Differentiating Carotid Terminus Occlusions into Two Distinct Populations Based on Willisian Collateral Status
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The outcomes of acute internal carotid artery (ICA) terminus occlusions are poor. We classified ICA terminus occlusions into 2 groups according to the occlusion pattern of the circle of Willis and hypothesized that clinical outcomes would significantly differ between them. METHODS: Consecutive patients with acute ICA terminus occlusions evaluated by baseline computed tomographic angiography were enrolled. We investigated the occlusion patterns in the circle of Willis, retrospectively classified patients into simple ICA terminus occlusion (STO; with good Willisian collaterals from neighboring cerebral circulation) and complex ICA terminus occlusion (CTO; with one or more of A2 anterior cerebral artery, fetal posterior cerebral artery occlusion, or hypoplastic/absent contralateral A1; or with poor collaterals from anterior communicating artery) groups, and compared their baseline characteristics and outcomes. RESULTS: The STO group (n=58) showed smaller infarct volumes at 72 hours than the CTO group (n=34) (median, 81 mL [interquartile range, 38-192] vs. 414 mL [193-540], P<0.001) and more favorable outcomes (3-month modified Rankin Scale 0-3, 44.8% vs. 8.8%, P<0.001; 3-month mortality, 24.1% vs. 67.6%, P<0.001). In multivariable analyses, STO remained an independent predictor for favorable outcomes (odds ratio 6.1, P=0.010). CONCLUSIONS: Favorable outcomes in STO group suggested that the outcomes of acute ICA terminus occlusions depend on Willisian collateral status. Documenting the subtypes on computed tomographic angiography would help predict patient outcome.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".