Transplantation of three mesenchymal stem cells for knee osteoarthritis, which cell and type are more beneficial? a systematic review and network meta-analysis
Bibliographic record
Abstract
BACKGROUND: In knee osteoarthritis (KOA), treatments involving knee injections of bone marrow-derived mesenchymal stem cells (BM-MSC), adipose tissue-derived mesenchymal stem cells (AD-MSC), or umbilical cord-derived mesenchymal stem cells (UC-MSC) have shown promise in alleviating symptoms. However, which types of mesenchymal stem cells (MSCs) have the best therapeutic outcomes remain uncertain. METHOD: We systematically searched PubMed, OVID, Web of Science, and the Cochrane Library until January 1, 2024. The study evaluated five endpoints: Visual Analog Score (VAS) for Pain, Range of Motion (ROM), Whole-Organ Magnetic Resonance Imaging Score (WORMS), Western Ontario McMaster Universities Osteoarthritis Index (WOMAC), and adverse events (ADs). Standard meta-analysis and network meta-analysis were performed using Stata 16.0. RESULTS: Fifteen studies involving 585 patients were included in the meta-analysis. Standard meta-analysis revealed significant improvements with MSCs in VAS score (P < 0.001), knee ROM (P < 0.001), and WOMAC (P < 0.016) compared to traditional therapy. In the network meta-analysis, autologous MSCs significantly improved VAS score [SMD = 2.94, 95% CI (1.90, 4.56)] and knee ROM [SMD = 0.26, 95% CI (0.08, 0.82)] compared to traditional therapy. Similarly, BM-MSC significantly improved VAS score [SMD = 0.31, 95% CI (0.11, 0.91)] and knee ROM [SMD = 0.26, 95% CI (0.08, 0.82)] compared to hyaluronic acid. However, compared with traditional therapy, autologous or allogeneic MSCs were associated with more adverse reactions [SMD = 0.11, 95% CI (0.02, 0.59)], [SMD = 0.13, 95% CI (0.002, 0.72)]. Based on the surface under the cumulative ranking results, autologous BM-MSC showed the most improvement in ROM and pain relief in KOA patients, UC-MSC (SUCRA 94.1%) were most effective for positive WORMS, and AD-MSC (SUCRA 70.6%) were most effective for WOMAC-positive patients. CONCLUSION: MSCs transplantation effectively treats KOA patients, with autologous BM-MSC potentially offering more excellent benefits.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.042 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".