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Record W4361215703 · doi:10.53740/rsm.v14i1.628

PREVALÊNCIA DE CAPSULITE ADESIVA NO OMBRO DE INDIVÍDUOS COM DIABETES MELLITUS

2023· article· pt· W4361215703 on OpenAlexaboutno aff
Érika Silva Rodrigues, Lorraine Souza de Oliveira, Vanessa Chiaparini Martin Coelho Pires, Jean De Paula Ferreira, Geovana Valadão Borges Fusco

Bibliographic record

VenueREVISTA SAÚDE MULTIDISCIPLINAR · 2023
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiabetes mellitusHumanitiesGynecologyEndocrinologyPhilosophy

Abstract

fetched live from OpenAlex

O intuito deste trabalho foi realizar um levantamento da prevalência da Capsulite Adesiva (CA) no ombro da população com diabetes mellitus (DM), seja do tipo I ou II. Objetivos: trazer possíveis associações da DM com a prevalência de CA; mostrar dados atualizados desta prevalência e contribuir para o manejo clínico da população com diabetes, visando prevenir a CA. Metodologia: uma revisão narrativa da literatura que incluiu estudos que analisaram homens e mulheres, maiores de 18 anos, com diagnóstico de algum tipo de DM. Aplicou-se a escala de Newcastle-Ottawa, que foi usada para avaliar a qualidade metodológica dos estudos. Resultados: constatamos que a capsulite adesiva tem maior prevalência em indivíduos com diabetes mellitus tipo 1 e 2 e está mais associada ao sexo, idade e outros. Discussão: a prevalência da CA em diabéticos varia entre 1,20% e 54,78%. Entretanto, a DM não foi o único vetor para predispor a CA. Considerações finais: consideramos que o mal controle glicêmico, por um longo período de tempo, desencadeia alterações musculoesqueléticas, como a CA, no organismo de indivíduos com DM em associação a outros fatores

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)0.006
metaresearch head score (Gemma)0.002
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0040.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.006

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 head0.038
GPT teacher head0.332
Teacher spread0.294 · 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.

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
Published2023
Admission routes1
Has abstractyes

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