Efficacy and safety of acupoint catgut embedding for knee osteoarthritis: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Acupoint catgut embedding (ACE) is a therapeutic method for pain management that involves inserting a thread or catgut into the body with anti-hyperalgesic effect. This study aims to systematically review and comprehensively compare the effectiveness of ACE with that of each comparator in the treatment of knee osteoarthritis (OA). METHODS: We searched 11 databases (PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, Chinese Biomedical Literature Database, Chinese Scientific Journal Database, WanFang Database, China National Knowledge Infrastructure, Oriental Medicine Advanced Searching Integrated System, Science-On, and KoreaMed) from their inception through August 1, 2023, without language limitations. Additionally, 2 registration platforms - ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry - were searched for ongoing trials. The primary outcomes were assessed using a visual analog scale (VAS) and the Western Ontario and McMaster Universities OA Index. The secondary outcomes included the total effective rate, Lysholm score, and adverse effects. The risk of bias was assessed using the Cochrane handbook. The meta-analysis was performed using review manager, while the quality of evidence was evaluated using GradePro. RESULTS: A total of 28 randomized controlled trials were included in the present study, encompassing 2120 participants. The most frequently used acupoint was GB34. The overall risk of bias was unclear. According to the meta-analysis results, the combination of ACE and conventional treatments showed higher effectiveness in term of the VAS, Western Ontario and McMaster Universities OA Index, total effectiveness, and Lysholm scores. Moreover, compared with the sham ACE control, the results showed that the combination of ACE and conventional treatments was more beneficial in term of the VAS, Western Ontario and McMaster Universities OA Index, and total effectiveness. CONCLUSION: Despite some potential improvement, the current evidence regarding the effectiveness of ACE for the treatment of knee OA is inconclusive due to the poor quality of the available evidence. Future well-designed randomized controlled trials are needed to confirm ACE's effectiveness for treating knee OA.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.037 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".