Motoric cognitive risk syndrome and incident dementia in older adults from the Québec NuAge cohort
Bibliographic record
Abstract
BACKGROUND: The co-occurrence of slow walking speed and subjective cognitive complaint (SCC) in non-demented individuals defines motoric cognitive risk syndrome (MCR), which is a pre-dementia stage. There is no information on the association between MCR and incident dementia in Québec's older population. OBJECTIVE: The study aims to examine the association of MCR and its individual components (i.e. SCC and slow walking speed) with incident dementia in community-dwelling older adults living in the province of Québec (Canada). DESIGN: Québec older people population-based observational cohort study with 3 years of follow-up. SETTING: Community dwellings. SUBJECTS: A subset of participants (n = 1,098) in 'Nutrition as a determinant of successful aging: The Québec longitudinal study' (NuAge). METHODS: At baseline, participants with MCR were identified. Incident dementia was measured at annual follow-up visits using the Modified Mini-Mental State (≤79/100) test and Instrumental Activity Daily Living scale (≤6/8) score values. RESULTS: The prevalence of MCR was 4.2% at baseline and the overall incidence of dementia was 3.6%. MCR (Hazard Ratio (HR) = 5.18, with 95% confidence interval (CI) = [2.43-11.03] and P ≤ 0.001) and SCC alone (HR = 2.54, with 95% CI = [1.33-4.85] and P = 0.005) were associated with incident dementia, but slow walking speed was not (HR = 0.81, with 95%CI = [0.25-2.63] and P = 0.736). CONCLUSIONS: MCR and SCC are associated with incident dementia in NuAge study participants.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".