Abstract 136: Infarct Topography, Effect of Anticoagulation, and Recurrence after Cryptogenic Stroke: A Subgroup Analysis of the ARCADIA Trial
Bibliographic record
Abstract
Introduction: The ARCADIA trial found no benefit of anticoagulation for secondary stroke prevention in patients with cryptogenic stroke and evidence of atrial cardiopathy. The trial screened all patients with cryptogenic stroke, regardless of infarct topography. Acute brain infarction in multiple arterial territories could more strongly suggest a central embolic source. The recurrent stroke risk and role of apixaban versus aspirin in these patients is not well understood. Hypothesis: Cryptogenic stroke patients with multi-territory infarction are at increased risk for recurrent stroke, and this population will benefit from treatment with apixaban compared to aspirin. Methods: The ARCADIA trial screened patients with cryptogenic stroke for atrial cardiopathy at 185 centers in the U.S. and Canada. Among participants who met eligibility criteria for atrial cardiopathy and were randomly assigned to treatment assignment, we performed a subgroup analysis of those with multi-territory infarction, defined as acute infarction in at least two of the following territories: left anterior circulation, right anterior circulation, or posterior circulation. Cox models were used to compare stroke recurrence in patients with multi-territory versus single-territory infarction. Models were adjusted for age, sex, race, ethnicity, heart failure, coronary artery disease, peripheral artery disease, hypertension, diabetes, and tobacco use. We used tests of interaction to compare the effect of apixaban versus aspirin in patients in multi- versus single-territory infarcts. Results: Of 1,015 randomized patients in ARCADIA, 123 had multi-territory infarction, of whom 55 (44.7%) received apixaban and 68 (55.3%) received aspirin. Risk of recurrent stroke was higher in patients who presented with multi-territory infarcts (HR 2.5, 95% CI 1.50-4.18). When adjusting for demographics and vascular risk factors, results were similar (HR 2.5, 95% CI 1.48-4.15). There was a similar lack of benefit of apixaban in patients with multi-territory infarct (HR 1.0, 95% CI 0.62-1.71) versus single-territory infarct (HR 1.0, 95% CI 0.43-2.51) ( P for interaction = 0.98). Conclusion: In patients with cryptogenic stroke and markers of atrial cardiopathy, multi-territory infarction was associated with an increased risk of recurrent stroke, but this population did not benefit from anticoagulation compared 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".