Uninterrupted anticoagulation with non‐vitamin K antagonist oral anticoagulants in atrial fibrillation catheter ablation: Lessons learned from randomized trials
Bibliographic record
Abstract
Catheter ablation has been established as a rhythm control strategy in selected patients with atrial fibrillation (AF) who have failed or wish to avoid anti-arrhythmic drugs. Uninterrupted oral anticoagulation with vitamin K antagonists (VKAs) peri-ablation is associated with a lower risk of thromboembolic and bleeding complications as compared to interrupted oral anticoagulation and bridging heparin. However, a substantial portion of patients with AF are treated with non-vitamin K antagonist oral anticoagulants (NOACs). Herein, we perform an in-depth review and comparison of three recent randomized trials of uninterrupted oral anticoagulation with NOACs vs VKAs in patients undergoing AF catheter ablation. Furthermore, we report pooled results of these randomized trials. The pooled incidence of major bleeding was significantly lower with NOACs as compared to VKAs (2% vs 4.9%, respectively; odds ratio [OR] 0.40; 95% confidence intervals [CI] 0.16-0.99). Similarly, cardiac tamponade was also reduced in the NOAC group (0.4% vs 1.5%; OR 0.27; 95% CI 0.07-0.97). Thromboembolic complications were not significantly different between groups. Overall, these findings support the 2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement's class I recommendation for uninterrupted NOAC use in patients undergoing AF catheter ablation.
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 | 0.102 | 0.202 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".