Síndrome da fragilidade em idosos institucionalizados: prevalência e fatores associados
Bibliographic record
Abstract
To investigate the prevalence and the factors associated with frailty syndrome in institutionalized elderly, residents in the city of Recife/PE, a descriptive, cross-sectional, quantitative study was performed in nine public or philanthropic Homes for the Aged, between January and May 2013. We included 214 seniors, assuming as independent variables, the sociodemographic and health conditions, self-reported or obtained from elderly records, and the degree of elderly fragility, as dependent variable, assessed by Edmonton Fragility Scale. The mean age equaled to 76.42 ± 0.66 years (95%CI 75.12 – 77.71). We found a predominance of females (69.6%), unmarried (53.7%), with study time ranging from one to four years (54.4%). More frequently they referred perception of income (86.4%) up to one minimum salary (73.4%) and the residence time was less than a year to 29.4% of elderly. Regarding cognition, 79.4% of respondents were disapproved by significant errors. The frailty syndrome was identified in 70.1% of the elderly. All factors included in elderly frailty scale reached statistical significance, associated with increased frailty prevalence, as well as education, with a prevalence equal to 3.0 (95%CI 1.3 – 6.6) for its absence, and 2.5 (95%CI 1.2 – 5.3), for a four-year study. The absence of personal income increased at twice the prevalence (95%CI 1.0 – 4.0). In multivariate analysis, the factors that most contributed to the prevalence were impaired cognition, functional independence, self-evaluation of health, frequency of social support, perceived weight loss and feeling of sadness/depression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".