Platelet‐rich plasma is safe for intra‐articular and peri‐articular cervical facet joint injections in the horse
Bibliographic record
Abstract
Summary Background No safety study has been conducted regarding platelet‐rich plasma (PRP) usage in cervical facet joints. Objectives To determine whether intra‐ and/or peri‐articular injections of PRP in cervical facet joints in the horse are safe. Study design Prospective, multi‐centre, safety study. Methods PRP was injected via ultrasound guidance into the cervical and/or cervicothoracic facet joints in horses with diagnosed cervical complaints. Data recorded for each case included: breed, sex, age, primary reason for treatment, list of which facet joints were injected, the volume of PRP injected, whether the PRP was injected intra‐articular or peri‐articular and gauge of needle used. Data were collected at three time points: prior to treatment, 48 h after treatment and a minimum of 30 days after treatment. At each time point, owners/trainers were asked to assess the level of pain the horse was suffering on a 0–10 (no pain to worst) scale. At the final evaluation, the owners/trainers were also asked if the treatment met their expectations on a 0–5 scale. Results No adverse events were reported. The average pain scores prior to treatment, at 48 h and at 30 days were 3.8, 3.4 and 1.1 respectively. At no point did any horse have an increase in its reported pain level. Main limitations Since PRP is not classified as a drug, it does not come with a label indicating items such as dosage or route of administration. Thus, methodologies will vary among veterinarians. This was a nonblinded study; ideally, owners/trainers should be blinded to the intervention. Additionally, this study only involved 17 horses. Conclusions PRP appears to be safe for cervical and/or cervicothoracic facet joint injections in the horse. Evidence for efficacy was also recorded by means of owner/trainer reporting that the injections overwhelmingly met their expectations.
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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 | 0.003 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".