Stroke prevention in atrial fibrillation changes after dabigatran availability in China: The GLORIA‐AF registry
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Bibliographic record
Abstract
BACKGROUND: Until the approval of dabigatran etexilate, treatment choices for stroke prevention in patients with atrial fibrillation (AF) were vitamin K antagonists (VKAs) or antiplatelet drugs. This analysis explored whether availability of non-vitamin K antagonist oral anticoagulants post-dabigatran approval was associated with changing treatment patterns in China. METHODS: Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation (GLORIA-AF) collected data on antithrombotic therapy choices for patients with newly diagnosed nonvalvular AF at risk for stroke. In China, enrollment in phase 1 (before dabigatran approval) and phase 2 (after dabigatran approval) occurred from 2011 to 2013 and 2013 to 2014, respectively. Analyses were restricted to sites within China that contributed patients to both phases. The weighted average of the site-specific results was estimated for standardization. Sensitivity analyses used multiple regression. RESULTS: -VASc ≥2) and bleeding (HAS-BLED ≥3); 55.5% were male. In phase 1, 16.7%, 61.6%, and 21.7% of patients were prescribed oral anticoagulants (OACs), antiplatelet agents, and no treatment, respectively. Respective proportions were 26.4%, 40.6%, and 33.0% in phase 2. The absolute increase in the site-standardized proportion of patients prescribed OACs after dabigatran availability was 9.9% (95% confidence interval [CI]: 3.7%-16.0%). There was a standardized 17.3% (95% CI: -24.3% to -10.4%) absolute decrease in antiplatelet agent use. CONCLUSIONS: There was an increase in OAC and decrease in antiplatelet agent prescription since dabigatran availability in China. However, a large proportion of AF patients at risk for stroke remained untreated.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it