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Record W2788125924 · doi:10.29328/journal.jsmt.1001023

Ultrasound conjugated with Laser Therapy in treatment of osteoarthritis: A case study

2018· article· en· W2788125924 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Sports Medicine and Therapy · 2018
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsnot available
FundersFinanciadora de Estudos e ProjetosConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsOsteoarthritisMedicineUltrasoundLaser therapyConjugated systemRadiologyLaserPathologyMaterials scienceOpticsAlternative medicine

Abstract

fetched live from OpenAlex

Osteoarthritis of the hand is a chronic condition that involves hand joints, but receives less attention. Few studies have investigated the use of ultrasound therapy and laser therapy for the treatment of hand osteoarthritis. The objective was to evaluate the effect of the conjugated treatment of therapeutic ultrasound and laser therapy on the pain and joint function of a patient with hand osteoarthritis. The is case of a woman, 57 years old, with a diagnosis of osteoarthritis on hand for 3 years, presenting constant pain and worsening after manual activities. The pain and function were evaluated, respectively, by Visual Analog Scale (VAS) and Australian Canadian Osteoarthritis Hand Index questionnaire (AUSCAN). After 12 sessions using ultrasound and laser therapy application, there was an expressive improvement in the pain and functional indexes of the patient. The combined application of therapeutic ultrasound and laser therapy, through the unified field action of the therapies used, proved to be efficient in reducing pain and improving the functionality.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.321
Teacher spread0.295 · 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 designCase report
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

Citations3
Published2018
Admission routes1
Has abstractyes

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