Intra-articular Injection of Type I Atelocollagen to Alleviate Knee Pain: A Double-Blind, Randomized Controlled Trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Collagen disruption is one of the underlying causes of knee pain in patients with osteoarthritis and/or diverse cartilage defects. Atelocollagen is a type of collagen that lacks telopeptides and thus has reduced antigenicity. The intra-articular injection of type I atelocollagen supplements collagen levels in the disrupted articular cartilage. This randomized controlled trial evaluated the effects of the intra-articular injection of atelocollagen for the management of knee pain. DESIGN: Two hundred patients with osteoarthritis, chondromalacia, or other cartilage defects were randomly assigned to receive a 3-mL intra-articular injection of atelocollagen (BioCollagen group) or saline (Placebo group). Clinical improvement was evaluated over a 24-week period using the 100-mm visual analogue scale (VAS), the Western Ontario and McMaster University Osteoarthritis Index (WOMAC), and the 36-item Short-Form Health Survey (SF-36). RESULTS: VAS scores were significantly better in the BioCollagen group as compared with the Placebo group at 24 weeks. More patients in the BioCollagen group reported exceeding 20% and 40% VAS improvements. The WOMAC and SF-36 scores were also significantly improved from baseline after the intra-articular injection of atelocollagen; although, the differences between the BioCollagen and Placebo groups were not significant. There were no unexpected or severe adverse events reported for either group. CONCLUSIONS: The results show that an intra-articular injection of atelocollagen effectively alleviates knee pain, as intended. Therefore, the intra-articular injection of atelocollagen can be considered an alternative solution to controlling knee pain due to osteoarthritis and diverse cartilage defects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it