Use of Anticoagulants and Antiplatelet Agents in Stable Outpatients with Coronary Artery Disease and Atrial Fibrillation. International CLARIFY Registry
Bibliographic record
Abstract
BACKGROUND: Few data are available regarding the use of antithrombotic strategies in coronary artery disease patients with atrial fibrillation (AF) in everyday practice. We sought to describe the prevalence of AF and its antithrombotic management in a contemporary population of patients with stable coronary artery disease. METHODS AND FINDINGS: CLARIFY is an international, prospective, longitudinal registry of outpatients with stable coronary artery disease, defined as prior (≥12 months) myocardial infarction, revascularization procedure, coronary stenosis >50%, or chest pain associated with evidence of myocardial ischemia. Overall, 33,428 patients were screened, of whom 32,954 had data available for analysis at baseline; of these 2,229 (6.7%) had a history of AF. Median (interquartile range) CHA2DS2-VASc score was 4 (3, 5). Oral anticoagulation alone was used in 25.7%, antiplatelet therapy alone in 52.8% (single 41.8%, dual 11.0%), and both in 21.5%. OAC use was independently associated with permanent AF (p<0.001), CHA2DS2-VASc score (p=0.006), pacemaker (p<0.001), stroke (p=0.04), absence of angina (p=0.004), decreased left ventricular ejection fraction (p<0.001), increased waist circumference (p=0.005), and longer history of coronary artery disease (p=0.008). History of percutaneous coronary intervention (p=0.004) and no/partial reimbursement for cardiovascular medication (p=0.01, p<0.001, respectively) were associated with reduced oral anticoagulant use. CONCLUSIONS: In this contemporary cohort of patients with stable coronary artery disease and AF, most of whom are theoretical candidates for anticoagulation, oral anticoagulants were used in only 47.2%. Half of the patients received antiplatelet therapy alone and one-fifth received both antiplatelets and oral anticoagulants. Efforts are needed to improve adherence to guidelines in these patients. TRIAL REGISTRATION: ISRCTN registry of clinical trials: ISRCTN43070564.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".