Emerging therapies for stroke prevention in atrial fibrillation
Bibliographic record
Abstract
Atrial fibrillation (AF) is a major risk factor for stroke. Recent studies show that treatment strategies which combine control of ventricular rate with antithrombotic therapy are as effective as those strategies aimed at restoring sinus rhythm. Current antithrombotic therapy regimens in patients with AF involve chronic anticoagulation with dose-adjusted vitamin K antagonists (VKAs), unless patients have a contraindication to these agents or are at low risk for stroke. AF patients at low risk for stroke may benefit from aspirin. Although VKAs are effective, their use is problematic, highlighting the need for new antithrombotic strategies. This paper will (i) provide an overview of the clinical trials that form the basis for current antithrombotic guidelines in patients with AF, (ii) highlight the limitations of current antithrombotic drugs used for stroke prevention, (iii) review the pharmacology of new antithrombotic drugs under evaluation in AF, (iv) describe ongoing trials with new antiplatelet therapies and idraparinux, and completed studies with ximelagatran in patients with AF, (v) discuss the role of non-pharmacological techniques to reduce the risk of stroke in AF patients, and (vi) provide clinical perspective into the potential role of new antithrombotic drugs in AF.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".