Abstract 4362017: Patient Preferences for Antithrombotic Therapy for Stroke Prevention in Device-Detected Subclinical Atrial Fibrillation: A Probability Trade-Off Interview Study
Bibliographic record
Abstract
Introduction: Device-detected subclinical atrial fibrillation (AF) is common in patients with implanted cardiac rhythm devices. The ARTESiA trial demonstrated that in patients with subclinical AF, apixaban, as compared to aspirin, reduced stroke (0.98% versus 2.25% per year, 5 fewer strokes in 4 years with CHA 2 DS 2 -VASc > 4). However, apixaban also increased major bleeding (2.13% vs 1.45% per year, 2.72 more bleeds in 4 years with CHA 2 DS 2 -VASc > 4). Our objective was to estimate patient thresholds for stroke prevention and bleeding avoidance, as these factors may influence treatment decisions. Methods: Trained interviewers enrolled patients with a CHA 2 DS 2 -VASc score ≥ 4 (irrespective of AF history) from a tertiary care pacemaker/defibrillator clinic. Participants underwent a structured interview with a probability trade-off tool. We determined risk thresholds for the minimum 4-year reduction in stroke necessary to prefer apixaban compared to aspirin (minimal important difference, stroke MID) and the maximum tolerable number of major bleeds to prevent one stroke (maximum allowable difference, bleed MAD). We grouped participants into one of four preference clusters: stroke averse (accepting of bleeds to prevent stroke), bleeding averse (accepting of stroke to prevent bleeds), realist (accepting of stroke or bleed) and idealist (unwilling to accept stroke or bleed). Results: Among 415 individuals approached, 300 participants consented and 275 completed the full interview. Mean age was 81.5 ± 6.9 years, 55.3% were female, median CHA 2 DS 2 -VASc score was 4 (IQR 4-5), and 148 (53.8%) had a history of AF. The overall mean stroke MID was 5.0 ± 4.5, meaning that on average, patients require a 5% reduction in stroke over 4 years of follow up to justify apixaban over aspirin. The overall bleed MAD was 8.0 ± 4.0, meaning that on average, patients were willing to endure 8 additional major bleeds to prevent one stroke. The highest proportion of participants were stroke averse (49.1%); a minority were bleeding averse (16.7%), realist (15.3%) and idealist (18.9%) [Figure]. Conclusions: Among patients with a cardiac rhythm device and CHA 2 DS 2 -VASc ≥ 4, the mean stroke risk reduction to justify the increased bleeding risk on apixaban, as compared to aspirin, is in line with the reduction in stroke seen for patients with subclinical AF in ARTESiA. Patients will accept a mean 8 additional bleeds to prevent one stroke. Patients are 3 times more likely to be stroke averse than bleeding averse.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".