Abstract WP67: Factors Associated with Reversed Discrepancy between CT and Diffusion-Weighted Imaging in Hyperacute Ischemic Stroke Patients
Bibliographic record
Abstract
INTRODUCTION: In patients with hyperacute ischemic stroke, diffusion-weighted imaging (DWI) sometimes fails to detect early CT ischemic lesions showing parenchymal hypoattenuation, which is termed Reversed Discrepancy (RD). The aim of the present study was to elucidate the factors associated to the development of RD. Method: One hundred sixty four consecutive patients with hyperacute anterior circulation ischemic stroke were enrolled. All patients underwent both MRI and CT within 3 hours of onset and before treatment. Three stroke neurologists independently and retrospectively evaluated presence of early ischemic changes in each the Alberta Stroke Programme Early CT Score (ASPECTS) region. Presence of RD was defined when the early ischemic change detected on CT was not detected on DWI. Patients’ baseline characteristics, ASPECTS on CT, ASPECTS on DWI, and modified Rankin Scale (mRS) 3 months after onset were compared between patients with RD (RD group) and without RD regions (non-RD group). Results: RD was found in 40 (32%) patients (mean age 78.7 years; 50 % men); it was located in the basal ganglia (n=23), the cortex (n=27), and the basal ganglia plus the cortex (n=10). RD group was older (78.7±9.6 vs. 74.1±12.1 years, p=0.03), had a higher NIHSS score on admission (median, 22 vs. 11, p<0.01), a higher rate of atrial fibrillation (75% vs. 42%, p<0.01), a higher rate of ICA/MCA proximal occlusion (55% vs. 28%, p<0.01), had lower grade of ASPECTS either on CT (median 5 vs. 10, p<0.01) or on DWI (7 vs. 9, p<0.01) than non-RD group. Multivariate logistic regression analysis demonstrated that atrial fibrillation was an independent predictor of the presence of RD (odds ratio 2.47; 95% C.I. 1.05-6.12). RD group had less frequently good outcome (mRS 0-1 after 3 months) than non-RD group (15% vs. 34%, p=0.03). Conclusions: Atrial fibrillation was related to the presence of RD. Patients with RD had unfavorable outcome.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".