Clinical Efficacy and Safety of Two Cycles of Intra-Articular Injection of Porcine Atelocollagen Versus Hyaluronic Acid in Knee Osteoarthritis
Bibliographic record
Abstract
(1) Background: Knee osteoarthritis (KOA) induces pain, stiffness, and impaired mobility, particularly in aging populations. Despite providing symptom relief, the long-term efficacy of intra-articular hyaluronic acid (HA) injections remains unclear. With its longer intra-articular residence time and potential chondroprotective effects, porcine-derived atelocollagen is an alternative to HA. We aimed to compare the safety and efficacy of collagen versus HA injections in symptomatic KOA. (2) Methods: This retrospective observational study included 40 patients with KOA who received either two cycles of collagen or HA injections at 6-month intervals. Clinical outcomes were assessed using the visual analog scale (VAS) and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) at baseline and 6 months after the first and second injections (Cycle 1 and Cycle 2, respectively). Patient satisfaction and adverse events were recorded. Non-inferiority analysis was conducted for VAS and WOMAC score changes. (3) Results: Significant intragroup improvements in VAS and WOMAC scores were noted after each injection cycle (p < 0.05), albeit without significant between-group differences, non-inferiority of collagen to HA based on predefined margins, and comparable patient-reported satisfaction (>85% reported improvement after each cycle), with similar incidence of mild adverse events (collagen: 20%, HA: 25%, p = 0.705). (4) Conclusions: Intra-articular collagen injections were clinically non-inferior to HA in reducing pain and improving function in patients with KOA across two treatment cycles. Given its favorable safety profile and potential structural benefits, collagen may serve as a viable alternative injectable therapy for the non-surgical management of KOA.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 teacher head, 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".