Laser Diode – GaAlAs Acupuncture in the Treatment of Central Obesity: a Randomized Clinical Trial
Bibliographic record
Abstract
Background: : Obesity is a global health challenge. Traditional approaches, including increased physical activity, dietary interventions, and medical therapy, often yield limited success, propelling some patients toward costly and invasive procedures like bariatric surgery. Laser acupuncture has been suggested as a complementary therapeutic approach to overcome this challenge. The present study investigated the effectiveness of laser acupuncture treatment in weight loss and abdominal subcutaneous fat reduction. Methods: : A randomized, blinded, sham-controlled clinical trial was conducted, with 30 subjects each in the intervention and control groups. Patients in the intervention group underwent 12 sessions of laser acupuncture treatment within a month (three sessions/week), whereas those in the control group received sham laser treatment on identical acupoints. The patients were instructed not to alter their physical activity levels or dietary regimens. All parameters were evaluated before and after the treatment. Results: : Significant reductions in weight, body mass index, and waist circumference were noted in both intervention and control groups. Further analysis revealed a more significant decrease in the laser acupuncture group. Abdominal sonography revealed a marked decrease in periumbilical fat thickness in the intervention group. Conversely, laboratory evaluations showed no significant difference between the two groups. Conclusion: : Laser acupuncture is an effective method for weight loss in patients with periumbilical abdominal fat. The observed impact on subcutaneous fat suggests its potential as a non-invasive intervention for individuals seeking weight management alternatives. Further research is warranted to validate these findings and explore the underlying mechanisms of laser acupuncture in adipose tissue modulation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".