In Vivo Effects of a Single Intra‐Articular Injection of 2% Lidocaine or 0.5% Bupivacaine on Articular Cartilage of Normal Horses
Bibliographic record
Abstract
OBJECTIVE: To assess the effects of an intra-articular (IA) lidocaine or bupivacaine injection on synovial fluid (SF) biomarkers of cartilage metabolism. STUDY DESIGN: Experimental. ANIMALS: Horses (n = 6). METHODS: The study had 2 components, each with an identical design: the first arm assessed the effects of bupivacaine (0.5%) IA in the intercarpal joints and, after a 2-week washout period, the second was conducted to evaluate the effects of IA lidocaine (2%) in the tarsocrural joints. The mares were randomly assigned to receive the test local anesthetic in the target joint or the placebo (0.9% NaCl) in the contralateral joint. After a 2-week washout period, treatments were reversed, yielding 6 joints for each treatment. SF samples were collected for measurement of biomarkers of cartilage metabolism. RESULTS: IA bupivacaine or lidocaine induced a significant increase in both markers of cartilage matrix synthesis (CS846-aggrecan and CPII-type II collagen) suggesting an anabolic effect. Bupivacaine also resulted in an unanticipated decrease in both collagen degradation markers (C2C and C1,2C). CONCLUSIONS: These results reveal an anabolic effect of single IA injections of local anesthetics on cartilage metabolism. Although collagen degradation biomarker results were not increased, it is possible that the anabolic response is because of an undetected cartilage insult, and requires further investigation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".