Efficacy of Eggshell Membrane in Knee Osteoarthritis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Osteoarthritis (OA) is a prevalent, degenerative joint disease, with knee OA being particularly common and impactful. This systematic review and meta-analysis aimed to assess the efficacy of eggshell membrane (ESM) supplementation in improving joint functionality and reducing pain in individuals with knee OA. A comprehensive search was conducted across PubMed, Scopus, Web of Science, and Cochrane Database up to July 2024, following PRISMA guidelines. Seven randomized controlled trials (RCTs) met the inclusion criteria, with five included in the meta-analysis. The studies compared ESM to a placebo, evaluating outcomes based on assessment tools such as the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Visual Analogue Scale (VAS), and Knee Injury and Osteoarthritis Outcome Score (KOOS). Results indicated that ESM significantly reduced pain and improved functionality, with notable improvements in total WOMAC score (effect size −0.34; 95% CI: −0.56 to −0.13; p < 0.001) and pain subscale (SMD −0.23; 95% CI: −0.42 to −0.04; p < 0.02). The findings support ESM as a promising adjunctive treatment for knee OA, offering a safe, natural supplement to enhance quality of life. Further high-quality RCTs are needed to confirm these results and explore the long-term effects and mechanisms of ESM.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.022 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".