Instrumentos na avaliação da fragilidade em idosos comunitários: uma revisão de literatura
Bibliographic record
Abstract
INTRODUCAO: Nao ha consenso a respeito da avaliacao de fragilidade. Devido a isso, a escolha do instrumento e dependente da definicao a que se refere, assim como da variacao populacional (BARRETO, 2012; KIM, 2014) O objetivo desta revisao foi buscar e descrever questionarios e testes aplicados no diagnostico e avaliacao da Sindrome da Fragilidade. METODOS: Realizou-se uma busca sistematica nas bases de dados PubMed, LILACS e MEDLINE por meio dos descritores Frailty Syndrome combinado com Assessment e Elderly OR Aged OR Older. RESULTADOS: Obteve-se um total de 37 artigos. Foram encontrados como instrumentos fisiologicos: marcadores imunologicos, 25 hidroxivitamina D, proteina C-reativa e concentracao de hormonios reprodutivos; e como instrumentos clinicos: The Marigliano Cacciafesta Polypathological Scale (MCPS), Study of Osteoporotic Fractures (SOF) index, Short Battery of Physical Performance, Groningen Frailty Index (GFI), Tilburg Frailty Index (TFI), Sherbrooke Postal Questionaire (SPQ), Cadiovascular Health Study (CHS) index, Edmonton Frailty Scale (EFS), CSBA index, The Frailty Trait Scale, FI-CGA, The Gill Frailty Index, Escala FRAIL, Frailty Index, Conselice Study of Brain Aging Score, Canadian Study of Health and Aging, Modified Short Emergency Geriatric, Clinical Global Impression of Change in Physical Frailty, Easycare Two-step Older persons Screening, Food Frequency Questionnaire, PRISMA-7, SMF-BIA, e Hubbard Scale. CONCLUSAO: Dentre os instrumentos encontrados na busca, apenas o Food Frequency Questionnaire, Groningen Frailty Indicator, Tilburg Frailty Indicator e o Edmonton Frail Scale foram validados para o portugues-Brasil, havendo a necessidade de mais estudos que avaliem fragilidade na comunidade brasileira.
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 | 0.015 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".