Diagnostic needle arthroscopy of the tarsocrural joint in standing sedated horses
Bibliographic record
Abstract
OBJECTIVE: To develop and assess a needle arthroscopic technique to diagnose conditions of the tarsocrural joint (TCj) in standing sedated horses. STUDY DESIGN: Experimental study. SAMPLE POPULATION: Six cadaveric hind limbs (phase 1) and six healthy horses (Phase 2). METHODS: In phase 1, each TCj was examined with a 1.2-mm-needle arthroscope. Suitability of the needle arthroscope and degree of joint visualization with traditional arthroscopic approaches were assessed. In phase 2, the feasibility of the procedure was assessed in six standing healthy horses. A custom-made splint and base were developed to maintain joint flexion during the procedure. RESULTS: Thorough evaluation of the dorsal intra-articular structures of the TCj via dorsomedial and dorsolateral approaches was possible in both phases. The procedure was feasible, quickly performed, and well tolerated by all horses. Complications consisted of moderate movement (2/6 horses) and hemarthrosis (3/6 horses). CONCLUSION: Diagnostic standing needle arthroscopy of the TCj allowed thorough evaluation of the dorsal aspect of the joint while avoiding the cost and risks associated with general anesthesia. Inadvertent puncture of the dorsomedial vasculature with the cannula and obturator led to significant hemarthrosis. CLINICAL IMPACT: Needle arthroscopy of the TCj offers an alternative diagnostic tool when traditional imaging techniques (radiography and ultrasonography) are unrewarding or nondiagnostic. The technique is conceived mainly for diagnostic purposes, but its use during short interventions warrants 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".