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Record W1926909635

Análise da funcionalidade de idosos com osteoartrite

2015· article· pt· W1926909635 on OpenAlexaboutno aff

Bibliographic record

VenueAmericanae (AECID Library) · 2015
Typearticle
Languagept
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology
DOInot available

Abstract

fetched live from OpenAlex

O objetivo deste estudo foi analisar a influência do gênero, idade e farmacoterapia da osteoartrite (OA) sobre a funcionalidade de idosos. Trata-se de um estudo transversal com 105 idosos de ambos os gêneros (Idade: 70,73±6,0 anos) e portadores de OA de quadril e/ou joelho, confirmado por análise radiográfica. A funcionalidade foi avaliada por dois instrumentos: Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) e Índice Algofuncional de Lequesne. As análises dos dados apresentaram pior funcionalidade tanto no questionário Lequesne (p=0,007) como no WOMAC (p=0,013) e em seus domínios Intensidade da Dor (p=0,013), Rigidez (p=0,032) e Funcionalidade (p=0,018). Contudo, não foram verificadas diferenças nos instrumentos avaliados quanto a diferentes faixas etárias ou comprometimento da articulação segundo alterações radiográficas (p>0,05). Foi observado que os medicados apresentavam pior funcionalidade em comparação aos que não utilizavam medicamentos para OA (Lequesne: p=0,005; WOMAC: p=0,008 e domínios: Intensidade da Dor: p=0,004; Rigidez: p=0,007 e Funcionalidade: p=0,023). No modelo multivariado, foi observado que o gênero e o tratamento farmacológico influenciam a funcionalidade de idosos portadores de OA (p<0,05), sendo as mulheres e os indivíduos medicados os que apresentam pior funcionalidade tanto no índice Lequesne quanto WOMAC. Observou-se pior funcionalidade em idosas portadoras de OA e que o uso de medicamentos para osteoartrite não promoveu melhora na condição funcional desses indivíduos.

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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.273
Teacher spread0.250 · 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

Citations6
Published2015
Admission routes1
Has abstractyes

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