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Avaliação da qualidade de vida, grau de incapacidade e do desenho da figura humana em pacientes com neuropatias na hanseníase

2017· article· pt· W4300910486 on OpenAlexaff
Camila Beltrame Benedicto, Tatiani Marques, Arianni Pereira Milano, Noêmi Garcia de Almeida Galan, Frank Duerksen, Lúcia Helena Soares Camargo Marciano, Renata Bilion Ruiz Prado

Bibliographic record

VenueActa Fisiátrica · 2017
Typearticle
Languagept
FieldMedicine
TopicLeprosy Research and Treatment
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsMedicineHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Na hanseníase, a presença de sintomas dermatoneurológicos com potencial evolução para incapacidades físicas pode comprometer a qualidade de vida (QV) e a imagem corporal do paciente. Objetivo: Avaliar as possíveis associações entre a QV, o Grau de Incapacidade (GI) e o Desenho da Figura Humana (DFH) em indivíduos com neuropatia hansênica. Método: Este estudo consiste em um estudo descritivo, com abordagem quanti-qualitativa. Foram utilizados quatro instrumentos de avaliação: Questionário sociodemográfico, NeuroQol (Neuropathy – Specific Quality of Life Questionnaire), DFH e Formulário de avaliação do GI. Foram incluídos pacientes com GI 1 ou 2 nos pés e idade igual ou superior a 18 anos. Resultados: Foram avaliados 100 indivíduos. Entre aqueles com GI 2, houve uma tendência à omissão do nariz (p=0,050) e DFH no tamanho pequeno (p=0,047). Houve associação entre o DFH e o domínio QV Sintomas difuso sensitivo-motores (p=0,035), sugerindo que a omissão dos pés no DFH pode representar perda da QV. Conclusão: Indivíduos com neuropatia hansênica apresentam QV boa à moderada. A omissão de segmentos do corpo pode indicar conflitos e sentimentos de insegurança. Há indícios de perda de autonomia quando o paciente omite ou corta os pés no DFH.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.071
GPT teacher head0.358
Teacher spread0.287 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2017
Admission routes1
Has abstractyes

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