P4799When are atrial fibrillation patients at risk to discontinue anticoagulation treatment? Results from the GLORIA-AF Registry
Bibliographic record
Abstract
Background: Oral anticoagulation (OAC) discontinuation has posed a barrier to achieving optimal outcomes in atrial fibrillation (AF) patients, most notably in the era when vitamin K antagonists (VKA) were the principle OAC in use. Objectives: The objective of this investigation was to evaluate when newly diagnosed AF patients initiating dabigatran etexilate (DE) treatment are most prone to discontinue oral anticoagulation, and to describe reasons for discontinuation. Methods: Patients with newly diagnosed AF (CHA2DS2VASc≥1) were consecutively enrolled in a prospective global registry (GLORIA-AF). Enrollment began once DE was available in respective countries (from 2011–2014) and those prescribed DE were followed for 2 years. Treatment start and stop dates were recorded; discontinuation was defined as switch to another treatment or index treatment stop for >30 days. Kaplan Meier probabilities of remaining on treatment (persistence) were calculated. Reasons for discontinuation are presented as % of total patients. Results: Of 4,873 eligible patients prescribed DE (mean age 70.2±10.4 years; 44.4% female), 4,859 took at least 1 dose (99.7%). Mean index DE therapy duration for the first treatment regimen was 18.0±9.4 months; probability of DE persistence at 2 years was 70.4% (95% CI 0.69–0.72). After the 2 year visit, 1305 patients (26.9%) were identified as having stopped DE (n=684, 14.1%) or switched to another OAC (n=621, 12.8%) at any point during the follow-up. Overall probability of persistence for the first 6 months was 83.5% (95% CI 82.4–0.84.6%), and for subsequent cohorts who remained on treatment at 12, 18 and 24 months, probability of persistence (95% CI) was numerically higher in each consecutive 6 month period: 92.3% (91.3–93.1%), 94.9% (94.1–95.6%) and 96.1% (95.4–96.8%) at 12, 18 and 24 months respectively. Patients who discontinued due to adverse events (AE) represent <10% of patients, the majority of which were observed in the first 6 months. The most frequently reported reason for discontinuation was “other” reason not further specified.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".