Mesenchymal stem cells therapy for the treatment of non-union fractures: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: This meta-analysis aimed to pool the existing evidence to determine the clinical efficacy and safety of mesenchymal stem cells (MSC) in patients with non-unions. METHODS: A systematic search in PubMed and Scopus was performed until October 2024 to gather pertinent studies. The inclusion criteria included participants with non-unions, the intervention of MSC administration, a comparator of standard treatment (bone graft), and outcomes focused on healing rate, healing time, or side effects. The Jadad score Newcastle-Ottawa Scale (NOS) was used to assess the risk of bias in randomized and non-randomized studies, respectively. Moreover, GRADE criteria were used to assess the quality of evidence. Using a random effects model, odds ratios (OR) with 95% confidence intervals (CIs) were calculated for healing and complication rates, while standardized mean differences (SMD) with their 95% CIs were used to assess the impact of MSC therapy on bone union time. RESULTS: Twenty-one studies, with 866 patients, were included. The bone healing rates were 44% at 3 months, 73% at 6 months, 90% at 9 months, and 86% at 12 months, eventually reaching 91% after 12 months of follow-up. MSC therapy, with or without scaffolds, was linked to higher odds of bone healing rate at 3 and 6 months, compared to bone grafts as the standard care (OR = 1.69). The time to union following the treatment was 6.30 months (95%CI: 86-96%), with patients treated with MSC/Scaffold experiencing a shorter time compared to MSC alone (5.85 vs. 6.36 months). MSC therapy significantly decreased bone union time (SMD:-0.54 months, 95% CI: -0.75 to -0.33). The complication rate was 1% (MSC/Scaffold: 0%, MSC alone: 2%), with MSC alone or MSC/Scaffold showing a lower risk than the standard care (OR = 0.41, 95% CI: 0.22-0.78). CONCLUSION: MSC is a potential adjunct therapy for patients with non-union fractures. CLINICAL TRIAL NUMBER: Not applicable.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.000 | 0.001 |
| 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".