The Effect of Catgut Embedding at Acupoints Versus Nonacupoints in Abdominal Obesity: Protocol for a Multicenter, Double-Blind, 16-Week Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Obesity is an increasing problem worldwide. The effective treatments for obesity mainly include diet, physical activity, behavioral intervention, pharmacotherapy, and bariatric surgery, which all have certain limitations. As a specific type of acupuncture therapy, acupoint catgut embedding (ACE) has gained substantial attention in the management of obesity in recent years. Previous studies suggested that ACE may be an effective obesity treatment. However, the evidence for the efficacy of ACE in abdominal obesity (AO) remains inadequate due to the paucity of high-quality studies. OBJECTIVE: This study aims to investigate the difference in the effectiveness of catgut embedding at acupoints and catgut embedding at nonacupoints in patients with AO and to further validate the efficacy and safety of ACE for AO. METHODS: This is a multicenter, double-blind, 16-week randomized controlled trial. A total of 92 eligible participants with AO will be randomly divided into 2 groups (1:1 allocation ratio). The ACE group will receive catgut embedding at acupoints and the control group will receive catgut embedding at nonacupoints. The intervention will be performed every 2 weeks for a total of 6 sessions. Follow-up will be performed every 2 weeks for a total of 2 visits. The primary outcome is waist circumference. Secondary outcomes include body weight, BMI, hip circumference, and the visual analog scale of appetite. Upon the completion of the trial, we will evaluate the effect of catgut embedding at acupoints or nonacupoints on obesity indicators in patients with AO. For treatment outcomes, an intention-to-treat analysis will be performed. RESULTS: The start of recruitment began in August 2019 and is expected to end in September 2023. CONCLUSIONS: Although studies have been conducted to demonstrate the effectiveness of ACE in the treatment of obesity, the evidence for the efficacy of ACE in AO remains insufficient due to the quality of the studies. This rigorous normative randomized controlled trial will verify the effect of catgut embedding at acupoints or nonacupoints in patients with AO. The findings will provide credible evidence as to whether ACE is an effective and safe treatment for AO. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR1800016947; https://tinyurl.com/2p82257p. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46863.
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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 | 0.033 | 0.029 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.044 | 0.007 |
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".