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Health care are associated with worsening of frailty in community older adults

2019· article· en· W2927259509 on OpenAlexaboutno aff
Jair Almeida Carneiro, Cássio de Almeida Lima, Fernanda Marques da Costa, Antônio Prates Caldeira

Bibliographic record

VenueRevista de Saúde Pública · 2019
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado de Minas Gerais
KeywordsMedicinePoisson regressionPolypharmacyGerontologySocioeconomic statusDemographyEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify the factors associated with the worsening of frailty in older adults resident in the community. METHODS: This is a prospective, longitudinal, and analytical study. The data collection in the baseline occurred in the participants' homes from a random sampling by conglomerates. Demographic and socioeconomic variables, morbidities, and use of health services were analyzed. Frailty was measured by the Edmonton Frail Scale. The second data collection was performed after an average period of 42 months. The adjusted prevalence ratios were obtained by multiple Poisson regression analysis with robust variance. RESULTS: A total of 394 older adults participated in both phases of the study, with 21.8% of them presenting worsening of the frailty condition. The variables that remained statistically associated with the transition to a worse state of frailty were: polypharmacy, negative self-perception of health, weight loss, and hospitalization over the past 12 months. CONCLUSIONS: The factors associated with worsening of frailty along the studied period among older adults in the community were those related to health care. This result must be considered by health professionals when addressing frail and vulnerable older adults.

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)0.001
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 score0.012
Threshold uncertainty score0.827

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.017
GPT teacher head0.293
Teacher spread0.275 · 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

Citations21
Published2019
Admission routes1
Has abstractyes

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