Cohort profile: the ESC EURObservational Research Programme Atrial Fibrillation III (AF III) Registry
Bibliographic record
Abstract
AIMS: The European Society of Cardiology (ESC) EURObservational Research Programme (EORP)-Atrial Fibrillation (AF) III Registry aims to identify contemporary patterns in AF management in clinical practice, assess their compliance with the 2016 ESC AF Guidelines, identify major gaps in guideline implementation, characterize the clinical practice settings associated with good vs. poor guideline implementation and assess and compare the 1-year outcome of guideline-adherent vs. guideline non-adherent management strategies. METHODS AND RESULTS: Consecutive adult AF patients (n = 8306) were enrolled between 1 July 2018 and 15 July 2019, and individual patient data were prospectively collected across 192 centres and 31 participating countries during the 3-month enrolment period per centre. The Registry collected baseline and 1-year follow-up data in the eight main domains: patient demographic/enrolment setting, AF diagnosis/characterization, diagnostic assessment, stroke prevention treatments, arrhythmia-directed therapies, integrated AF management, major outcomes (death, non-fatal stroke or systemic embolic event, and non-fatal bleeding event), and the quality of life questionnaire. CONCLUSION: The EORP-AF III Registry is an international, prospective registry of care and outcomes of patients treated for AF, which will provide insights into the contemporary patterns in AF management, ESC AF Guidelines implementation in routine practice and barriers to optimal management of this highly prevalent arrhythmia.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.006 | 0.003 |
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".