Efficacy and safety of the target-specific oral anticoagulants for stroke prevention in atrial fibrillation: the real-life evidence
Bibliographic record
Abstract
The aim of our article is to provide a concise review for clinicians entailing the main studies that evaluated the efficacy and safety of target-specific oral anticoagulants (TSOAs) for thromboembolic stroke prevention in the real-world setting. Atrial fibrillation (AF) is one of the most common supraventricular arrhythmias that requires anticoagulation therapy to prevent stroke and systemic embolism. TSOAs, dabigatran, apixaban and rivaroxaban have become available as an alternative to warfarin anticoagulation in nonvalvular atrial fibrillation (NVAF). Randomized clinical trials showed non-inferior or superior results in efficacy and safety of the TSOAs compared with warfarin for stroke prevention in NVAF patients. For this reason, the 2012 update to the European Society of Cardiology guidelines for the management of AF recommends TSOAs as broadly preferable to vitamin K antagonists (VKAs) in the vast majority of patients with NVAF [Camm et al. 2012]. Although the clinical trial results and the guideline’s indications, there is a need for safety and efficacy data from unselected patients in everyday clinical practice. Recently, a large number of studies testing the efficacy and the safety of TSOAs in clinical practice have been published. The aim of our article is to provide a concise review for clinicians, outlining the main studies that evaluated the efficacy and safety of TSOAs for thromboembolic stroke prevention in the real-world setting.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".