Angiographically Defined Collateral Circulation and Risk of Stroke in Patients With Severe Carotid Artery Stenosis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Blood supply through collateral pathways improves regional cerebral blood flow and may protect against ischemic events. The effect of collaterals on the risk of stroke and transient ischemic attack (TIA), in the presence of angiographic severe internal carotid artery (ICA) stenosis, was assessed. METHODS: Angiographic collateral filling through anterior communicating and posterior communicating arteries and retrograde filling through ophthalmic arteries were determined in all patients at entry into the North American Symptomatic Carotid Endarterectomy Trial. Kaplan-Meier event-free survival analyses were performed on 339 medically treated and 342 surgically treated patients. RESULTS: The presence of collaterals supplying the symptomatic ICA increased with severity of stenosis. Two-year risk of hemispheric stroke in medically treated patients with severe ICA stenosis was reduced in the presence of collaterals: 27.8% to 11.3% (P=0.005). Similar reductions were observed for hemispheric TIA (36.1% versus 19.1%; P=0.008) and disabling or fatal strokes (13.3% versus 6.3%; P=0.11). For surgically treated patients, the perioperative risk of hemispheric stroke was 1.1% in the presence of collaterals versus 4. 9% when absent. The 2-year stroke risks for surgical patients with and without collaterals were 5.9% versus 8.4%, respectively. Neither comparison in the surgical group was statistically significant. The observed reductions were independent of the degree of ICA stenosis and other vascular risk factors. CONCLUSIONS: Collaterals are associated with a lower risk of hemispheric stroke and TIA, both long term and perioperatively. Angiographic identification of collaterals assists in identifying patients with severe ICA stenosis at lower risk of stroke and TIA.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".