Multimodal CT: Favorable Outcome Factors in Acute Middle Cerebral Artery Stroke with Large Artery Occlusion
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: We investigated which parameters of multimodal computed tomography (CT) or their combinations might be useful as additional imaging predictors for favorable outcomes in acute stroke patients with large artery occlusion. METHODS: The parameters of multimodal CT, including non-enhanced CT, CT angiography, perfusion CT parameters, CT angiography source image (CTA-SI), and collateral flow, were analyzed in 66 consecutive patients with acute middle cerebral artery stroke with large artery occlusion. For favorable outcomes at the 3-month follow-up, odds ratios of multimodal CT parameters with an optimum predictive cut-off Alberta Stroke Program Early CT Score (ASPECTS) were assessed. RESULTS: Cerebral blood volume (CBV) ASPECTS ≥6, CTA-SI ASPECTS ≥7, and good collateral flow were associated with a favorable outcome. The combination of those parameters had better predictive validity compared to a single parameter only: CBV (p = 0.039), CTA-SI (p = 0.038), and collateral flow (p < 0.001). CONCLUSION: Among the various parameters of multimodal CT, CBV ASPECTS ≥6, CTA-SI ASPECTS ≥7, and good collateral flow might be the most reliable predictors for favorable outcomes in acute stroke patients with large artery occlusion. Moreover, considering these parameters simultaneously might improve the predictive validity of multimodal CT for functional outcome.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it