Anterior Temporal Artery Sign in CT Angiography Predicts Reduced Fatal Brain Edema and Mortality in Acute M1 Middle Cerebral Artery Occlusions
Bibliographic record
Abstract
BACKGROUND: Mortality in acute ischemic middle cerebral artery (MCA) stroke ranges from 5% to 45%. We identify a vascular imaging sign, presence of "prominent anterior temporal artery" on computed tomography (CT) angiography (CTA) and investigate whether it predicts mortality in acute M1-MCA occlusions. METHODS: One hundred and two patients with acute M1-MCA occlusions from 2003-to 2007 were included in the study. A prominent anterior temporal artery arising from proximal M1 MCA was identified by two readers blinded to clinical outcome. Primary clinical outcome was survival (modified Rankin Scale [mRS] 0-5) at 3 months. RESULTS: An anterior temporal artery arising from M1 MCA was present in 20/102 (20%). Eighteen of 20 (90%) patients with this sign survived at 3 months (mRS 0-5) when compared to 66/82 (80.4%) patients without the sign (odds ratio 2.2 CI(95) .5-10.4). The sign has a sensitivity of 21% (CI(95) .13-.25) but specificity of 89% (CI(95) .64-.98) in predicting survival at 3 months. Positive predictive value was 90% with likelihood ratio of 1.9 (CI(95) .9-7.6). CONCLUSION: Presence of prominent anterior temporal artery in M1-MCA occlusions on CTA identifies a group of patients with reduced case fatality. The mechanism is likely related to a reduced chance of malignant cerebral edema.
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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 | 0.005 |
| 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 | 0.001 | 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".