Association of Motoric Cognitive Risk Syndrome and High C-Reactive Protein Serum Levels With Incident Major Neurocognitive Disorder: Results From the Quebec NuAge Cohort
Bibliographic record
Abstract
Both motoric cognitive risk (MCR) syndrome and C-reactive protein (CRP) serum levels have been separately associated with increased risk of incident major neurocognitive disorder. The study aims to compare the CRP serum levels of older adults with and without MCR and to examine the associations of MCR and CRP serum levels and their combination with incident major neurocognitive disorder. 915 individuals participating in an older adult's population-based observational cohort study with a 3-year follow-up design were selected. MCR and CRP serum levels were collected at baseline. Incident major neurocognitive disorder was measured at annual follow-up visits using the Modified Mini-Mental State Examination (≤79/100) and simplified instrumental activity daily living scale (<4/4) score values. The prevalence of MCR at baseline assessment was 3.7%. The overall incidence of major neurocognitive disorder was 3.0%. MCR alone (hazard ratio = 25.36 with 95% confidence interval = [6.25-102.95] and p ≤ .001) and MCR with a high CRP serum level (hazard ratio = 5.61, with 95% confidence interval [1.29-24.26] and p = .021) were significantly associated with incident major neurocognitive disorder. MCR is a significant risk factor for predicting major neurocognitive disorder in older adults, while serum CRP levels are not. In addition, serum CRP levels reduce the predictive strength of MCR for major neurocognitive disorder.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".