How do family medicine residents choose an anticoagulation regimen for patients with nonvalvular atrial fibrillation?
Bibliographic record
Abstract
Aim To examine the choices Canadian family medicine residents make for oral anticoagulation (OAC) for patients with nonvalvular atrial fibrillation (AF). BACKGROUND: AF increases the risk of strokes. An important consideration in AF management is risk stratification for stroke and prescription of appropriate OAC. Family physicians provide the vast majority of OAC prescriptions. METHODS: We administered a survey to residents in multiple Canadian family medicine training programmes. Questions explored the experiences and attitudes towards risk stratification and choices of OAC when presented with standardized clinical scenarios. In each scenario, a novel oral anticoagulant (NOAC) would be the preferred treatment according to the contemporary Canadian and European guidelines. Findings A total of 247 residents participated in the survey. Most used the congestive heart failure, hypertension, age ≥ 75, diabetes mellitus, stroke or TIA (2 points) (81%) and congestive heart failure, hypertension, age ≥ 75 (2 points) or age 65-74 (1 point), diabetes mellitus, stroke or TIA, vascular disease including peripheral arterial disease, myocardial infarction, or aortic plaque, sex (female) (67%) risk stratification schemes while the preferred bleeding risk stratification scheme was hypertension, abnormal liver or renal function, stroke, bleeding, labile international normalized ratio, elderly (age ≥ 65), drugs or alcohol (84%). In the clinical scenarios, residents generally preferred warfarin in favour of NOACs, independent of training level. Residents ranked the risk of adverse events and the cost to the patient as their most and least important consideration when prescribing OAC, respectively. Therefore in patients with nonvalvular AF, Canadian family medicine residents prefer warfarin in comparison with NOACs despite the latest Canadian and European guideline recommendations. This knowledge gap may be enhanced by multiple factors, including a sometimes magnified fear of adverse events and a rapidly changing landscape in stroke prophylaxis.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".