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Record W3136353204 · doi:10.1161/str.52.suppl_1.p359

Abstract P359: Secondary Thalamic Atrophy Related to Brain Infarction is Associated With Post-Stroke Cognitive Impairment

2021· article· en· W3136353204 on OpenAlexaffabout
Jieli Geng, Kie Honjo, Fuqiang Gao, Joel Ramirez, Melissa F. Holmes, Sabrina Adamo, Miracle Ozzoude, Christopher J.M. Scott, Maged Goubran, David L. Nyenhuis, Sandra E. Black

Bibliographic record

VenueStroke · 2021
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsOntario Brain InstituteSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineAtrophyThalamusMontreal Cognitive AssessmentStroke (engine)Brain sizeCardiologyInfarctionCognitionInternal medicineMagnetic resonance imagingNeuroscienceCognitive impairmentRadiologyPsychologyPsychiatryMyocardial infarction

Abstract

fetched live from OpenAlex

Background: The thalamus is globally connected to many brain regions. Previous work highlights thalamic contributions to multiple cognitive functions, but few studies have measured thalamic volume changes or explored correlates of such changes with post-stroke cognition. Hence this study investigates possible associations of thalamic volumes with post-stroke cognitive functions. Methods: Participants with brain infarcts (6-42 months) underwent volumetric brain MRI and cognitive testing, including the Montreal Cognitive Assessment (MoCA). Focal Brain infarcts and thalami were traced manually. If the patient had bilateral infarcts, the side of the primary infarct volume defined the hemisphere involved. Brain parcellation and volumetrics used our comprehensive semi-automatic brain region and vascular lesion extraction pipeline (Ramirez, Neuroimage, 2011). MRI in 24 age and gender-matched healthy people provided normal comparative thalamic volumes. Thalamic atrophy was defined by percent thalamic volume loss in the stroke hemisphere compared to the other side. Spearman correlation assessed relationships between thalamic and infarct volumes and MoCA scores. Logistic regression analysis assessed whether thalamic atrophy correlated with MoCA score. Results: Thalami volumes ipsilateral to the infarct in stroke patients (n=55) were smaller than left (4.4 ± 1.4 vs. 5.4 ± 0.8 cc, p = 0.012) and right (4.4 ± 1.4 vs. 5.3 ± 0.7 cc, p = 0.024) thalamic volumes in the controls. Thalamic volumes were inversely correlated with ipsilateral infarct volumes (r = -0.384, p = 0.004). After controlling for head-size and brain atrophy, infarct volume independently correlated with ipsilateral thalamic volume s (β= -0.068, P=0.026), and only frontal infarcts (β = 2.300, p = 0.021) independently contributed to > 15% ipsilateral thalamic atrophy. Left thalamic atrophy of > 10% correlated significantly with poorer MoCA performance (β = 3.139, p = 0.023), after controlling for demographics and infarct volumes. Conclusions: Our results suggest that remote effects of infarction on ipsilateral thalamic volume, presumably related to disrupted thalamic-cortical interconnectivity, is associated with a commonly used metric of post-stroke cognitive impairment.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.013
GPT teacher head0.247
Teacher spread0.234 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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