Motoric cognitive risk syndrome and incident hospitalization in Quebec's older population: Results of the NuAge cohort study
Bibliographic record
Abstract
Background Screening older adults at risk of hospitalization is essential to prevention of this adverse event. Motoric cognitive risk syndrome (MCR) has been associated with incident dementia and falls, which are both risk factors of hospitalization. There is no information on the association of MCR with incident hospitalization in older adults. Objective The study aims to examine the association of MCR with incident hospitalization in community-dwelling older adults. Design Quebec older population-based observational cohort study with 3 years of follow-up. Setting Community dwellings. Subjects A subset of 999 participants recruited in the NuAge study. Methods Participants with MCR (i.e., with slow gait and cognitive complaint without dementia or motor disability) were identified at baseline assessment. Incident hospitalization (i.e., ≥1) and its recurrence (i.e., ≥2) were collected annually over a 3 year follow-up period. Results The prevalence of MCR was 5.0% at baseline. The overall incidence of hospitalization was 29.0% and its recurrence 4.8%. MCR was associated with incident recurrent hospitalization [adjusted Hazard Ratio (aHR) = 2.58 with 95% Confidence Interval (CI) = (1.09–6.09) and P = 0.031], but not with incident hospitalization [aHR = 1.48, with 95%CI = (0.95–2.28) and P = 0.081]. Conclusion MCR is associated with incident recurrent hospitalization in NuAge participants, suggesting that MCR may be of clinical interest for screening individuals at risk for hospitalization in Quebec's older population.
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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".