Abstract TP428: Antithrombotic Therapy in Patients With Atrial Fibrillation and Prior Stroke in GLORIA- AF Phase II (Global Registry on Long-term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation, Phase II)
Bibliographic record
Abstract
Introduction: Given their substantial risk of recurrent stroke, patients with atrial fibrillation (AF) and prior stroke are at highest risk. Such patients should be pre-scribed oral anticoagulants (OAC), either a Vitamin K Antagonist (VKA) or Non-VKA OAC (NOAC). Methods: Using an inception cohort design, GLORIA-AF collected data on choice of antithrombotic therapy for patients with newly identified AF at risk of stroke (CHA2DS2VASc scores ≥ 1) in the course of routine care. We examined the use of an-tithrombotic therapy in those with prior stroke. Results: From 15,092 patients in Phase II of GLORIA-AF enrolled in 5 geographical regions worldwide (Europe, North America, Asia, Latin America and Africa/Middle East), 1,582 patients (median age 75 years, 54.9% male) had previous stroke, with a median CHA2DS2-VASc score of 5, compared with a score of 3 in those without previ-ous stroke (n=13,500). For 10 patients previos stroke status was unknown. In those with previous stroke, VKA alone was prescribed in 25.2%, VKA plus an-tiplatelet therapy (AP) in 5.8%, NOAC alone in 42.9%, NOAC plus AP in 7.7%, and AP alone in 12.1%; 6.3% received no antithrombotic therapy. Proportions were broadly similar in males and females. In comparison, among patients without prior stroke the proportions on AP only or no therapy were a little higher (20.2 versus 18.3%). Among those with prior stroke, proportions on AP alone in Asia, Europe, and North America were 24.2, 9.9 and 5.6% respectively, while proportions on no antithrombotic therapy in these regions were 16.3, 3.2 and 4.5%. Conclusion: In this prospective registry, AF patients with prior stroke and a median CHA2DS2-VASc score of 5, approximately 18% were treated with AP alone or no an-tithrombotic therapy, and the treatment gap was greater in Asia than in Europe or North America.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".