Mesenchymal stromal cells improve outcomes in equine carpus and fetlock osteoarthritis
Bibliographic record
Abstract
Background: Mesenchymal stromal cells (MSCs) are widely used for osteoarthritis (OA) treatment. Optimizing dose, timing, and safety while comparing efficacy with standard therapies like hyaluronic acid (HA) is essential for their standardization. Objectives: To assess the safety and efficacy of eCB-MSCs in client-owned horses with fetlock or carpus OA. Study design: Prospective blinded randomized clinical study. Methods: Horses of any breed, age, sex, or sport horse discipline diagnosed by blocking with fetlock or carpus OA were randomly assigned to receive either 10 or 20 million eCB-MSCs in hyaluronic acid (HA), while the control group received 3 ml of HA alone. Subjective lameness examinations were performed at baseline, 3- and 6- weeks post-treatment; additionally, 24-72 hours post-injection, horses were evaluated for adverse reactions. Follow-up surveys were sent to owners 18-weeks after treatment. Results: A total of 27 client-owned horses were enrolled. No significant adverse reactions occurred. There were no significant differences in lameness outcomes between treatment groups (HA: 1.7 ± 1.24 [1.22-2.27]; 10-MSC+HA: 1.2 ± 1.27 [0.67-1.73]; 20-MSC+HA: 1.1 ± 1.28 [0.55-1.64] grades) (P > 0.05) or by treatment by time (P > 0.05). All groups, irrespective of treatment, improved by week 6 by 0.5 ± 0.65 [0.2-0.8] grades (P < 0.05). Although return-to-work rates were not significantly different between treatment groups (P > 0.05), both MSC groups had higher rates of return to the same or higher work levels compared to HA-only (89%, 78%, and 56%, respectively). Main limitations: This study aimed to assess the safety and efficacy of MSC treatment in client-owned horses. It expected higher exercise return rates at 18 weeks for MSC groups (10 or 20 million). However, unexpectedly high returns in the HA group rendered the study underpowered. Based on observed rates, 30 horses per group would be needed for confident conclusions favouring MSCs.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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".