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Record W4403298528 · doi:10.55905/cuadv16n10-066

Association between vulnerability, frailty and risk of falling in elderly people

2024· article· en· W4403298528 on OpenAlexaboutno aff
Cristiane dos Santos Silva, Rodrigo Mercês Reis Fonsca, Adriano Almeida Souza, Shahjahan Mozart Alexandre da Silva Nery, David Ohara, Margarida Neves de Abreu, José Ailton Oliveira Carneiro, Luciana Araújo dos Reis

Bibliographic record

VenueCuadernos de Educación y Desarrollo · 2024
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsVulnerability (computing)Poisson regressionGerontologyFear of fallingMedicineScale (ratio)Falling (accident)Geriatric Depression ScaleDemographyEnvironmental healthPsychologySuicide preventionPoison controlGeographyPsychiatryPopulationComputer securityCognitionCartography

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.305
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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