Abstract WP84: Hemispheric White Matter Sparing and Neurological Outcome After Recanalization Treatment in ESCAPE Trial
Bibliographic record
Abstract
Background: Ischemic tolerance differs between white matter (WM) and grey matter. Timely reperfusion may result in preferential sparing of WM. We investigated if the degree of WM sparing after recanalization therapy has an impact on early neurological recovery and functional outcomes. Methods: Patients from ESCAPE trial were included if they had follow-up MRI brain. WM involvement was scored on a semiquantitative scale which divides hemispheric WM into twelve regions (Figure), adding one point for each area involved. Using receiver operating characteristics analysis and Youden J, optimum cutoff value of WM score for favorable outcome (90-day mRS≤2) was calculated and then used to classify patients into WM spared vs involved groups. Early neurological recovery was compared using difference in median 24-h NIHSS. Multivariable logistic regression was used to test the association between the WM score and outcome. Results: Among 108 patients, median WM score was 2 (IQR 1-4) in EVT (endovascular thrombectomy) arm (n= 70) and 3 (IQR 1-6) in control arm (n= 38). The threshold of ≤2 (WM spared) had sensitivity 69.1 and specificity of 69.8% for favorable outcome (AUC 0.74; 95% CI, 0.65 to 0.82; P<0.001). WM sparing was independently associated with favorable outcome after adjusting for age, baseline NIHSS, EVT use, cortical involvement, infarct volume and symptomatic hemorrhage (adjusted OR 5.34; 95% CI, 1.62-17.9, P=0.006). These patients had better neurological recovery (median 24-h NIHSS 4 in WMspared vs 11 in WMinvolved group; P <0.001) and lower infarct volumes (8 ml vs 47 ml; P <0.001). Patient with WMspared also had numerically lower incidence of malignant brain edema (0 vs 5.6%; P=0.24), intracerebral hemorrhage (symptomatic 0 vs 7.4%; P=0.12), and mortality (3.7 vs 11.1%; P=0.27) than WM involved group. Conclusion: White matter sparing was an independent predictor of early neurological recovery, and functional outcomes in the ESCAPE trial.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".