Heart Rhythm Monitoring Practices, Detection of Atrial Fibrillation, and Effect of Anticoagulation in the ARCADIA Trial
Bibliographic record
Abstract
Background The ARCADIA (Atrial Cardiopathy and Antithrombotic Drugs in Prevention After Cryptogenic Stroke) trial found no benefit of anticoagulation for preventing recurrent stroke in patients with atrial cardiopathy. Data on AF monitoring across trial sites may provide context for the findings and knowledge about the current standard of care for poststroke monitoring. Methods At study visits, sites reported any preceding use of prolonged heart rhythm monitoring, classified as either external ambulatory monitors or implantable loop recorders. We used relative risk regression, least absolute shrinkage and selection operator (LASSO) regression, and survival analysis to explore patient characteristics associated with monitoring, the association between monitoring and AF detection, and the interaction between monitoring and study treatment effect on recurrent stroke. Results Of 1633 patients with monitoring data, 957 (58.6%) underwent prolonged monitoring: 567 (34.7%) external ambulatory monitor, 479 (29.3%) implantable loop recorder, and 89 (5.5%) both. The strongest predictors of monitoring were Hispanic ethnicity (standardized LASSO coefficient, −0.19 [risk ratio (RR), 0.66]), National Institutes of Health Stroke Scale score (LASSO, −0.15 [RR per point, 0.97]), left atrial diameter (LASSO, 0.13 [RR per cm, 1.09]), and serum hemoglobin (LASSO, −0.12 [RR per g/dL, 0.97]). At the site level, the median proportion of patients who underwent monitoring was 63% (interquartile range, 36%–92%). The site‐level proportion of patients with an implantable loop recorder was associated with greater likelihood of AF detection (RR, 3.9 [95% CI, 2.1–7.4]) but did not modify the trial treatment effect ( P value for interaction, 0.99). Conclusions In the ARCADIA trial, which enrolled patients with cryptogenic stroke across the United States and Canada, nearly 60% of patients underwent prolonged heart rhythm monitoring. Use of implantable loop recorders was associated with greater likelihood of AF detection.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".