Mortality and morbidity hazards associated with cognitive status in seniors: A Canadian population prospective cohort study
Bibliographic record
Abstract
INTRODUCTION: Although cognitive impairment is widely accepted as a leading indicator of dementia, influences of cognitive status on incident dementia and mortality remain unclear. The present study investigated the morbidity hazard associated with cognitive impairment and the mortality hazard associated with dementia in comparison to cognitively intact seniors. METHODS: A population-based sample of 2914 seniors with clinically diagnosed cognitive status at Wave I (1991-1992) of the Canadian Study of Health and Aging (CSHA) were followed-up 5 years later (1996-1997). At Wave I, there were 921 cognitively intact, 861 cognitively impaired but not demented (CIND), and 1132 seniors with dementia, respectively. The primary outcome measures 5 years later were being cognitively intact, CIND, dementia and death. Kaplan-Meier estimates, log-rank tests, and Cox's proportional models were used in the analyses. RESULTS: Respondents with CIND at Wave I were 2.191 times (95%CI 1.706-2.814) more likely to have dementia 5 years later than cognitively intact seniors. After adjusting for confounding socio-demographic and health status factors, the odds ratio was reduced to 2.147 times (95%CI 1.662-2.774), but remained significant. Respondents with CIND had a mortality rate 1.869 times (95%CI 1.602-2.179) and seniors with dementia 3.362 times greater (95%CI 2.929-3.860) than that of seniors who were cognitively intact. After controlling the confounders, the odds remained significant at 1.576 (95%CI 1.348-1.843) for CIND respondents and 2.415 (95%CI 2.083-2.800) for seniors with dementia. DISCUSSION: CIND increases both the risk of dementia and mortality. Early intervention with CIND is warranted to reduce both dementia incidence and mortality.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 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".