Abstract 2925: DWI-ASPECTS As A Predictor Of Neurological Recovery In Acute Stroke Patients With The Middle Cerebral Artery Occlusion Treated With IV t-PA.
Bibliographic record
Abstract
Background and Purpose: Diffusion-weighted imaging-Alberta Stroke Programme Early CT Score (DWI-ASPECTS) has been associated with short-term and long-term neurological recovery and outcome in acute stroke patients treated with intravenous tissue plasminogen activator (IV-tPA). However, previous reports did not analyze the DW-ASPECTS based on the presence of major arterial occlusion. We investigated whether initial DWI-ASPECTS can predict the short-term neurological recovery in acute stroke patients with the middle cerebral artery occlusion (MCAO) treated with IV t-PA. Methods: Consecutive acute stroke patients with MCAO treated with IV t-PA within 3 hours of onset were enrolled from 2005 October to 2011 May. All patients were examined using DWI and magnetic resonance angiography on admission. Only patients with horizontal MCAO were included. Neurological deficits were assessed using National Institutes of Health Stroke Scale (NIHSS) score on admission and day 7. On day 7, dramatic recovery (DR) was defined as a ≥10 point reduction or a total NIHSS score of 0 or 1. Good recovery (GR) was a ≥4 point reduction, excluding DR. Worsening was a ≥4 point increase. Results: Seventy-one patients (median age [quartiles]; 77 [70-83], male; 44 [62%]) were enrolled into the study. The median NIHSS score was 18 (12-22). The median DWI-ASPECTS was 4 (6-9). Median DWI-ASPECTS was 7 (6-9) in 27 patients with DR group, 5 (4-9) in 13 with GR group, and 3 (2-6) in 17 with worsening (p<0.001). Median DWI-ASPECTS was 4 (3-6) in 4 (6%) patients with type2-parencymal hematoma within 7 days. Using ROC curve, the optimal cut-off DWI-ASPECTS to differentiate DR group from others was >5 (sensitivity of 85% and specificity of 57%, area under curve [AUC] 0.692, p=0.007), and that for worsening group was <4 (sensitivity of 96% and specificity of 59%, AUC 0.785, p<0.001). Multivariate regression analysis demonstrated that initial DWI-ASPECTS of >5 was significantly associated with DR (OR 9.75, 95%CI 1.41-67.67, p=0.021), and <4 with worsening (OR 15.94, 95%CI 4.01-63.25, p<0.001). Conclusion: DWI-ASPECTS can predict the short-term outcome in acute stroke patients with MCAO treated with IV-tPA.
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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 | 0.002 |
| 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) | 0.001 | 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".