Apixaban to Prevent Covert Infarcts After Cryptogenic Stroke in Patients With Atrial Cardiopathy
Bibliographic record
Abstract
Importance: In the Atrial Cardiopathy and Antithrombotic Drugs in Prevention After Cryptogenic Stroke (ARCADIA) randomized clinical trial, anticoagulation did not prevent recurrent stroke among patients with a recent cryptogenic stroke and atrial cardiopathy. It is unknown whether anticoagulation prevents covert infarcts in this population. Objective: To test the use of apixaban vs aspirin for prevention of nonlacunar covert infarcts after cryptogenic stroke in patients with atrial cardiopathy. Design, Setting, and Participants: ARCADIA-MRI, an ancillary study to the ARCADIA trial with a median follow-up period of 27 months, enrolled participants from 75 sites in the US from November 14, 2019, until December 2, 2022. Participants in ARCADIA were invited to coenroll in ARCADIA-MRI if they had not permanently discontinued the study drug and had no contraindications on magnetic resonance imaging (MRI). A total of 310 (31%) of the 1015 ARCADIA participants enrolled in ARCADIA-MRI and of those 174 (56%) with adequate quality baseline and follow-up MRI were included in the present analyses. Interventions: MRI performed at the time of the index stroke served as the baseline image unless it was unavailable or of insufficient quality, in which case a new research MRI was obtained. A follow-up research MRI was performed upon each participant's completion of participation in the ARCADIA parent study. Main Outcomes and Measures: The primary outcome was incident nonlacunar covert infarct on the follow-up MRI assessed by 2 independent raters who were masked to treatment assignment. Results: Baseline characteristics were balanced between the apixaban (n = 79) and aspirin (n = 95) arms. The mean (SD) age was 66 (10.6) years, and the median (IQR) modified Rankin Scale (mRS) score 1 (0-2). Ninety-one participants (52.3%) were male. During the median (IQR) follow-up of 811 (487-1288) days, the risk of incident nonlacunar covert infarcts was lower in the apixaban group (5.1%) than the aspirin group (17.9%) (weighted relative risk, 0.29; 95% CI, 0.10-0.83). Conclusions and Relevance: Apixaban compared to aspirin was associated with fewer incident nonlacunar covert infarcts among a subset of patients with a recent cryptogenic ischemic stroke and atrial cardiopathy who were enrolled in ARCADIA. Trial Registration: ClinicalTrials.gov Identifier: NCT03192215.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".