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Record W2143762700 · doi:10.5380/ce.v20i2.39928

AVALIAÇÃO DA FRAGILIDADE DE IDOSOS INTERNADOS EM SERVIÇO DE EMERGÊNCIA DE UM HOSPITAL UNIVERSITÁRIO

2015· article· pt· W2143762700 on OpenAlexaboutno aff
Juliane de Fátima Santos Antunes, Meiry Fernanda Pinto Okuno, Maria Carolina Barbosa Teixeira Lopes, Cássia Regina Vancini Campanharo, Ruth Ester Assayag Batista

Bibliographic record

VenueCogitare Enfermagem · 2015
Typearticle
Languagept
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGerontology

Abstract

fetched live from OpenAlex

O objetivo do estudo foi avaliar a fragilidade de idosos internados no Serviço de Emergência de umhospital universitário do estado de São Paulo. O período da coleta de dados foi de março a junho de 2014.Estudo transversal com 101 idosos, por período igual ou superior a 24 horas. Análise realizada pela aplicaçãoda Edmonton Frail Scale. A média de idade foi 75 anos, 50,5% sexo feminino, 58,4% não terminou o ensinofundamental, 89,1% aposentados ou pensionistas e 84,2% acompanhados de cuidador. Antecedentes frequentesforam: hipertensão arterial (65,3%), diabetes mellitus (65,3%) e tabagismo (44,6%). Em relação à fragilidade, amédia do escore total foi 9,85, indicando fragilidade moderada. Os idosos com doenças neurológicas, demência,idade mais avançada e que tinham cuidador apresentaram maior fragilidade. O rastreamento da fragilidade propiciaplanejamento com vistas à prevenção de incapacidade e o agravamento das condições de saúde dos idosos.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.304
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2015
Admission routes1
Has abstractyes

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