Fu’s subcutaneous needling for knee osteoarthritis: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Acupuncture has been listed as an alternative treatment in several knee osteoarthritis (KOA) international guidelines. Fu’s subcutaneous needling (FSN), as a novel acupuncture therapy, has shown greater potential for treating KOA. The objective of this systematic review is to compare the efficacy and safety of FSN to routine acupuncture therapy (RAT) for KOA. Methods China National Knowledge Infrastructure, VIP, China Biomedical Literature Database, Wanfang Medical, Embase, PubMed, Ovid, and the Cochrane Library were searched from inception to March 2025, and randomized controlled trials on FSN for KOA were included. The primary outcomes were total efficacy rate, Visual Analog Scale (VAS) pain scores and Western Ontario and McMaster Universities Arthritis Index (WOMAC) scores. Literature quality was assessed using Cochrane risk-of-bias tool 1.0. Heterogeneity among trials was assessed using the Cochrane Q test and I2 values, determining model selection (fixed/random effects). The meta-analyses of included studies used odds ratios and mean differences when appropriate, along with significance threshold α = 0.1. The evidence was evaluated by the GRADE guideline. The PROSPERO International Prospective Register of Systematic Reviews received this research for registration (CRD42024595903). Results A total of 14 studies were included (1,186 patients, with 594 in FSN group and 592 in RAT group). Primary outcomes: The total efficacy rate of the FSN group was significantly higher than that of the RAT group [OR = 3.83, 95% CI (2.36, 6.91), p < 0.01, n = 10, 470/467 participants]. FSN also demonstrated greater effectiveness in reducing VAS pain scores [MD = −1.44, 95% CI (−1.62, −1.26), p < 0.01, n = 6, 205/206 participants] and WOMAC scores [MD = −6.07, 95% CI (−8.16, −3.97), p < 0.01, n = 5, 160/161 participants]. Secondary outcomes: FSN group showed a greater reduction in inflammatory cytokines: IL-6 [MD = −1.50 ng/mL, 95% CI (−1.55, −1.46), p < 0.01, n = 4, 180/180 participants], TNF-α [MD = −2.26 pg/mL, 95% CI (−2.30, −2.23), p < 0.01, n = 4, 180/180 participants]. Conclusion Compared to RAT for KOA, FSN demonstrates superior efficacy in alleviating pain, reducing inflammation, and improving joint dysfunction. Further high-quality studies are needed to determine the long-term efficacy of FSN. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/view/CRD42024595903 .
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.028 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".