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Record W4310239156 · doi:10.1161/jaha.122.027295

Effects of Carotid Artery Stiffness on Cerebral Small‐Vessel Disease and Cognition

2022· article· en· W4310239156 on OpenAlexaboutno aff
Caroline Robert, Lieng Hsi Ling, Eugene S.J. Tan, Bibek Gyanwali, Narayanaswamy Venketasubramanian, Shir Lynn Lim, Lingli Gong, Josephine Lunaria Berboso, Mark Richards, Christopher Chen, Saima Hilal

Bibliographic record

VenueJournal of the American Heart Association · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsnot available
FundersNational Medical Research CouncilMedical Research CouncilNational University Health System
KeywordsMedicineCardiologyCarotid arteriesInternal medicineDiseaseCognitionArterial stiffnessBlood pressurePsychiatry

Abstract

Background Carotid artery stiffness is associated with cognitive impairment and dementia, but the underlying mechanisms remain unknown. We examined the associations of carotid artery stiffness with cerebral small‐vessel disease markers, cognition, and dementia subtypes in a memory clinic cohort. Methods and Results A total of 272 participants underwent carotid ultrasonography, 3 Tesla brain magnetic resonance imaging, and neuropsychological assessment. Carotid ultrasonography was used to assess β‐index, pressure‐strain elastic modulus, and pulse‐wave velocity‐β. Brain magnetic resonance images were graded for cerebral small‐vessel disease markers, including white matter hyperintensities, lacunes, and cerebral microbleeds. Participants were classified as having no cognitive impairment, cognitive impairment and no dementia, or dementia subtyped as Alzheimer disease and vascular dementia. Cognition was assessed using National Institute of Neurological Disorders and Stroke–Canadian Stroke Network harmonization battery. After adjusting for age, sex, cardiovascular risk factors, and diseases, multivariable models showed that β‐index ( β =0.69; P =0.002), elastic modulus ( β =0.78; P <0.001), and pulse‐wave velocity‐β ( β =0.80; P <0.001) were associated with white matter hyperintensities, and elastic modulus (odds ratio [OR], 1.39 [95% CI, 1.04–1.85]) and pulse‐wave velocity‐β (OR, 1.47 [95% CI, 1.10–1.98]) were independently associated with lacunes. Similarly, β‐index (OR, 2.04 [95% CI, 1.14–4.13]), elastic modulus (OR, 2.22 [95% CI, 1.25–4.42]), and pulse‐wave velocity‐β (OR, 2.50 [95% CI, 1.36–5.18]) were independently associated with vascular dementia. Carotid stiffness measures were independently associated with worse performance in global cognition, visuomotor speed, visuospatial function, and executive function. These associations became largely nonsignificant after further adjusting for cerebral small‐vessel disease markers. Conclusions In memory clinic patients, carotid artery stiffness was associated with white matter hyperintensities and lacunes, impairment in global and domain‐specific cognition, and causative subtypes of dementia, particularly vascular. The effects of carotid stiffness on cognition were not independent of, and were partially mediated by, cerebral small‐vessel disease.

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: about_only · design weight: 3321.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: empirical
about Canada: no
confidence: high

Clinical cohort study of carotid artery stiffness, small-vessel disease and cognition.

GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high

It examines carotid stiffness and dementia outcomes in patients, not research practice.

Grok 4.5OUT
genre: empirical
about Canada: no
confidence: high

Clinical cohort study linking carotid stiffness to cognition and dementia, not research practice.

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)0.005
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 score0.009
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.008
GPT teacher head0.254
Teacher spread0.246 · 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

Citations35
Published2022
Admission routes1
Has abstractyes

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