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Evaluation of the effects of acoustic wave therapy on keloids

2017· article· en· W2772117296 on OpenAlexaboutno aff
Dóris Hexsel, Fernanda Oliveira Camozzato, Aline Flor Silva, Carolina Siega

Bibliographic record

VenueSurgical & Cosmetic Dermatology · 2017
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineKeloidDermatology

Abstract

fetched live from OpenAlex

Introdução: A terapia por ondas acústicas estimula os processos de regeneração e recuperação dos tecidos. Nesse sentido, espera-se que esse equipamento possa atuar em cicatrizes. Objetivo: Avaliar a eficácia e segurança da terapia por ondas acústicas na melhora de queloides. Métodos: Estudo aberto, prospectivo, unicêntrico que incluiu 20 participantes com diagnóstico clínico de queloide. Foram realizadas oito sessões de terapia por ondas acústicas, uma por semana, durante oito semanas. Os participantes foram avaliados no momento basal e uma e 12 semanas após o término do tratamento. Medidas de elasticidade e avaliação clínica pela Escala de Cicatrizes de Vancouver foram realizadas. Ao final do tratamento foi observada a satisfação dos participantes com o tratamento. Resultados: Após o tratamento, a percentagem de participantes com espessura do queloide entre dois e 5mm caiu de 71% para 47%, aumentando a percentagem de participantes com espessura menor do queloide na amostra total (<2mm, de 24% para 41%). Os aspectos da vascularização e flexibilidade também apresentaram melhora em alguns participantes. Não foram relatados eventos adversos relacionados ao tratamento. Conclusões: O tratamento por ondas acústicas é seguro e pode ser eficaz na melhora funcional de lesões de queloide e de alguns aspectos clínicos da lesão.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.715
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

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

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 head0.065
GPT teacher head0.383
Teacher spread0.318 · 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.

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
Published2017
Admission routes1
Has abstractyes

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