Does Self‐Rated Health Predict Survival in Older Persons with Cognitive Impairment?
Bibliographic record
Abstract
OBJECTIVES: To determine whether baseline self-rated health (SRH) independently predicted survival in an older Canadian population and to investigate the role of cognition on the SRH-mortality relationship. DESIGN: Population-based prospective cohort study. SETTING: Ten Canadian provinces, community-based. PARTICIPANTS: A total of 8,697 community-dwelling participants aged 65 and older. MEASUREMENTS: Self-reported measures of overall health, physical function, comorbidities, and demographic characteristics were obtained by interview. Cognitive ability was ascertained using the Modified Mini-Mental State Examination (3MS). Participants were followed for their survival status from the initial interview in 1991 until October 31, 1996. RESULTS: Subjects with reports of poor SRH were significantly more likely to die during follow-up than those reporting good SRH, after adjusting for relevant covariates (adjusted hazard ratio (AHR)=1.38, 95% confidence interval (CI)=1.24-1.53). SRH was also related to other measures of health status across levels of cognitive impairment. SRH remained a significant predictor of mortality in subjects with mild to moderate cognitive impairment (AHR=1.26, 95% CI=1.01-1.59) but not in those with severe cognitive impairment (AHR=1.00, 95% CI=0.76-1.31). CONCLUSION: This study supports the utility of SRH assessments in predicting survival of individuals with mild to moderate cognitive impairment. The findings highlight the potential role of complex cognitive processes underlying the SRH-mortality relationship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".