P3848Why do clinicians withhold anticoagulation in patients with atrial fibrillation and CHA2DS2VASc score of 2 or higher?
Bibliographic record
Abstract
Background: Guidelines recommend oral anticoagulant (OAC) therapy to prevent stroke and systemic embolism for atrial fibrillation (AF) patients at high thromboembolic risk (CHA2DS2-VASc score ≥2). Approximately 30–40% of eligible patients do not receive OAC therapy. The reasons for guideline non-adherence are unclear. Purpose: To identify patient characteristics associated with non-use of OAC for AF. Methods: The Global Anticoagulant Registry in the FIELD (GARFIELD-AF) registry is a prospective multicentre study of patients with newly diagnosed AF and ≥1 additional risk factors for stroke. We analysed GARFIELD-AF data for patient characteristics associated with non-use of OAC for patients with CHA2DS2-VASc score ≥2 using logistic regression. The rates per 100 person-years (%/y) of all-cause mortality, cardiovascular mortality, stroke or systemic embolism (SSE) and major bleeding were also compared between patients receiving and those not receiving OAC. P-values less than 0.05 were considered statistically significant. To explore patient characteristics that influence decision-making, we distributed a web-based survey to physicians treating AF in Belgium, Canada, France, and Portugal.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".