MétaCan
Menu
← Back to cohort
Record W4412756335 · doi:10.1136/bmjopen-2025-104901

Prevalence of mild cognitive impairment among former elite athletes without a history of sport-related concussions compared to the general older population: a protocol for a cross-sectional study with exploratory subgroup analyses

2025· article· en· W4412756335 on OpenAlexaboutno aff
Shuo Luan, Haojie Li, Qing Zhao, Jie Cong, Hairong He, Jiaying Xu, Jingjing Ren, Jinghua Qian

Bibliographic record

VenueBMJ Open · 2025
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
FundersFundamental Research Funds for the Central Universities
KeywordsMedicineAthletesMontreal Cognitive AssessmentGerontologyPopulationCognitionDementiaEpidemiologyBeijingCross-sectional studyPhysical therapySports medicineCognitive impairmentPsychiatryEnvironmental healthChina

Abstract

fetched live from OpenAlex

INTRODUCTION: Epidemiological evidence regarding the impact of elite athletic careers on cognitive trajectories remains contentious. Although consistent physical activity has been associated with long-term brain health, former elite athletes appear to represent a unique population. While past research has established a connection between sport-related concussions (SRCs) and later cognitive decline, less attention has been given to the cognitive function of former athletes who have not experienced SRCs. Therefore, well-structured cross-sectional studies accounting for established dementia risk factors are needed to compare mild cognitive impairment (MCI) prevalence between former elite athletes and the general population. METHODS AND ANALYSIS: This cross-sectional study will be conducted at Beijing Sport University (BSU) in Beijing, China. It is designed as a comparative study, aiming to recruit a sample of around 360 participants aged 65 and above. This sample will comprise 180 former elite athletes without a history of SRCs recruited via the BSU Retirement Welfare Office (the former athlete group), and 180 age-matched individuals from the communities in three districts in Beijing (the comparison group). Participants will complete a comprehensive questionnaire covering sociodemographic information, dementia-related risk factors, current physical activity levels and, for the former athlete group specifically, details of their athletic careers. MCI and instrumental activities of daily living will be assessed using the Montreal Cognitive Assessment, Memtrax continuous recognition test and Lawton Instrumental Activities of Daily Living (IADL) scale. The primary objective is to determine whether former elite athletes without a history of SRCs have a lower MCI prevalence than the general population. The secondary objective is to assess if these former elite athletes have a reduced prevalence of amnestic MCI and impairment in IADL compared with the general population. Additionally, the study aims to explore whether specific career-related characteristics of former athletes, such as the type of sport and contact exposure, are correlated with their cognitive function and IADL abilities in later life as a secondary exploratory component. The study will calculate the crude prevalence ratios (PRs) and adjusted prevalence ratios (aPRs) with 95% CIs using the modified Poisson regression model with robust error variance. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Ethics Committee/Internal Review Board of BSU (approval number: 2024042H). All procedures will adhere to the Helsinki Declaration. The study's findings will be provided to participants as deemed appropriate. The outcomes will be communicated through abstract presentations at national or international conferences/academic seminars, as well as through publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: ChiCTR2400085800.

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)0.017
metaresearch head score (Gemma)0.013
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.017
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.013
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0040.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.236
GPT teacher head0.515
Teacher spread0.278 · 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
GenreProtocol

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueBMJ Open→Same topicTraumatic Brain Injury Research→French-language works237,207→