Motoric Cognitive Risk Syndrome as a Predictor of Adverse Health Outcomes: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".