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Record W4410347682 · doi:10.1161/strokeaha.124.048900

MRI Predictors of Cognitive Function After Lacunar Infarction

2025· article· en· W4410347682 on OpenAlexaffabout
Sara Hassani, Deborah K. Attix, Timothy J. Amrhein, Shakthi Unnithan, Hussein R. Al‐Khalidi, Cheryl Bushnell, Larry B. Goldstein, Nada El Husseini

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineMontreal Cognitive AssessmentMagnetic resonance imagingLacunar strokeCognitionAtrophyStroke (engine)CardiologyInternal medicinePhysical therapyPhysical medicine and rehabilitationCognitive impairmentRadiologyPsychiatryIschemiaIschemic stroke

Abstract

fetched live from OpenAlex

BACKGROUND: Poststroke cognitive impairment is associated with disability and decreased quality of life. We assessed whether individual or collective magnetic resonance imaging (MRI) biomarkers can aid in predicting cognitive impairment after lacunar infarction (LACI). METHODS: We conducted a retrospective analysis of data from the American Stroke Association Bugher Small Vessel Study, which included 134 patients within 2 years of an acute LACI, enrolled between 2007 and 2012 at 4 North Carolina hospitals. MRI brain measures at the time of the stroke included as follows: 1, total number of LACIs (index LACI and nonindex radiographic lacunes); 2, size of the largest lacune; 3, ventricular size; 4, cerebral atrophy; 5, radiographic locations (supratentorial, infratentorial, or both); and 6, white matter disease (WMD) extent. WMD extent, cerebral atrophy, and ventricular size were graded using the CHS (Cardiovascular Health Study) scores. The primary outcomes were as follows: 1, total score on Short-Form Montreal Cognitive Assessment to assess global cognition; and 2, time to complete TRAIL Making Test Part B (TMT-B) to evaluate executive function. Regression analyses were used to assess the association between the 6 MRI measures and cognitive function adjusting for demographic and clinical variables. RESULTS: One hundred thirty-four participants completed Short-Form Montreal Cognitive Assessment testing and 100 completed TMT-B at a mean of 76.5 (SD, 172.7) days from the index LACI. There were no associations between MRI characteristics and Short-Form Montreal Cognitive Assessment. On univariable analyses, cerebral atrophy (β=35 [95% CI, 14.17–55.83]; P =0.0010), ventricular size (β=40.1 [95% CI, 22.24–57.96]; P <0.0001), and WMD extent (β=55.25 [95% CI, 38.52–71.98]; P <0.0001) were each associated with TMT-B time. Extent of WMD was the only MRI measure associated with TMT-B time (β=37.74 [95% CI, 19.04–56.44]; P <0.0001). In adjusted models after performing variable selection, the extent of WMD remained the only MRI measure associated with TMT-B time. CONCLUSIONS: Among the assessed MRI measures, only the extent of WMD was independently associated with executive function after LACI.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.286
Teacher spread0.279 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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