How toMonitor Patients Receiving Direct Oral Anticoagulants for Stroke Prevention in Atrial Fibrillation: A Practice Tool Endorsed by Thrombosis Canada, the Canadian Stroke Consortium, the Canadian Cardiovascular Pharmacists Network, and the Canadian Card
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Anticoagulation for atrial fibrillation with direct oralanticoagulants (DOACs)—apixaban, dabigatran, edoxaban, and rivaroxaban—is one of the most power-ful stroke prevention interventions (1) and is now being prescribed to millions worldwide. Guidelines, however, have focused primarily on patient selection and therapy initiation, with little guidance on patient follow-up and monitoring for these long-term therapies. Given the in-creasing use of these agents, their associated risks for bleeding and nonadherence (one quarter of patients in recent reports was less than 80 % adherent [2–4]), the absence of routine coagulation monitoring, and vari-able follow-up practices, we advocate regular, stan-dardized clinical monitoring of patients receiving these agents aimed at minimizing adverse events (Table). GOALS OF ANTICOAGULANT FOLLOW-UP VISITS
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it