Extent of Hypoattenuation on CT Angiography Source Images Predicts Functional Outcome in Patients With Basilar Artery Occlusion
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Quantification of early ischemic changes (EIC) may predict functional outcome in patients with basilar artery occlusion (BAO). We tested the validity of a novel CT score, the posterior circulation Acute Stroke Prognosis Early CT score (pc-ASPECTS). METHODS: Pc-ASPECTS allots the posterior circulation 10 points. Two points each are subtracted for EIC in midbrain or pons and 1 point each for EIC in left or right thalamus, cerebellum or PCA-territory, respectively. We studied 2 different populations: (1) patients with suspected vertebrobasilar ischemia and (2) patients with BAO. We applied pc-ASPECTS to noncontrast CT (NCCT), CT angiography source images (CTASI), and follow-up image by 3-reader consensus. We calculated sensitivity for ischemic changes and analyzed the predictivity of pc-ASPECTS for independent (modified Rankin Scale [mRS] score </=2) and favorable (mRS score </=3) outcome. RESULTS: Of 130 patients with suspected vertebrobasilar ischemia, 72% (94) had posterior circulation stroke, 8% (10) transient ischemic attack, and 20% (26) nonischemic etiology. Sensitivity for ischemic changes was improved with CTASI compared to NCCT (65% [95% CI, 57% to 73%] versus 46% [95% CI, 37% to 55%], respectively). Pc-ASPECTS score on CTASI but not NCCT predicted functional independence (OR 1.58; P=0.005 versus 1.22; P=0.42, respectively). Of 46 patients with BAO, 52% (12/23) with CTASI pc-ASPECTS score >/=8 but only 4% (1/23) with a score <8 had favorable functional outcome (RR 12.1; 95% CI, 1.7 to 84.9). This difference was consistent in 21 patients with angiographic recanalization (RR 7.7; 95% CI, 1.1 to 52.1). CONCLUSIONS: The CTASI pc-ASPECTS score may identify BAO patients unlikely to have a favorable outcome despite recanalization.
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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) | 0.001 | 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".