Which Recommendations Are You Using? A Survey of Emergency Physician Management of Paroxysmal Atrial Fibrillation
Bibliographic record
Abstract
Background Both the Canadian Cardiovascular Society (CCS) and the Canadian Association of Emergency Physicians (CAEP) have published documents to guide atrial fibrillation (AF) management. In 2021, the CAEP updated its AF checklist. Prior to this update, the recommendations of the 2 organizations differed in several key areas, including the suggested cardioversion timeframe, the factors determining cardioversion eligibility, and anticoagulant initiation after cardioversion. Whether emergency physicians (EPs) are aware of, or adhering to, one, both, or neither of these documents is unknown. Methods We assessed document awareness, adherence, and EP practice using a piloted questionnaire administered to EPs at 5 emergency departments in 3 provinces. Results Of 166 survey recipients, 123 (74.1%) responded. The majority (64.7%) worked at an academic site, 38.8% identified as female, and median years in practice was 10.0. Most (93.1%) were aware of at least one of the documents; 45.7% were aware of both. Reported awareness was higher for the CCS (77.6%) vs the CAEP (61.2%) guidelines. Respondents varied in their adherence, with 40.5% using parts of both documents. Considerable practice variability occurred when recommendations conflicted. Despite its use not being recommended by either organization, half of respondents (50.0%) reported using the CHA 2 DS 2 -VASc score as their stroke-risk assessment tool. Conclusions Although most surveyed EPs were aware of at least one organization's AF documents, many reported using parts of both. When recommendations conflicted, EPs were divided in their decision-making. These findings emphasize the need to improve consensus between organizations and further improve knowledge translation.
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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 | 0.008 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".