Comparative effectiveness and safety of oral anticoagulants for atrial fibrillation in real-world practice: a population-based cohort study protocol
Bibliographic record
Abstract
INTRODUCTION: Anticoagulants are arguably the most important drug family of all, based on the frequency and duration of their use, and the clinical importance and frequency of benefits and harms. Several direct acting oral anticoagulants (DOACs) have recently joined warfarin for the treatment of atrial fibrillation, with a resultant significant expansion in use of oral anticoagulants (OACs). Our objectives are to compare safety and effectiveness of DOACs versus warfarin in a full population where anticoagulation management is good and to identify which types of patients do better with DOACs versus warfarin and vice versa. METHODS AND ANALYSIS: This is a retrospective cohort study of all adults living in British Columbia who have a diagnosis of atrial fibrillation in hospital or medical service data, and a first prescription for an OAC. Coprimary outcomes are ischaemic stroke and systemic embolism (benefit) and major bleeding (harm). Secondary outcomes include net clinical benefit (composite of stroke, systemic embolism, major bleeds, myocardial infarction, pulmonary embolism and death), drug discontinuation and individual composite item occurrence. We will estimate the effects of treatment in a 2-year follow-up period, using time-to-event models with propensity score adjustment to control confounding. Secondary analyses will examine 'as treated' outcomes. ETHICS AND DISSEMINATION: The protocol, data creation plan, privacy impact statement and data sharing agreements have been approved. Dissemination is planned via conferences and publications as well as directly to drug policy leaders. Information on the overall comparative effectiveness and safety of DOACs versus warfarin in a country with high quality anticoagulation management, as well as for vulnerable subgroups, will be an important addition to the literature.
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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 | 0.040 | 0.040 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.045 | 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, 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".