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Record W4393055203 · doi:10.1161/strokeaha.123.045825

Influence of Infarct Morphology and Patterns on Cognitive Outcomes After Endovascular Thrombectomy

2024· article· en· W4393055203 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueStroke · 2024
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsCentre Hospitalier de l’Université de MontréalFoothills Medical CentreNoNO (Canada)St. Michael's HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineGrey matterMontreal Cognitive AssessmentStroke (engine)Odds ratioWhite matterOcclusionPlaceboNeglectInternal medicineCognitionCardiologyMagnetic resonance imagingRadiologyCognitive impairmentPsychiatryPathology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.264
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it