Efficacy and safety of thread embedding acupuncture on knee osteoarthritis
Bibliographic record
Abstract
INTRODUCTION: Although there are various therapeutic methods for the treatment of knee osteoarthritis, each has its advantages and shortcomings, and a definitive treatment method is yet to be determined. This pilot study is designed to obtain basic data for a further large-scale trial as well as provide information about the feasibility of thread embedding acupuncture (TEA) with polydioxanone thread in knee osteoarthritis patients. METHODS AND ANALYSIS: This study is a clinical trial to evaluate the efficacy and safety of TEA for knee osteoarthritis. Forty participants will be recruited at the hospital and after randomization into 2 groups of 20 (experimental and control); they will be treated for 6 weeks. The experimental group will receive TEA treatment 6 times (1 time/week) in 6 weeks on 14 defined knee areas, and the control group, acupuncture treatments 12 times (2 times/week) in 6 weeks on 9 defined acupuncture points. The visual analogue scale (VAS) will be used for the primary efficacy assessment and Short-form McGill Pain Questionnaire (SF-MPQ), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) will be used for the secondary efficacy assessment. The follow-ups before clinical trial, 3 weeks after procedure, 6 weeks after procedure, and 4 weeks after the end of procedure will be done to compare the degree of pain with the control group, which received the acupuncture treatment. CONCLUSION: The trial based on this study will provide clinical information on the efficacy and safety of TEA treatment on knee osteoarthritis. TRIAL REGISTRATION NUMBER: KCT0004844.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".