Abstract 2261: Presence of Large Deep White Matter Lesion May Predict Futile Recanalization in Endovascular Therapy for Acute Ischemic Stroke
Bibliographic record
Abstract
Background: A subset of stroke patients treated with endovascular recanalization therapy suffers poor outcome despite good arterial recanalization. The aim of this study is to identify whether large ischemic lesion in deep white matter (DWM) on diffusion weighted imaging (DWI) prior to therapy predicts futile recanalization. Method: Consecutive acute stroke patients with anterior circulation ischemia whose artery had been recanalized at Thrombolysis in Myocardial Infarct (TIMI) flow grade 2 or 3 following endovascular therapy were included. All patients underwent CT and MRI before endovascular therapy. We defined large DWI - DWM lesion if DWI showed the hyperintense lesion in the DWM which mostly extended between anterior and posterior horn of the lateral ventricle. We identified Alberta Stroke Program Early CT Scores (ASPECTS) of CT and DWI, and volumes measured on initial DWI and mean transit time of perfusion weighted images. We assessed the prevalence of TIMI grade 3 recanalization and parenchymal hemorrhage type 2, and final ischemic lesion volume after endovascular therapy. Stroke severity was assessed by the National Institutes of Health Stroke Scale (NIHSS) score. Futile recanalization was defined as a 30-day modified Rankin Scale score 3 to 6 despite recanalization at TIMI grade 2 or 3. Univariate and multivariate regression analyses were performed to identify predictors of futile recanalization. Results: Partial or complete recanalization (TIMI grade 2 or 3) was observed in 35 of 46 patients (76 %). Of the 35 patients, futile recanalization was observed in 20 patients (57 %). Patients with futile recanalization had older age (median, 74 versus 58 years old, p = 0.053), higher initial NIHSS score (median, 17 versus 9, p = 0.042), pre-treatment large DWI - DWM lesion (45 versus 9 %, p = 0.022), and larger final ischemic lesion volume (median, 37 versus 9 ml, p = 0.003). ASPECTS of CT (median, 9 versus 9, p = 0.527) and DWI (median, 8 versus 8, p = 0.943) and initial ischemic lesion volumes on DWI (median, 21 versus 14 ml, p = 0.230) and on mean transit time (median, 189 versus 192 ml, p = 0.976) did not demonstrate statistically significance between patients with and without futile recanalization. There were also no significant differences between the outcome groups in times from stroke onset to imaging or endovascular therapy. Logistic regression analysis demonstrated that large DWI - DWM lesion was an independent predictor of futile recanalization (OR 10.40, 95 % CI 1.03 to 105.21, p = 0.047). Conclusion: Patients who have large pre-treatment DWI - DWM lesion may be poor candidates for endovascular therapy.
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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 | 0.001 | 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) | 0.003 | 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".