Antithrombotic therapy after bioprosthetic aortic valve replacement: ACTION Registry survey results☆
Bibliographic record
Abstract
AIMS: A variety of antithrombotic regimens have been described for the early postoperative period after bioprosthetic aortic valve replacement (AVR). This study reviews antithrombotic practice for patients undergoing bioprosthetic AVR with or without coronary artery bypass graft (CABG) amongst the centers participating in the ACTION (Anticoagulation Treatment Influence on Postoperative Patients) Registry. METHODS AND RESULTS: An antithrombotic therapy questionnaire was answered by the 49 centers participating in the ACTION Registry located in Europe, Middle East, Canada and Asia. The 43% of centers prescribe vitamin K antagonist (VKA), 20% prescribe VKA and acetyl salicylic acid (ASA), 33% prescribe only ASA and 4% do not prescribe any therapy after bioprosthetic AVR. For patients undergoing bioprosthetic AVR and CABG 39% of the centers prescribe VKA and ASA, 37% prescribe VKA and 24% prescribe ASA. After the first three postoperative months following bioprosthetic AVR, 61% of the centers prescribe only ASA, while 39% do not prescribe any therapy. Patients with bioprosthetic AVR and CABG receive ASA in 90% centers, in 2% centers VKA and ASA, and 8% centers do not prescribe any antithrombotic. CONCLUSION: This study demonstrates that, despite guidelines published by several professional societies, medical practice for the prevention of thrombotic events early after bioprosthetic AVR varies widely among cardiac surgical centers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.001 | 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".