Descriptive Analysis of the Process and Quality of Oral Anticoagulation Management in Real-Life Practice in Patients with Chronic Non-valvular Atrial Fibrillation
Bibliographic record
Abstract
Background/objectives: Expert oral anticoagulation management is the key to good outcomes and is performed variably in different health care systems throughout the world. We set out to assess the quality of anticoagulation management in five countries in patients receiving vitamin K antagonists (VKAs) for stroke prophylaxis in chronic non-valvular atrial fibrillation (NVAF), and to compare the anticoagulation management practices in these countries. \nMethods and results: This was a retrospective, multi-centre cohort study in the United States, Canada, France, Italy, and Spain. About 1,511 patients were randomly recruited from representative practices (routine medical care (RMC) in the US, Canada, and France; anticoagulation clinics in Italy and Spain) and data pertaining to their oral anticoagulation care were abstracted from their medical records. The predominant anticoagulant in use was warfarin in the US, Canada, and Italy; acenocoumarol in Spain; and fluindione in France. Documentation of care was poor in the US, Canada, and France, countries where RMC was studied. Percent INRs or time-in-therapeutic range was greater in the two anticoagulation clinic samples compared with the RMC samples. \nConclusion: Oral anticoagulation care varies considerably from country to country. Findings suggest that anticoagulation clinic care (ACC) may provide better outcomes as assessed by international normalized ratio (INR) time-in-range. Physicians tend to under treat more than over treat. Finally, documentation of care is often inadequate.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".