Cognition, even in the normal range, predicts disability: cross‐sectional and prospective analyses of a population‐based sample
Bibliographic record
Abstract
OBJECTIVE: To determine if the modified mini-mental state examination (3MS) predicts functional status and if any effect on function is observed within the normal range of cognition. DESIGN: Cohort study. SETTING: Community-dwelling older adults in the Canadian province of Manitoba sampled in 1991 and followed in 1996. PARTICIPANTS: Baseline sample of 1751 adults aged 65+ from a representative registry. Five years later, 1028 participants remained in the community and had no missing data. MEASUREMENTS: The 3MS, age, gender, education, living arrangements, self-rated health, and depressive symptoms were self-reported. Functional status was assessed using the Older Americans Resource Survey, which was dichotomized into no/mild disability versus moderate/severe disability. RESULTS: Baseline 3MS score predicted baseline functional status. This effect was a gradient across the entire 3MS score, extending into the normal range with no apparent threshold. In logistic regression models, the unadjusted odds ratio (OR, 95% confidence interval) for the association of 3MS score with disability was 0.94 (0.93, 0.95); the adjusted OR was 0.96 (0.95, 0.98) in models including age, gender, education, and other covariates. Baseline 3MS score also predicted functional status 5 years later: The unadjusted OR for disability was 0.94 (0.92, 0.95); the adjusted OR was 0.97 (0.95, 0.99). Again, the risk of functional impairment at time 2 was a gradient effect, extending into the normal range of baseline 3MS score. CONCLUSIONS: The 3MS predicts functional decline, and this effect is a gradient effect. These results support the hypothesis that cognition is a continuum in risk.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".