USE OF DWI-ASPECTS AND CORE VOLUME TO DETERMINE THE MALIGNANT PROFILE IN ACUTE ISCHEMIC STROKE
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Bibliographic record
Abstract
Aim u2013 To clarify the correlation between diffusion-weighted imaging (DWI)-Alberta Stroke Program Early CT Score (ASPECTS) and DWI lesion ischemic core volume (VolDWI) in acute ischemic stroke (AIS) due to large vessel occlusion (LVO) and determine the thresholds for the malignant profile.Methods and Results u2013 DWI-ASPECTS and VolDWI were measured in consecutive AIS patients with anterior LVO. VolDWI was assessed with automated software. Favorable/unfavorable outcome was defined as modified Rankin Scale score 0u20132/5u20136 at 3 months. Malignant profile was defined as optimal DWI-ASPECTS and VolDWI for unfavorable outcome. Of total, 198 patients (111 men, 77u00b113 years old) were enrolled. Median baseline National Institutes of Health Stroke Scale score was 21 (interquartile range 14u201327), median DWI-ASPECTS was 7 (5u20139), and median VolDWI was 55 (6u2013134) mL. Seventy two (36%) patients underwent reperfusion therapy [39 (20%) intravenous thrombolysis, 54 (27%) endovascular treatment, and 21 (11%) combination therapy]. Forty eight (24%) patients had favorable outcomes and 83 (42%) had unfavorable outcomes. There was a significant correlation between DWI-ASPECTS and VolDWI (u03c1=u22120.90, p<0.01). The threshold values for malignant profile on receiver operating characteristic curve analysis for DWI-ASPECTS and VolDWI were 4 [area under the curve (AUC) 0.78, p<0.01; sensitivity 0.71, specificity 0.75] and 71 mL (AUC 0.80, p<0.01; sensitivity 0.76, specificity 0.77), respectively. Conclusions u2013 A significant correlation was found between DWI-ASPECTS and VolDWI. The cut-off values for malignant profile were DWI-ASPECTS 4 and VolDWI 71 mL. DWI-ASPECTS was not an adequate substitute for VolDWI in cases with DWI-ASPECTS u22644.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.022 | 0.012 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.005 | 0.015 |
| Open science | 0.011 | 0.019 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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