infarction (first composite outcome), and the same composite excluding bleeding (second composite outcome), both tested at 30 days and 3 months. The first composite outcome occurred significantly less in the aspirin‐alone group at 30 days (10.3% versus 14.7%, odds ratio [OR], 0.67; 95% CI, 0.46–0.97, P =0.034) and 3 months (11.0% versus 16.5%, hazard ratio [HR], 0.66; 95% CI, 0.47–0.94, P =0.02), compared with the DAPT group. The second composite outcome occurred in 5.5% and 6.6% at 30 days (OR, 0.83; 95% CI, 0.50–1.38, P =0.47) and in 6.9% and 8.5% at 3 months in the aspirin‐alone group compared with the DAPT group (HR, 0.82; 95% CI, 0.52–1.29, P =0.39), respectively. Conclusions In patients without an indication for oral anticoagulation undergoing transcatheter aortic valve implantation, aspirin alone significantly reduced the composite of thromboembolic and bleeding events, and does not increase the composite of thromboembolic events after transcatheter aortic valve implantation, compared with DAPT.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.029 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".