Reclassification of Ischemic Stroke Etiological Subtypes on the Basis of High-Risk Nonstenosing Carotid Plaque
Bibliographic record
Abstract
Background and Purpose- Carotid artery plaque with <50% luminal stenosis may be an underappreciated stroke mechanism. We assessed how many stroke causes might be reclassified after accounting for nonstenosing plaques with high-risk features. Methods- We included patients enrolled in the Cornell Acute Stroke Academic Registry from 2011 to 2015 who had anterior circulation infarction, magnetic resonance imaging of the brain, and magnetic resonance angiography of the neck. High-risk plaque was identified by intraplaque hemorrhage ascertained from routine neck magnetic resonance angiography studies using validated methods. Infarct location was determined from diffusion-weighted imaging. Intraplaque hemorrhage and infarct location were assessed separately in a blinded fashion by a neuroradiologist. We used the McNemar test for matched data to compare the prevalence of intraplaque hemorrhage ipsilateral versus contralateral to brain infarction. We reclassified stroke subtypes by including large-artery atherosclerosis as a cause if there was intraplaque hemorrhage ipsilateral to brain infarction, regardless of the degree of stenosis. Results- Among the 1721 acute ischemic stroke patients registered in the Cornell Acute Stroke Academic Registry from 2011 to 2015, 579 were eligible for this analysis. High-risk plaque was more common ipsilateral versus contralateral to brain infarction in large-artery atherosclerotic (risk ratio [RR], 3.7 [95% CI, 2.2-6.1]), cryptogenic (RR, 2.1 [95% CI, 1.4-3.1]), and cardioembolic strokes (RR, 1.7 [95% CI, 1.1-2.4]). There were nonsignificant ipsilateral-contralateral differences in high-risk plaque among lacunar strokes (RR, 1.2 [95% CI, 0.4-3.5]) and strokes of other determined cause (RR, 1.5 [95% CI, 0.7-3.3]). After accounting for ipsilateral high-risk plaque, 88 (15.2%) patients were reclassified: 38 (22.6%) cardioembolic to multiple potential etiologies, 6 (8.5%) lacunar to multiple, 3 (15.8%) other determined cause to multiple, and 41 (20.8%) cryptogenic to large-artery atherosclerosis. Conclusions- High-risk carotid plaque was more prevalent ipsilateral to brain infarction across several ischemic stroke subtypes. Accounting for such plaques may reclassify the etiologies of up to 15% of cases in our sample.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".