Atrial fibrillation in outpatients with stable coronary artery disease : results from the multicenter RECENT study
Bibliographic record
Abstract
INTRODUCTION: Atrial fibrillation (AF) frequently coexists with other cardiovascular diseases. OBJECTIVES: The aim of this study was to assess the prevalence of AF in outpatients with stable coronary artery disease (CAD) and to determine clinical and laboratory parameters associated with the higher prevalence of this arrhythmia. In addition, we compared the indications for antithrombotic treatment using the older CHADS₂ and the currently used CHA₂DS₂-VASc scores. PATIENTS AND METHODS: We studied the clinical data of 2578 Polish patients with stable CAD participating in the multicenter RECENT study (age, 65 ±10 years; men, 55%; Canadian Cardiovascular Society class I/II/III+IV, 38%/48%/14%). RESULTS: AF was present in 19% of patients with CAD. Advanced age, longer history of CAD, and concomitant heart failure were independently associated with the higher prevalence of AF (all P <0.05). Among patients with CAD and AF, 73% of the patients required antithrombotic treatment according to the CHADS₂ score (≥2), and 94%-according to the CHA₂DS₂-VASc score (≥2). A CHA₂DS₂-VASc score of 2 or higher was found in 47% of the patients with a CHADS₂ score of 0 and 85% of those with a CHADS2 score of 1. Twenty-one percent of patients with CAD and AF did not have unequivocal indications for antithrombotic treatment according to the CHADS₂ score (0-1), while they had strong indications for such treatment on the basis of the CHA₂DS₂-VASc score (≥2). CONCLUSIONS: AF affects every fifth ambulatory patient with CAD. According to the CHA₂DS₂-VASc score, almost all patients with CAD and AF require antithrombotic treatment, which may complicate coronary revascularization and related antiplatelet treatment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".