P3‐161: Changes in cognition in relation to frailty in older Canadians
Bibliographic record
Abstract
With age, on average, people show decline in both cognition and in fitness, appreciated as increasing frailty. While frailty is recognized as a risk for dementia, it is less clear how the accumulation of general health deficits relates to the accumulation of cognitive deficits, although each has been identified separately as arising from structurally similar stochastic processes. Here, we analyzed how five-year changes in cognition (defined as the errors 0n the Modified Mini-Mental State Examination) are related to general health status (defined by the Frailty Index) in older Canadians (n = 8,403). Cognitive change was analyzed using a novel multistate transition (stochastic) model the output of which was well fit (R-square >0.85) by a modified Poisson distribution. In multivariable analyses, both age and frailty were independently associated with cognitive changes and the risk of death. Risk estimates varied by sex. Women had both a higher chance of staying alive (29% died, 95%CI=27%-31%) and of showing improvement or stabilization (34%, 95%CI=32%-36%), whereas fewer men survived (34% died, 95%CI=32% -36%) and fewer showed stabilization or improvement (30%, 95%CI=28%-32%). Frail people less often showed cognitive improvement or stabilization (20%, 95% CI=18%-22%) compared to non-frail people, of whom 39% (95%=37%-41%) did not deteriorate. Similarly, frail people were more likely to die (48%, 95%CI=46%-50%) versus 20% (95% CI=18%-22%) of non-frail people. By contrast, there was no difference in mortality by education level, but a greater chance of cognitive stabilization/improvement for people with higher education. Among more educated people 35% improved or remained stable (95% CI=33%-37%) than did less educated people (29%, 95%CI=27%-31%). The overall probability of dying amongst higher educated people was 28% (95%CI=26%-30%) versus 36% (95%CI=34%-38%) in people with lower levels of education. Cognitive changes generally correlate with general health status. Men and women each show deleterious effects from frailty, but the profiles of relative risk expression differ between them.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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".