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Record W1956397613 · doi:10.1186/s13063-015-0748-4

Effect of laser acupuncture on obesity: study protocol for a randomized controlled trial

2015· article· en· W1956397613 on OpenAlexaff
Chi‐Chuan Tseng, Alan Tseng, Chia‐Hao Chang

Bibliographic record

VenueTrials · 2015
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAcupunctureWaistBody mass indexRandomized controlled trialPhysical therapyObesityCrossover studyBody fat percentageInternal medicineAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Obesity-related diseases have a profound economic impact on health care systems. Laser acupuncture has been shown to have beneficial effects on obesity. However, to our knowledge, those trials were either non-randomized, non-blinded or included low-calorie diet control. We have, therefore, designed a patient-assessor-blinded, randomized, sham-controlled crossover trial to investigate the significance of laser acupuncture on obesity. METHODS/DESIGN: 104 subjects above 20 years of age with a body mass index (BMI) of over 25 kg/m(2) will be divided into 2 groups: experimental and control. Each subject will receive the treatment relevant to their group 3 times a week for 8 weeks. After 8 weeks of treatment the subject will enter a 2-week washout period, after which the subjects will switch groups. Measurements will include BMI, body fat percentage, waist-to-hip ratio (WHR), waist circumference, hip circumference, skinfold thickness, thigh circumference, body fat, blood pressure, heart rate, hunger and the 36-item Short-Form Health Survey (SF-36). DISCUSSION: The results of this study will provide the basis for future large-scale multicenter trials investigating the effects of laser acupuncture on obesity. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02167308 ; registration date: 14 June 2014.

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)0.029
metaresearch head score (Gemma)0.086
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.057
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0290.086
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0100.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.137
GPT teacher head0.509
Teacher spread0.372 · 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; both teacher heads agree on what is shown here.

Study designRandomized trial
Domainnot available
GenreProtocol

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

Citations8
Published2015
Admission routes1
Has abstractyes

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