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Método Isostretching como tratamento da dor lombar

2015· article· pt· W2289275280 on OpenAlexaboutno aff
Carlos Fernando Taborda, Gisele Maria Moschen, Magda Yaemi Mitsuro, Andersom Ricardo Fréz, Christiane Riedi Daniel

Bibliographic record

VenueRevista Brasileira de Qualidade de Vida · 2015
Typearticle
Languagept
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

OBJETIVO: Verificar os efeitos do método Isostretching na qualidade de vida, na intensidade da dor e na funcionalidade em sujeitos com dor lombar e determinar a influência desta técnica na mobilidade da coluna.MÉTODOS: Participaram da pesquisa 18 sujeitos com idade média de 35,68 ± 6,85 anos. Foram aplicadas de 12 a 15 posturas do método Isostretching, 3 vezes por semana, durante 8 semanas, totalizando 24 intervenções. Foram consideradas as variáveis: dor, avaliada pela Escala Visual Analógica e pelo Questionário de McGill; capacidade funcional, utilizando o Questionário de Incapacidade de Roland-Morris; qualidade de vida, utilizando o Questionário SF-36; flexibilidade, pelo banco de Wells; e, amplitude de movimento do tronco, utilizando a goniometria. Para a análise dos dados, utilizou-se o teste t pareado para os resultados com distribuição normal e o teste não paramétrico de Wilcoxon para dados não homogêneos.RESULTADOS: Diferenças significativas foram observadas em ambas as avaliações da dor (p<0,001); da capacidade funcional (p<0,0001), da qualidade de vida (p<0,0001) e em todos os domínios do SF-36 (p<0,05), da flexibilidade (p<0,0001) e da amplitude de movimento lombar (p<0,05).CONCLUSÃO: As 24 intervenções do método Isostretching foram eficazes para redução da dor, melhora da capacidade funcional e da qualidade de vida e aumento da flexibilidade da cadeia posterior e da mobilidade da coluna lombar.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.052
GPT teacher head0.351
Teacher spread0.299 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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