Association between vulnerability, frailty and risk of falling in elderly people
Bibliographic record
Abstract
Vulnerability and frailty are well-known fall risk factors in older people. However, whether both factors are associated has not been fully elucidated, and more current scientific evidence on this relationship is still lacking. The objective of this study was to analyze the relationship between vulnerability and fragility and the risk of being left behind. This is a cross-sectional study, a household survey of elderly people aged ≥ 60 years, carried out in two Family Health Units in the southwest of Bahia, with a sample of 218 elderly people. The instruments used were: Mini-Mental State Examination (MMSE); sociodemographic questionnaire and health conditions; Edmonton Frailty Scale; Time Up and Go Test (TUGT) and the Vulnerability Scale/VES13. For data analysis, the Prevalence Ratio estimated by the Poisson regression model was used using the statistical software SPSS version 21.0. There was a significant association between the risk of falls and frailty (PR=1.06; CI=0.89-1.26; p<0.001), when the model was adjusted with the variables age group, MMSE and vulnerability. The risk of falling is directly related to frailty in older people, but not to vulnerability. Health care, such as physical activity, is needed to reduce the risk of falls.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".