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Record W4396593156 · doi:10.1159/000538314

Motoric Cognitive Risk Syndrome as a Predictor of Adverse Health Outcomes: A Systematic Review and Meta-Analysis

2024· review· en· W4396593156 on OpenAlexaboutno aff
Cheng Huang, Bei Wu, Chen Zhang, Zhuqin Wei, Liming Su, Junwei Zhang, Lina Wang

Bibliographic record

VenueGerontology · 2024
Typereview
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisMedicineCognitionMEDLINEPsychologyPsychiatryInternal medicineBiology

Abstract

fetched live from OpenAlex

INTRODUCTION: Motoric cognitive risk syndrome (MCR) is a newly proposed pre-dementia syndrome characterized by subjective cognitive complaints (SCCs) and slow gait (SG). Increasing evidence links MCR to several adverse health outcomes, but the specific relationship between MCR and the risk of frailty, Alzheimer's disease (AD), and vascular dementia (VaD) remains unclear. Additionally, literature lacks analysis of MCR's components and associated health outcomes, complicating risk identification. This systematic review and meta-analysis aimed to provide a comprehensive overview of MCR's predictive value for adverse health outcomes. METHODS: Relevant cross-sectional, cohort, and longitudinal studies examining the association between MCR and adverse health outcomes were extracted from ten electronic databases. The Newcastle-Ottawa Scale (NOS) and modified NOS were used to assess the risk of bias in studies included in the analysis. Relative ratios (RRs) and 95% confidence intervals (CIs) were pooled for outcomes associated with MCR. RESULTS: Twenty-eight longitudinal or cohort studies and four cross-sectional studies with 1,224,569 participants were included in the final analysis. The risk of bias in all included studies was rated as low or moderate. Pooled analysis of RR indicated that MCR had a greater probability of increased the risk of dementia (adjusted RR = 2.02; 95% CI = 1.94-2.11), cognitive impairment (adjusted RR = 1.72; 95% CI = 1.49-1.99), falls (adjusted RR = 1.32; 95% CI = 1.17-1.50), mortality (adjusted RR = 1.66; 95% CI = 1.32-2.10), and hospitalization (adjusted RR = 1.46; 95% CI = 1.16-1.84); MCR had more prominent predictive efficacy for AD (adjusted RR = 2.23; 95% CI = 1.81-2.76) compared to VaD (adjusted RR = 3.78; 95% CI = 0.49-28.95), while excluding analyses from the study that utilized the timed-up-and-go test and one-leg-standing to evaluate gait speed. One study examined the association between MCR and disability (hazard ratios [HR] = 1.69; 95% CI = 1.08-2.02) and frailty (OR = 5.53; 95% CI = 1.46-20.89). SG was a stronger predictor of the risk for dementia and falls than SCC (adjusted RR = 1.22; 95% CI = 1.11-1.34 vs. adjusted RR = 1.19; 95% CI = 1.03-1.38). CONCLUSION: MCR increases the risk of developing any discussed adverse health outcomes, and the predictive value for AD is superior to VaD. Additionally, SG is a stronger predictor of dementia and falls than SCC. Therefore, MCR should be routinely assessed among adults to prevent poor prognosis and provide evidence to support future targeted interventions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.714
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0200.004
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.140
GPT teacher head0.474
Teacher spread0.333 · 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 teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations14
Published2024
Admission routes1
Has abstractyes

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