Intra-Articular Injection of Autologous Adipose Tissue-Derived Mesenchymal Stem Cells for the Treatment of Knee Osteoarthritis: A Phase IIb, Randomized, Placebo-Controlled Clinical Trial
Bibliographic record
Abstract
Mesenchymal stem cells (MSCs) have been the focus of an emerging treatment for osteoarthritis. However, few studies reported about outcomes of an intra-articular injection of autologous adipose-derived mesenchymal stem cells (AD-MSCs). This study aimed to assess the efficacy and safety of a single intra-articular injection of AD-MSCs for patients with knee osteoarthritis. It was a prospective double-blinded, randomized controlled, phase IIb clinical trial. AD-MSCs were administered for 12 patients (MSC group), and the group was compared with 12 knees with injection of normal saline (control group) up to 6 months. All procedures were performed in the outpatient clinic. Primary outcome measure was the Western Ontario and McMaster Universities Osteoarthritis index (WOMAC) score. Secondary outcome measure included various clinical and radiologic examination, and safety after injection. Change of cartilage defect after injection was evaluated using magnetic resonance imaging (MRI). Single injection of AD-MSCs led to a significant improvement of the WOMAC score at 6 months. In the control group, there was no significant change in the WOMAC score at 6 months. No serious adverse events were observed in both groups during the follow-up period. In MRI, there was no significant change of cartilage defect at 6 months in MSC group whereas the defect in the control group was increased. An intra-articular injection of autologous AD-MSCs provided satisfactory functional improvement and pain relief for patients with knee osteoarthritis in the outpatient setting, without causing adverse events at 6 months' follow-up. Larger sample size and long-term follow-up are required. Stem Cells Translational Medicine 2019;8:504-511.
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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 | 0.001 | 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) | 0.004 | 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".