Efficacy of natural eggshell membrane for knee osteoarthritis: A randomized, double-blind, placebo-controlled clinical trial
Bibliographic record
Abstract
• Natural eggshell membrane was effective in reducing pain and joint function of early-stage knee osteoarthritis patients. • Natural eggshell membrane significantly improved quality of life of early-stage knee osteoarthritis patients. • Natural eggshell membrane significantly changed cartilage oligomeric matrix protein of knee osteoarthritis. • No adverse effect significantly relevant to the natural eggshell membrane was found. Knee osteoarthritis (KOA) is a common degenerative disease in older adults. Natural Eggshell Membrane (NEM) comprises bioactive ingredients known to relieve the symptoms of KOA, such as glycosaminoglycans, and has been shown by preclinical studies to be effective in the treatment of KOA. Participants received either NEM (n = 49) or a placebo product (n = 50). After 12 weeks of NEM intake, the Western Ontario and McMaster Universities Osteoarthritis Index score, visual analog scale pain score, and World Health Organization Quality of Life-BREF score (physical health, social relationship score) significantly improved compared to those in the placebo group ( p < 0.05). However, NEM intake did not significantly change in inflammation and cartilage markers, except for cartilage oligomeric matrix protein. Additionally, no serious adverse events were associated with NEM intake. The 12-week NEM intake was effective and safe for improving pain and joint function in patients with early-stage KOA.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".