Multiterritory Brain Infarcts, Anticoagulation, and Recurrence After Cryptogenic Stroke: A Subgroup Analysis of the ARCADIA Trial
Bibliographic record
Abstract
BACKGROUND: In patients with cryptogenic stroke, the characteristics of multiterritory brain infarcts, the recurrent stroke risk, and the response to anticoagulation remain unclear. METHODS: The ARCADIA trial (Atrial Cardiopathy and Antithrombotic Drugs in Prevention After Cryptogenic Stroke) screened patients with cryptogenic stroke for atrial cardiopathy at 185 centers in the United States and Canada from 2018 to 2022. Investigators reported baseline acute brain infarction in the left anterior, right anterior, and posterior circulation. Atrial cardiopathy was defined as P-wave terminal force in ECG lead V1s >5000 μV·ms, NT-proBNP (N-terminal pro-B-type natriuretic peptide) >250 pg/mL, or left atrial diameter index ≥3 cm/m 2 . Site echocardiography laboratories determined left atrial diameter index and a central echocardiography laboratory determined LVEF. We used ANCOVA to examine whether atrial cardiopathy biomarkers or LVEF were associated with the number of territories with infarction. Cox regression was used to examine whether the number of infarct territories was associated with recurrent stroke or modified the effect of apixaban compared with aspirin. RESULTS: Among 3464 patients with reported baseline magnetic resonance imaging data, 220 (6.4%) had no visible acute infarct and 2794 (80.7%) had acute infarction in 1, 374 (10.8%) in 2, and 76 (2.2%) in 3 territories. Atrial cardiopathy biomarkers and LVEF were not associated with the number of infarct territories. Among 937 of these 3464 patients who were randomized, we found higher risks of recurrent stroke associated with infarcts in 2 territories (hazard ratio, 2.4 [95% CI, 1.3–4.2]) or 3 territories (hazard ratio, 3.7 [95% CI, 1.5–9.3]) relative to single-territory infarction, whereas the absence of visible infarction was not associated with recurrence (hazard ratio, 1.8 [95% CI, 0.6–4.9]). The number of infarct territories did not modify the effect of apixaban versus aspirin in relation to recurrent stroke ( P for interaction, 0.71). CONCLUSIONS: Multiterritory brain infarction was not associated with atrial cardiopathy biomarkers or LVEF in the ARCADIA trial. Multiterritory infarction was associated with a significantly higher risk of recurrent stroke, but this heightened risk was not reduced by apixaban relative to aspirin.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".