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Record W2144958050 · doi:10.1136/jnnp.2009.201665

Cortical and frontal atrophy are associated with cognitive impairment in age-related confluent white-matter lesion

2010· article· en· W2144958050 on OpenAlexaboutno aff
Vincent Mok, Kelvin Wong, Yunyun Xiong, Adrian Wong, R. Schmidt, Chiu‐Wing Winnie Chu, Xintao Hu, Eric Yim Lung Leung, Sheng Chen, Yuanfeng Chen, Wai Kwong Tang, Xia Chen, Carine Ho, Ka Sing Wong, Stephen T.C. Wong

Bibliographic record

VenueJournal of Neurology Neurosurgery & Psychiatry · 2010
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsHyperintensityCardiologyMontreal Cognitive AssessmentAtrophyDementiaPsychologyCognitionClinical Dementia RatingInternal medicineWhite matterStroke (engine)Cognitive declineMedicineAudiologyCognitive impairmentNeuroscienceMagnetic resonance imagingDiseaseRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Although age-related confluent white-matter lesion (WML) is an important substrate for cognitive impairment, the mechanisms whereby WML induces cognitive impairment are uncertain. The authors investigated cognitive predictors in patients with confluent WML. METHODS: Among 100 patients with ischaemic stroke with confluent WML on MRI, the authors assessed executive function and global cognition by the Mattis Dementia Rating Scale--Initiation/Perseveration Subscale (MDRS I/P) and Mini-Mental State Examination (MMSE), respectively. All volumetric measures were corrected for intracranial volume. The authors investigated the association between basic demography, vascular risk factors, APOE status, WML volume, infarct measures (volume, number, location), microbleed number, atrophy measures (global, central, regional) and cognitive performance. The authors also performed Pittsburgh Compound B (PIB) imaging among seven cognitive impaired patients with stroke. RESULTS: WML was no longer related to cognitive performance after adding atrophy into regression equations. Multivariate regression models showed that cortical grey matter volume independently accounted for performance on both the MDRS I/P (β=0.241, p=0.045) and MMSE (β=0.243, p=0.032). Models examining frontal subregions revealed that volumes of both left (β=0.424, p<0.001) and right (β=0.219, p=0.045) lateral frontal orbital gyri predicted MDRS I/P, whereas education (β=0.385, p<0.001) and left lateral frontal orbital gyrus (β=0.222, p=0.037) predicted MMSE. Volumes of WML and cognitively relevant brain regions were significantly associated. Seven patients with PIB imaging showed no uptake pattern typical of Alzheimer's disease, suggesting a predominantly vascular aetiology for the cognitive impairment and brain changes in these patients. CONCLUSIONS: Cognitive impairment in patients with confluent WML is mediated by global and frontal cortical atrophy.

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)0.003
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.270
Teacher spread0.260 · 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

Citations59
Published2010
Admission routes1
Has abstractyes

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