Poor Collateral Circulation Assessed by Multiphase Computed Tomographic Angiography Predicts Malignant Middle Cerebral Artery Evolution After Reperfusion Therapies
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Collateral circulation (CC) has been associated with recanalization, infarct volume, and clinical outcome in patients undergoing acute reperfusion therapies. However, its relationship with the development to malignant middle cerebral artery infarction (mMCAi) has not been evaluated. Our aim was to determine the impact of CC using multiphase computed tomographic angiography (during the acute stroke phase in the prediction of mMCAi. METHODS: Patients with consecutive acute stroke with <4.5 hours who were evaluated for reperfusion therapies and presented with an M1-MCA or terminal internal carotid artery occlusion by CTA were included. CC was evaluated on 6 grades by multiphase CTA according to the University of Calgary CC Scale; CC status was defined as poor (grades, 0-3) or good (grades, 4-5). The mMCAi was defined according to clinical and radiological criteria. Recanalization was assessed with transcranial Doppler at 24 hours and final Thrombolysis in Brain Ischemia score≥2b in patients undergoing endovascular reperfusion treatment. RESULTS: Eighty-two patients were included. Mean age was 65.1±13.83 years, median baseline National Institutes of Health Stroke Scale score was 18 (interquartile range, 13-20), and 67.9% M1 and 32.1% terminal internal carotid artery occlusions. Fifty-three patients received endovascular reperfusion treatment. Fifteen patients developed mMCAi. In the univariate analysis, patients with mMCAi had lower CC scores (2.29 versus 3.71; P=0.001). Endovascular reperfusion treatment was associated with lower rate of mMCAi development than only intravenous reperfusion treatment (9.4% versus 29.6%; P=0.028). Patients with poor CC had higher risk of developing mMCAi (13% versus 2%; P=0.001). On the multivariate analysis adjusted by age, vessel occlusion, baseline National Institutes of Health Stroke Scale, and recanalization, the presence of poor CC by multiphase CTA was the only independent predictor of mMCAi (P=0.048; odds ratio, 9.72; 95% confidence interval, 1.387-92.53). CONCLUSIONS: CC assessment by multiphase CTA independently predicts malignant MCA infarction progression. In patients with persistent occlusion after reperfusion therapies, the presence of poor CC may improve the early mMCAi detection and management.
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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 | 0.001 | 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) | 0.002 | 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".