Methodological considerations for investigating oral anticoagulation persistence in atrial fibrillation
Bibliographic record
Abstract
AIMS: Reports of long-term oral anticoagulant (OAC) therapy for atrial fibrillation (AF) reveal highly variable, and generally suboptimal estimates of medication persistence. The objective of this review is to summarize current literature and highlight important methodological considerations for interpreting persistence research and designing studies of persistence on OAC treatment. METHODS AND RESULTS: We summarize differences in study methodology, setting, timing, treatment, and other factors associated with reports of better or worse persistence. For example, prospective compared with retrospective study designs are associated with higher reported persistence. Similarly, patient factors such as permanent AF or high stroke risk, and treatment with non-vitamin K oral antagonists relative to vitamin K antagonists are associated with higher persistence. Persistence has also been reported to be higher in Europe compared with North America and higher when the treating physician is a general practitioner compared with a specialist. We propose a framework for assessing and designing persistence studies. This framework includes aspects of patient selection, reliability and validity of measures, persistence definitions, clinical utility of measurements, follow-up periods, and analytic approaches. CONCLUSIONS: Differences in study design, patient selection, treatments, and factors such as the countries/regions where studies are conducted or the type of treating physician may help explain the variability in OAC persistence estimates. A framework is proposed to assess persistence studies. This may have utility to compare and interpret published studies as well as for planning of future studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".