Mesenchymal stem cells in knee osteoarthritis treatment: A systematic review and meta-analysis
Bibliographic record
Abstract
Stem cells are considered to be one of the greatest potential treatments to cure degenerative diseases. Stem cells injection for knee osteoarthritis (OA) is still a relatively new treatment and has not yet gained popularity. So, the effectiveness, safety and potential of mesenchymal stem cells (MSCs) for knee OA treatment is worthy to be explored. Explore the effectiveness and safety of mesenchymal stem cells (MSCs) in the treatment of knee osteoarthritis. We collected clinical trials using MSCs as treatment for knee OA (before April 2019), including randomized controlled trials (RCTs), retrospective studies and cohort studies. We searched PubMed, EMBASE, Cochrane Library, Web of Science and the ClinicalTrials.gov with keywords (Mesenchymal stem cells [MSCs], Knee osteoarthritis, Effectiveness and Safety), and then performed a systematic review and cumulative metaanalysis of all RCTs and retrospective comparative studies. To evaluate the effectiveness and safety of MSC in knee OA treatment, we applied visual analog scale score, Western Ontario and McMaster Universities Osteo-arthritis Index and adverse events. We included 15 RCTs, two retrospective studies and two cohort studies including a total of 584 knee OA patients in this study. We demonstrated that MSC treatment could significantly decrease visual analog scale in a 12-month follow-up study compared with controls (p < 0.001). MSC therapy also showed significant decreases in Western Ontario and McMaster Universities Osteoarthritis Index scores after the 6-month follow-up (p < 0.001). MSC therapy showed no difference compared with controls (p > 0.05) in adverse events. We suggest that MSC therapy could serve as an effective and safe therapy for clinical application in OA treatment. THE TRANSLATIONAL POTENTIAL OF THIS ARTICLE: This study provided the best available evidence and a wider perspective to MSCs application in the management of knee OA. MSCs therapy will have great translational potential in the clinical treatment of various degenerative diseases once optimum formula and explicit target population are identified.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".