Long-term vitamin K antagonists treatment patterns of Non-Valvular Atrial Fibrillation (NVAF): a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Recent trends in vitamin K antagonists (VKA) use in non-valvular atrial fibrillation (NVAF) are useful to evaluate the potential improvement in management of NVAF since the introduction of new oral anticoagulants. Our objective was therefore to describe the contemporary VKA treatment patterns following NVAF diagnosis. METHODS AND RESULTS: We used the computerized databases of the Régie de l'assurance maladie du Québec (RAMQ), responsible for administering the universal health care services for all its residents, to identify a population-based cohort of 135,241 patients with an incident diagnosis of NVAF during 2000-2009 and RAMQ medication coverage. Following NVAF diagnosis, 47.1 % of the patients were prescribed VKA, 35.5 % received an antiplatelet only, and 17.4 % did not initiate antithrombotic therapy. The proportion of patients initiating VKA within 3 months of diagnosis increased from 33 % to 39 % over the 10-year study period, mainly driven by a higher proportion of treated patients aged 80 or more (from 29 % to 41 %). At the end of the study period, women were prescribed VKA as frequently as men, except in the subgroup of patients with a low risk of ischemic stroke. The median time from VKA initiation to the first discontinuation varied greatly according to the definition of discontinuation, ranging from 11 months to 5.7 years. CONCLUSION: Although VKA remain underused after NVAF diagnosis, there has been an increase in VKA treatment over the last decade, particularly among older patients. Also the gap in treatment between men and women has been closing within the last decade. Once initiated, most VKA interruptions were temporary rather than definitive.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.000 |
| 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 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".