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Record W6991041147

Evolução da mobilidade tecidular em cicatrizes pós-mamoplastia de aumento com intervenção de fisioterapia

2022· dissertation· pt· W6991041147 on OpenAlexaboutno aff

Bibliographic record

VenueScientific Repository of the Polytechnic Institute of Porto (The Polytechnic Institute of Porto) · 2022
Typedissertation
Languagept
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsnot available
Fundersnot available
KeywordsLimitingRisk factorWilcoxon signed-rank testPhysical activity
DOInot available

Abstract

fetched live from OpenAlex

As cicatrizes patológicas são uma preocupação em mulheres. A mobilidade cicatricial é um objetivo na reabilitação pós-cirúrgica e desconhecem-se a existência de estudos que descrevam os efeitos da intervenção após uma mamoplastia de aumento. Verificar o efeito de um plano de intervenção em Fisioterapia na mobilidade de tecidos cicatriciais pós mamoplastia de aumento por via infra-mamária. 17 mulheres com cicatrizes infra-mamárias de mamoplastia de aumento entre 10 a 14 dias após a cirurgia. Todas receberam um tratamento combinado de drenagem linfática manual (DLM), seguida de mobilização de tecidos mole (MTM) e educação para as atividades da vida diária (AVD’s). Foram avaliadas a mobilidade e a aparência na cicatriz, antes e após a intervenção. Analisaram-se os resultados através do teste Wilcoxon para 2 amostras emparelhadas, com um nível de significância de 0.05. no local da cicatriz, a mobilidade global e as específicas aumentaram significativamente de M0 para M1, assim como a relação entre os índices de severidade da aderência (ISA). A avaliação com a Escala de Vancouver diminuiu significativamente (p˂0,05). 8 sessões de Fisioterapia com combinação de DLM, MTM e educação para as AVD’s apresentam efeitos benéficos na mobilidade e aparência da cicatriz.

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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.268
Teacher spread0.255 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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