Jurisdictional Guidance on DOAC Use—Will It Affect Practice? A Comparison of European, American, and Canadian Product Monographs
Bibliographic record
Abstract
Objective: To identify clinically relevant areas of concordance and discordance between product monographs for 4 direct oral anticoagulants (DOACs) approved by regulatory authorities in Europe, the United States, and Canada. Data Sources: For each DOAC (apixaban, dabigatran, edoxaban, rivaroxaban), manufacturer product monographs were retrieved from the European Medicines Database, US Food and Drug Administration, and Health Canada Drug Product Database. Data Extraction: Monographs for each DOAC were independently reviewed by 2 investigators to identify areas of concordance and discordance. Discordance existed if it was deemed that a potentially clinically relevant difference existed. A heat map summarizing the data was created to identify areas of complete concordance, partial concordance (concordance between 2 of 3 monographs), and complete discordance. Data Synthesis: The areas of concordance were indications for use, use in extremes of weight, and switching to/from the DOAC. Areas of discordance included the following: differing recommendations for use/dosing with renal dysfunction; contraindication or use with caution with drug interactions, pregnancy, and hepatic/renal dysfunction; and timing of DOAC with spinal/epidural anesthesia after a procedure or traumatic puncture. Relevance to Patient Care and Clinical Practice: Concordance was most evident for uncomplicated patients with atrial fibrillation or venous thromboembolism, whereas discordance emerged for those having characteristics/factors wherein clinicians may seek clarification within product monographs (eg, impaired renal/hepatic function, drug interactions). As such, clinicians must be familiar with product information within their country of practice. Conclusion: Variability between jurisdictions was evident, and variability of DOAC use is likely to increase with expanding worldwide uptake.
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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 | 0.063 | 0.277 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.020 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.003 |
| 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".