Ultrasound‐guided periarticular injections of the sacroiliac region in horses: A cadaveric study
Bibliographic record
Abstract
REASON FOR PERFORMING STUDY: The traditional techniques for injection of the sacroiliac (SI) region are based on external landmarks. Because of the depth of the SI joint and pathological modifications, SI injections are sometimes challenging in horses. HYPOTHESIS: An ultrasound-guided techniques would allow placement of the needle without depending on external landmarks. METHODS: Fourteen pelvic specimens were isolated from mature horses. A 20 cm bent spinal needle was positioned with ultrasonographic guidance under both iliac wings aiming for SI joints using 5 approaches: cranial, craniomedial, medial and 2 caudal approaches. The length of needle inserted was recorded and 2 ml of latex injected. The distance from latex to the closest sacral articular margin, the contact between latex and the SI interosseous ligament or the contact with the neurovascular structures emerging from the greater sciatic foramen were recorded at the time of dissection. RESULTS: Latex was identified under the iliac wing in all injections but one. The distance from the latex to the closest sacral articular margin was significantly shorter (P = 0.02) for the 2 caudal approaches compared to the cranial, craniomedial and medial approaches. Contact between latex and the SI interosseous ligament was significantly more frequent (P = 0.01) with the cranial, craniomedial and medial approaches (38/73) compared to the caudal approaches (1/24). Contact between latex and the neurovascular structures was significantly less frequent (P = 0.005) for the cranial and craniomedial approaches (0/47) compared to the medial and caudal approaches (8/60). Four erratic injections were encountered. CONCLUSIONS: Ultrasonographic guidance allowed the needle to engage under the iliac wing without being dependent on external landmarks. The caudal approaches allowed deposition of liquid extremely close to the SI joint although retroperitoneal injections occurred. CLINICAL RELEVANCE: Each approach has advantages/drawbacks that could be favoured for selected purposes, but additional work is required to evaluate them on clinical cases.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".