Patterns of oral anticoagulants use in atrial fibrillation.
Bibliographic record
Abstract
BACKGROUND: Novel oral anticoagulants are available for the management of atrial fibrillation and are considered more convenient to use than warfarin. OBJECTIVE: The main objective of this study was to describe patterns of oral anticoagulant use in the 6 months period following the availability of dabigatran at our hospital. METHODS: A cross-sectional study was conducted in a single University hospital in the province of Québec, Canada. Medical records of subjects on oral anticoagulants for atrial fibrillation that were hospitalized between October 1st, 2011 and March 31th, 2012 were reviewed. Type of use (prevalent, incident and switch) and patient's characteristics of warfarin and dabigatran users were compared using Chi-squared and T-tests. RESULTS: In the 6-month period following dabigatran availability in the hospital, 59 patients (13%) were on dabigatran and 388 (87%) on warfarin. Mean CHADS2 score, mean age and mean number of chronic medications were lower in the dabigatran group. The percentage of patients with coronary artery disease was lower and renal function was higher in the dabigatran group. CONCLUSION: Dabigatran use remained low in the first 6 months period following the approval of dabigatran at our hospital, which could be explained by limited data on the efficacy and safety of this agent in subjects with multiple comorbidities.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".