P3862A prospective global registry on oral antithrombotic treatment in patients with atrial fibrillation: GLORIA-AF Phase III baseline characteristics
Bibliographic record
Abstract
Background/Introduction: Following the introduction of non-vitamin K antagonist oral anticoagulants (NOACs), treatment patterns for stroke prevention in patients with atrial fibrillation (AF) are changing. GLORIA-AF is a prospective, three-phase, global registry program, which assesses treatment patterns and outcomes in patients with AF. Phase III enrollment started ∼2 years after the first NOAC, dabigatran etexilate, was approved for stroke prevention in AF in the respective countries. Methods: Newly diagnosed AF patients at risk of stroke were consecutively enrolled from January 2014–December 2016 at 935 clinical sites in 38 countries reflecting a wide variety of physicians and settings. Sites were eligible based on availability of both dabigatran and vitamin K antagonists [(VKA). Results: 21,248 eligible patients (median age 71; 44.9% female) in four geographical regions were enrolled. Stroke risks were high (CHA2DS2-VASc score ≥2) for 85.6% of patients and 9.3% had known high bleeding risk (HAS-BLED ≥3). Overall, oral anticoagulation was prescribed in 82.2% of patients (NOACs: 59.5% and VKAs: 22.7%), antiplatelet drugs alone in 11.2%, and 6.6% of patients received no antithrombotic therapy. Use of oral anticoagulants (OACs) was lower in Asia (61.5% vs other regions, 87.4%) where patients were less often at high stroke risk (78.7% vs 87.3%) and more often at high bleeding risk (11.8% vs 8.7%) than in other regions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".