Impact of oral anticoagulation in patients with atrial fibrillation at very low thromboembolic risk
Bibliographic record
Abstract
OBJECTIVE: To investigate reasons for and impact of oral anticoagulation (OAC) in patients with atrial fibrillation (AF) at very low thromboembolic risk. METHODS: -VASc score 0 (men) or 1 (women) from the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) were studied. Baseline characteristics according to OAC use were evaluated by logistic regression analysis. Non-haemorrhagic stroke or systemic embolism, major bleeding, cardiovascular and all-cause mortality were compared. RESULTS: -VASc patients in GARFIELD-AF, 44% received OAC. In an adjusted model, increasing age up to 65 years (OR (95% CI)=1.31 (1.19 to 1.44)) and persistent AF (OR (95% CI)=3.25 (2.44 to 4.34)) or permanent AF (OR (95% CI)=2.29 (1.59 to 3.30)) versus paroxysmal/unclassified AF were associated with OAC use. Concomitant antiplatelet therapy (OR (95% CI)=0.21 (0.17 to 0.27)) was inversely associated. Crude incidence rates per 100 person-years over 2 years in patients on OAC versus not on OAC were 0.32 (95% CI 0.14 to 0.71) vs 0.30 (95% CI 0.14 to 0.63) for non-haemorrhagic stroke or systemic embolism, 0.21 (95% CI 0.08 to 0.57) vs 0.17 (95% CI 0.06 to 0.46) for major bleeding, 0.26 (95% CI 0.11 to 0.64) vs 0.26 (95% CI 0.12 to 0.57) for cardiovascular mortality and 0.74 (95% CI 0.44 to 1.25) vs 0.99 (95% CI 0.66 to 1.49) for all-cause mortality. CONCLUSIONS: -VASc score receive OAC. Persistent or permanent AF and increasing age up to 65 years are associated with OAC use, while concomitant antiplatelet therapy shows an inverse association. Regardless whether patients received OAC therapy, few thromboembolic and bleeding events occur, highlighting the low risk of this population.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".