Influence of Infarct Morphology and Patterns on Cognitive Outcomes After Endovascular Thrombectomy
Bibliographic record
Abstract
BACKGROUND: To assess the association of qualitative and quantitative infarct characteristics and 3 cognitive outcome tests, namely the Montreal Cognitive Assessment (MOCA) for mild cognitive impairment, the Boston Naming Test for visual confrontation naming, and the Sunnybrook Neglect Assessment Procedure for neglect, in large vessel occlusion stroke. METHODS: Secondary observational cohort study using data from the randomized-controlled ESCAPE-NA1 trial (Safety and Efficacy of Nerinetide in Subjects Undergoing Endovascular Thrombectomy for Stroke), in which patients with large vessel occlusion undergoing endovascular treatment were randomized to receive either intravenous Nerinetide or placebo. MOCA, Sunnybrook Neglect Assessment Procedure, and 15-item Boston Naming Test were obtained at 90 days. Total infarct volume, gray matter, and white matter infarct volumes were manually measured on 24-hour follow-up imaging. Infarcts were also visually classified as either involving the gray matter only or both the gray and white matter and scattered versus territorial. Associations of infarct variables and cognitive outcomes were analyzed using multivariable ordinal or binary logistic regression models. RESULTS: Of 1105 patients enrolled in ESCAPE-NA1, 1026 patients with visible infarcts on 24-hour follow-up imaging were included. MOCA and Sunnybrook Neglect Assessment Procedure were available for 706 (68.8%) patients and the 15-item Boston Naming Test was available for 682 (66.5%) patients. Total infarct volume was associated with worse MOCA scores (adjusted common odds ratio per 10 mL increase, 1.05 [95% CI, 1.04-1.06]). After adjusting for baseline variables and total infarct volume, mixed gray and white matter involvement (versus gray matter-only adjusted common odds ratio, 1.92 [95% CI, 1.37-2.69]), white matter infarct volume (adjusted common odds ratio per 10 mL increase 1.36 [95% CI, 1.18-1.58]) and territorial (versus scattered) infarct pattern (adjusted common odds ratio, 1.65 [95% CI, 1.15-2.38]) were associated with worse MOCA scores. Results for Sunnybrook Neglect Assessment Procedure and 15-item Boston Naming Test were similar, except for the territorial infarct pattern, which did not reach statistical significance in multivariable analysis. CONCLUSIONS: Besides total infarct volume, infarcts that involve the white matter and that show a territorial distribution were associated with worse cognitive outcomes, even after adjusting for total infarct volume.
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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 | 0.001 | 0.007 |
| 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 | 0.000 |
| 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".