Efficacy and safety of undenatured collagen type II in modulating knee joint function in healthy and osteoarthritis subjects: a systematic review and meta-analysis
Bibliographic record
Abstract
Collagen has emerged as a potential pharmacotherapeutic intervention for knee osteoarthritis (OA). This study evaluates the effectiveness and safety of undenatured collagen type II (UC-II) among patients with knee OA and healthy subjects without joint-related disease but experiencing activity-related joint discomfort. Systematic literature search was conducted through PubMed, Embase, and Cochrane up to June 2024, and a total of 17 articles were included in the final analysis. The primary outcome was efficacy: Western Ontario and McMaster Universities (WOMAC) score, visual analog scale (VAS) score, Lequesne’s functional index (LFI), and knee range of motion (ROM). The secondary outcome was safety: adverse events (AEs) and serious AEs. In patients with knee OA, UC-II significantly decreased knee OA symptoms and improved the quality of life (QoL) by significant reductions of WOMAC scores (pain: −9.24 [P = 0.004], stiffness: −6.47 [P = 0.091], physical function: −7.31 [P = 0.043], total: −9.83 [P < 0.001]), VAS (−1.87; P = 0.006), LFI (−2.17; P < 0.001) and knee ROM. Treatment in healthy people reduced VAS scores and significantly increased the step number to the first onset of pain over the baseline (P < 0.05). The treatment was safe with no significant individual AE (headache: RR = 0.34, diarrhoea: RR = 0.48) and total AE (RR = 1.0090) in both populations. This study highlights the benefits and safety of UC-II to improve knee health and QoL in patients with knee OA and healthy subjects.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.026 |
| Bibliometrics | 0.004 | 0.005 |
| 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) | 0.003 | 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".