Regional Differences in Antithrombotic Treatment for Atrial Fibrillation: Insights from the GLORIA-AF Phase II Registry
Bibliographic record
Abstract
Introduction Although guideline-adherent antithrombotic therapy (ATT) for stroke prevention in atrial fibrillation (AF) is associated with lower mortality and thromboembolism, ATT uptake shows geographic variation worldwide. We aimed to assess thromboembolic risk and baseline ATT by geographic region and identify factors associated with prescription of ATT in a large, truly global registry of patients with recently diagnosed AF. Methods and Results Our analysis comprises 15,092 patients newly diagnosed with non-valvular AF at risk for stroke, enrolled in Phase II of Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation (GLORIA-AF). Global oral anticoagulation (OAC) use was 79.9%, being highest in Europe (90.1%), followed by Africa/Middle East (87.4%) and Latin America (85.3%), North America (78.3%) and Asia (55.2%). Among OAC users, vitamin K antagonists (VKAs) have been replaced by non-VKA OACs (NOACs) as the more prevalent OAC option in all regions, with highest use in North America (66.5%) and lowest in Asia (50.2%). In Asia, OAC was 80.4% in community hospitals but only 49.8% in university hospitals and 42.6% in specialist offices, and varied from 21.0% in China to 89.7% in Japan (NOACs at 5.8% in China and 83.3% in Japan). Globally, 76.5% of low-risk patients were prescribed ATT (46.1% OAC), whereas 17.7% high-risk patients were not anticoagulated (Europe 8.8%; North America 18.9%; Asia 42.4%). Conclusion Substantial inter- and intra-regional differences in ATT for stroke prevention in AF are evident in this global registry. While guideline-adherent ATT can be further improved, NOACs are the main contributor to high OAC use worldwide.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".