Larger A1/M1 Diameter Ratio Predicts Embolic Anterior Cerebral Artery Territorial Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: In contrast to middle cerebral artery territory strokes, anterior cerebral artery strokes (ACAS) occur rarely. The low frequency of ACAS, in relation to middle cerebral artery territory strokes, may be explained by differences in ACA and middle cerebral artery anatomy influencing their respective flow-directed embolism rates. We aimed to determine whether variability in ACA anatomy, and in particular A1 segment diameter, is associated with embolic ACAS. METHODS: Consecutive patients admitted to Boston Medical Center with embolic ACAS were reviewed. Ipsilateral and contralateral A1 diameters, M1 diameters, and terminal internal carotid artery bifurcation angles were measured from computed tomographic angiography and MRI angiography images. We compared these measurements between cases of ACAS and consecutive cases of embolic middle cerebral artery territory strokes. RESULTS: The study comprised 55 individuals (27 ACAS, 28 middle cerebral artery territory strokes) with mean age of 69 years. In multivariate regression analysis, larger ipsilateral A1 diameters (odds ratio per 1 mm increment: 8.5; 95% confidence interval, 1.4-53.3) and ipsilateral A1/M1 diameter ratio (odds ratio per 10% increment: 1.8; 95% confidence interval, 1.2-2.9) were associated with ACAS, whereas larger ipsilateral M1 diameters was protective for ACAS (odds ratio per 1 mm increment: 0.8; 95% confidence interval, 0.0-0.9). CONCLUSIONS: Larger ipsilateral A1 diameters and A1/M1 diameter ratio are associated with embolic ACAS. These findings suggest that A1 diameters and M1 diameters are important in determining the path of emboli that reach the terminal internal carotid artery.
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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 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".