A Combined Arterial and Venous Grading Scale to Predict Outcome in Anterior Circulation Ischemic Stroke
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Bibliographic record
Abstract
OBJECTIVE: Prognostic evaluation based on cortical vein score difference in stroke (PRECISE) score, a novel venous grading scale better predicted stroke outcomes. Henceforth, we aimed to describe and determine if a physiologically relevant combined arterial and venous grading scale (CRISP grading scale) is accurate in determining 90-day stroke outcomes in patients with proximal arterial occlusion in the anterior circulation. METHODS: Data are from the Keimyung Stroke Registry. Consecutive patients with M1 middle cerebral artery (MCA) or terminal internal carotid artery (ICA) occlusion on CT-angiography (CTA) from May-2004 to July-2008 were included. The affected hemisphere 'four veins composite score' and 'arterial collaterals' were each graded 'good' and 'poor'. On the combined scale, a 'good' grade represented a 'good' score on both scales and a 'poor' grade represented a 'poor' score on both scales. The 'other two' combinations were graded 'intermediate.' RESULTS: Eighty-one patients were included in the study. Dummy variable regression analysis demonstrated that poor outcome was commonly seen in the group with poor arterial and venous grades [OR(95%CI); 48 (8.24, 279.598); P < 0.00001] as opposed to poor arterial collaterals alone [OR(95%CI); 9.6(1.483,62.162); P = 0.018]. In multivariate analysis the CRISP grade [OR(95%CI); 2.638(1.192, 6.039), P = 0.017] and National Institutes of Health Stroke Scale [OR(95%CI);1.230(1.085, 1.395),P = 0.001(per unit increase)] emerged as the independent predictors of poor outcome (modified Rankin Scale >2) when adjusted for other imaging predictors of outcome. CONCLUSION: CRISP grading was precise in predicting stroke outcomes when compared to individual imaging scales including arterial collateral grading, PRECISE score and CTA-SI ASPECTS in patients with proximal arterial occlusion in the anterior circulation.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it