Values and preferences in oral anticoagulation in patients with atrial fibrillation, physicians' and patients' perspectives: protocol for a two-phase study
Bibliographic record
Abstract
BACKGROUND: Oral anticoagulation prevents strokes in patients with atrial fibrillation but, for reasons that remain unclear, less than 40% of all patients with atrial fibrillation receive warfarin. The literature postulates that patient and clinician preferences may explain this low utilization. DESIGN: The proposed research seeks to answer the following questions: i) When assessed systematically, do patients' and clinicians' preferences explain the utilization of warfarin to prevent strokes associated with atrial fibrillation? ii) To what extent do patients' and clinicians' treatment preferences differ? iii) What factors explain any differences that exist in treatment preferences between patients and clinicians? To answer these questions we will conduct a two-phase study of patient and clinician preferences for health states and treatments. In the first phase of this study we will conduct structured interviews to determine their treatment preferences for warfarin vs. aspirin to prevent strokes associated with atrial fibrillation using the probability trade-off technique. In the same interview, we will conduct preference-elicitation exercises using the feeling thermometer to identify the utilities that patients place on taking medication (warfarin and aspirin), and on having a mild stroke, a severe stroke, and a major bleed. In the second phase of the study we will convene focus groups of clinicians and patients to explore their answers to the exercises in the first phase. DISCUSSION: This is a study of patient and clinician preferences for health states and treatments. Because of its clinical importance and our previous work in this area, we will conduct our study in the clinical context of the decision to use antithrombotic agents to reduce the risk of stroke in patients with non-valvular chronic atrial fibrillation.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| grok | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| opus | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.063 | 0.071 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.049 | 0.010 |
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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".