International trends in clinical characteristics and oral anticoagulation treatment for patients with atrial fibrillation: Results from the GARFIELD-AF, ORBIT-AF I, and ORBIT-AF II registries
Why this work is in the frame
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Bibliographic record
Abstract
Atrial fibrillation (AF) is the most common cardiac arrhythmia in the world. We aimed to provide comprehensive data on international patterns of AF stroke prevention treatment. Demographics, comorbidities, and stroke risk of the patients in the GARFIELD-AF (n = 51,270), ORBIT-AF I (n = 10,132), and ORBIT-AF II (n = 11,602) registries were compared (overall N = 73,004 from 35 countries). Stroke prevention therapies were assessed among patients with new-onset AF (≤6 weeks). Patients from GARFIELD-AF were less likely to be white (63% vs 89% for ORBIT-AF I and 86% for ORBIT-AF II) or have coronary artery disease (19% vs 36% and 27%), but had similar stroke risk (85% CHA2DS2-VASc ≥2 vs 91% and 85%) and lower bleeding risk (11% with HAS-BLED ≥3 vs 24% and 15%). Oral anticoagulant use was 46% and 57% for patients with a CHA2DS2-VASc = 0 and 69% and 87% for CHA2DS2-VASc ≥2 in GARFIELD-AF and ORBIT-AF II, respectively, but with substantial geographic heterogeneity in use of oral anticoagulant (range: 31%-93% [GARFIELD-AF] and 66%-100% [ORBIT-AF II]). Among patients with new-onset AF, non–vitamin K antagonist oral anticoagulant use increased over time to 43% in 2016 for GARFIELD-AF and 71% for ORBIT-AF II, whereas use of antiplatelet monotherapy decreased from 36% to 17% (GARFIELD-AF) and 18% to 8% (ORBIT-AF I and II). Among new-onset AF patients, non–vitamin K antagonist oral anticoagulant use has increased and antiplatelet monotherapy has decreased. However, anticoagulation is used frequently in low-risk patients and inconsistently in those at high risk of stroke. Significant geographic variability in anticoagulation persists and represents an opportunity for improvement.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it