Circle of Willis Collateral During Temporary Internal Carotid Artery Occlusion I: Observations From Digital Subtraction Angiography
Bibliographic record
Abstract
INTRODUCTION: Impaired collateral circulation can lead to stroke during carotid endarterectomy. Carotid stump pressure (CSP) is used as a surrogate measure of collateral flow. The objective was to determine whether anatomical features obtained from digital subtraction angiography correlate with CSP during temporary internal carotid artery occlusion. The second objective was to use these features in combination to predict CSP. METHODS: Digital subtraction angiographies from 102 patients obtained before endarterectomy were reviewed for anatomical variables including: degree of ipsilateral and contralateral carotid artery stenosis; patency of the anterior communicating artery; presence of cross-flow into ipsilateral middle cerebral artery branches; and size (< or ≥1 mm calibre) of the ipsilateral proximal anterior cerebral (A1), the contralateral A1, and the ipsilateral posterior communicating arteries. At surgery, systemic mean arterial pressure (MAP) and CSP were recorded. Multiple regression analysis was used to assess for anatomical features significantly associated with CSP. A "predicted CSP" equation was applied to 54 subsequent patients and correlated with measured CSP. RESULTS: Variables correlating with CSP included MAP (p=0.001); the presence of severe contralateral carotid stenosis (p=0.002); patency of the anterior communicating artery (p=0.013); and the size of the contralateral A1 segment (p=0.029). Angiographic cross-flow, ipsilateral A1 size, and ipsilateral posterior communicating artery size were not significant. Predicted CSP correlated significantly with measured CSP (p<0.0001; R 2=0.34). CONCLUSIONS: Anatomical features and systemic MAP are associated with carotid stump pressure during internal carotid artery occlusion and account for a significant amount of its variation.
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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 | 0.003 |
| 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 | 0.001 |
| 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".