Abstract W P339: Anticoagulation Remains Underutilized in the Management of Atrial Fibrillation: Results From the Edmonton Registry of Atrial Fibrillation and StrokE (ERASE) Study
Bibliographic record
Abstract
Background: Since 2010, three novel oral anticoagulants (NOAC) have been approved and included in the guidelines as alternatives to warfarin for the prevention of stroke in patients with non-valvular atrial fibrillation (NVAF). Prior to the introduction of NOACs, studies showed that anticoagulation with warfarin in stroke patients with NVAF is suboptimal with as few as 40% anticoagulated and most subtherapeutic. The goal of this study is to examine anticoagulation usage in a contemporary prospective registry of TIA/stroke patients with NVAF and determine whether the introduction of NOACs has increased anticoagulation usage. Methods: This is an ongoing single centre observational study. Consecutive TIA/ischemic stroke admissions (2012-13) to a tertiary hospital in Edmonton, Canada with NVAF were enrolled. Data regarding demographic, clinical, antithrombotic treatment and laboratory parameters were collected in a prospectively maintained database. Those with previously diagnosed NVAF were included in the present analysis (149/181). Clinical characteristics were compared between patients on anticoagulants and those on other/no antithrombotic therapy. Results: The 149 included patients had a mean (SD) age of 78.7 (10.0) years. Male were 52.3% and 86.6% (129) had a preadmission CHADS2 score ≥2. At the time of TIA/stroke, 51% (76/149) were on an anticoagulant, 24.2% (36/149) on antiplatelet agents and 28.4% (37/149) were on no antithrombotic therapy. Of the 76 patients on anticoagulants, 81.6% were on warfarin and the remaining (18.4%) were on a NOAC. Only 31% of patients on warfarin had a therapeutic INR at the time of stroke. Patients not anticoagulated had a similar frequency of prior stroke (21% vs. 23%; p=0.80) but tended to have a lower CHADS2 score (p=0.082) than those anticoagulated. In patients with CHADS≥2, 47% were not on an anticoagulant. Conclusions: Despite therapeutic advances in the treatment of NVAF, anticoagulation usage in TIA/stroke patients with preexisting NVAF remains suboptimal. In this study, only 53% of patients with NVAF and a CHADS≥2 were treated with anticoagulants. This study emphasizes the need for increased efforts to encourage prescribing of oral anticoagulants in high-risk individuals.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".