P265 Efficacy and safety of intraarticular stem cell administration (retrospective study)
Bibliographic record
Abstract
Please confirm that an ethics committee approval has been applied for or granted: Yes: I’m uploading the Ethics Committee Approval as a PDF file with this abstract submission Background and Aims Osteoarthritis (OA) is a chronic degenerative joint disease. In recent years, adipose-derived mesenchymal stem cells (AD-MSCs) have emerged as a promising treatment for regenerative medicine. The application of stem cells to degenerated joints has been shown to restore articular cartilage, alleviate pain, and improve quality of life. Methods This study retrospectively reviewed 86 patients with knee and hip osteoarthritis who underwent intra-articular stem cell therapy. Patients were evaluated using visual analog scale (VAS), Western Ontario and McMaster University Osteoarthritis Index (WOMAC), Lequesne, Short Form-36 (SF-36) scores, and radiological scores on current radiographs before and after the procedure. Additionally, adverse events were monitored during the 6-month follow-up period. Results The patients’ VAS scores decreased significantly from 8 at baseline to 3 and 2 at 1st and 6th months, respectively, according to the Friedman test (p < 0.001). WOMAC total score was 65, 24 in the 1st month after treatment and 18 in the 6th month after treatment. Lequesne and SF-36 scores also improved significantly from baseline to 1st and 6th months. These measurements were statistically significant (p<0.001). No adverse events were reported. Mild transient pain and swelling were noted in a few patients in the small patient group, but no major side effects occurred. Conclusions The intra-articular application significantly improved outcomes in patients and did not cause any side effects, suggesting that intra-articular stem cell application may be a promising option in the treatment of osteoarthritis. However, prospective RCTs with larger sample size and long-term follow-up are needed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".