Early risk of stroke after a transient ischemic attack in patients with internal carotid artery disease
Bibliographic record
Abstract
BACKGROUND: Transient ischemic attacks (TIAs) often herald a stroke, but little is known about the acute natural history of TIAs. Our objective was to quantify the early risk of stroke after a TIA in patients with internal carotid artery disease. METHODS: Using patient data from the medical arm of the North American Symptomatic Carotid Endarterectomy Trial, we calculated the risk of ipsilateral stroke in the territory of the symptomatic internal carotid artery within 2 and 90 days after a first-recorded hemispheric TIA. We also studied similar outcomes among patients in the trial who had a first-recorded completed hemispheric stroke. RESULTS: For patients with a first-recorded hemispheric TIA (n = 603), the 90-day risk of ipsilateral stroke was 20.1% (95% confidence interval [CI] 17.0%-23.2%), higher than the 2.3% risk (95% CI 1.0%-3.6%) for patients with a hemispheric stroke (n = 526). The 2-day risks were 5.5% and 0.0%, respectively. Patients with more severe stenosis of the internal carotid artery (> 70%) appeared to be at no greater risk of stroke than patients with lesser degrees of stenosis (adjusted hazard ratio 1.1, 95% CI 0.7-1.7). Infarct on brain imaging (adjusted hazard ratio 2.1, 95% CI 1.5-3.0) and the presence of intracranial major-artery disease (adjusted hazard ratio 1.9, 95% CI 1.3-2.7) doubled the early risk of stroke in patients with a hemispheric TIA. INTERPRETATION: Patients who had a hemispheric TIA related to internal carotid artery disease had a high risk of stroke in the first few days after the TIA. Early risk of stroke was not affected by the degree of internal carotid artery stenosis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".