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Record W4406202767 · doi:10.1212/wnl.0000000000210246

Covert Vascular Brain Injury and Cognitive Dysfunction Among Chinese Adults Living in Canada and China

2025· article· en· W4406202767 on OpenAlexaffabout
Calvin Ke, Sonia S. Anand, Eric E. Smith, Karleen Schulze, Alan R. Moody, Scott A. Lear, Paul Poirier, Trevor Dummer, Dipika Desai, Vivekanandan Thayalasuthan, Salim Yusuf, Koon Teo, Andreas Wielgosz, Douglas S. Lee

Bibliographic record

VenueNeurology · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of OttawaHealth Sciences CentreSunnybrook Health Science CentreUniversity of British ColumbiaSimon Fraser UniversityUniversity of CalgaryUniversity of TorontoHamilton Health SciencesMcMaster UniversityUniversité LavalPopulation Health Research Institute
Fundersnot available
KeywordsChinaCovertCognitionMedicineCognitive impairmentMedical emergencyPsychologyGerontologyPsychiatryPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: It is unclear whether variation in covert cerebrovascular disease prevalence is attributable to ethnic differences or to other factors. We aimed to examine the associations of country of residence with covert vascular brain injury (VBI) and cognitive dysfunction among Chinese adults residing in Canada and China. METHODS: This was a multisite cross-sectional study of Chinese adults aged 40-80 years in the Canadian Alliance for Healthy Hearts and Healthy Minds (CAHHM; January 1, 2014, to December 31, 2018) and Prospective Urban Rural Epidemiological-Mind (PURE-MIND; November 1, 2010, to July 31, 2015) cohorts living in Canada and China. The exposure was country of residence. The co-primary outcomes were covert VBI (defined as MRI findings of high white matter hyperintensities or covert brain infarct) and cognitive dysfunction (defined as a Montreal Cognitive Assessment [MoCA] score <26). We used generalized linear models to describe the association between country of residence and each outcome, adjusting for selected covariates. RESULTS: We included 884 adults living in Canada (mean age 57.3 years, 55.4% female) and 473 living in China (mean age 56.8 years, 60.3% female). Participants in Canada had a lower prevalence of covert VBI (age 65-79 years: male, 11.5%; female, 12.2%) than those living in China (age 65-79 years: male, 62.9%; female, 52.1%). Prevalence of MoCA score <26 was lower among men and women in Canada (age 65-79 years: 40.2% and 30.0%, respectively) than among men and women in China (age 65-79 years: 74.3% and 79.2%). Living in China was associated with a 6-fold increase in the odds of covert VBI (5.85, 4.06-8.45), which remained significant after covariate adjustment. Living in China was associated with a 7-fold increase in the odds of MoCA score <26 (6.98, 5.38-9.04), which was no longer significant after covariate adjustment. DISCUSSION: Despite sharing a similar ethnicity, the prevalence of covert VBI and cognitive dysfunction varied substantially by country of residence. Disparities in cognitive dysfunction were completely explained by differences in education and traditional cerebrovascular risk factors, whereas disparities in covert VBI prevalence were only partially explained by differences in such factors, suggesting a role for other environmental factors.

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 score0.082
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.002
GPT teacher head0.204
Teacher spread0.202 · 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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