Effect of laser acupuncture on obesity: study protocol for a randomized controlled trial
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.037 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.017 | 0.005 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.075 | 0.011 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".