Relative Fitness and Frailty of Elderly Men and Women in Developed Countries and Their Relationship with Mortality
Bibliographic record
Abstract
OBJECTIVES: To investigate the relationship between accumulated health-related problems (deficits), which define a frailty index in older adults, and mortality in population-based and clinical/institutional-based samples. DESIGN: Cross-sectional and cohort studies. SETTING: Seven population-based and four clinical/institutional surveys in four developed countries. PARTICIPANTS: Thirty-six thousand four hundred twenty-four people (58.5% women) aged 65 and older. MEASUREMENTS: A frailty index was constructed as a proportion of all potential deficits (symptoms, signs, laboratory abnormalities, disabilities) expressed in a given individual. Relative frailty is defined as a proportion of deficits greater than average for age. Measures of deficits differed across the countries but included common elements. RESULTS: In each country, community-dwelling elderly people accumulated deficits at about 3% per year. By contrast, people from clinical/institutional samples showed no relationship between frailty and age. Relative fitness/frailty in both sexes was highly correlated (correlation coefficient >0.95, P<.001) with mortality, although women, at any given age, were frailer and had lower mortality. On average, each unit increase in deficits increased by 4% the hazard rate for mortality (95% confidence interval=0.02-0.06). CONCLUSION: Relative fitness and frailty can be defined in relation to deficit accumulation. In population studies from developed countries, deficit accumulation is robustly associated with mortality and with age. In samples (e.g., clinical/institutional) in which most people are frail, there is no relationship with age, suggesting that there are maximal values of deficit accumulation beyond which survival is unlikely.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".