Repeated intra-articular injections of umbilical cord-derived mesenchymal stem cells for knee osteoarthritis: a phase I, single-arm study
Bibliographic record
Abstract
INTRODUCTION: Stem cell therapy has emerged as an effective treatment for multiple diseases, and some studies also demonstrate that it may be a promising treatment for osteoarthritis (OA). However, few studies have clarified the safety of repeated intra-articular injection of human umbilical cord-derived mesenchymal stem cells (UC-MSCs). To promote its application in treating OA, we conducted an open-label trial to investigate the safety of repeated intra-articular injections of UC-MSCs. METHODS: Fourteen patients with OA (Kellgrene-Lawrence grade 2 or 3) who received repeated intra-articular injections of UC-MSCs were evaluated in three months of follow-up. The primary outcomes were the adverse events, and the second outcomes included visual analog scale (VAS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) scores and SF-12 quality of life score. RESULTS: A total of 5 of 14 patients (35.7%) experienced transient adverse reactions, which resolved spontaneously. All patients showed some improvement in knee function limitation and pain after receiving stem cell therapy. VAS score 6.0 to 3.5, WOMAC score 26.0 to 8.5, MOCART score 42.0 to 58.0, SF-12 score 39.0 to 46.0. CONCLUSION: Repeated intra-articular injection of UC-MSCs demonstrates safety in treating OA and does not induce serious adverse events. This treatment may transiently improve symptoms in patients with knee OA and may be a potential therapeutic option for OA.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".