Surgical Correction of Traumatic Lateral Patellar Luxation
Bibliographic record
Abstract
OBJECTIVE: To report successful surgical repair of a grade IV lateral patellar luxation in a 437-kg heifer. STUDY DESIGN: Case report. ANIMAL: Seventeen-month-old Holstein heifer (437 kg). METHODS: Diagnosis of traumatic lateral patellar luxation was made based on physical examination, and confirmed on radiographs. Arthroscopic examination of the stifle assessed joint changes. Lateral patellar luxation was surgically repaired using lateral release of the patella and medial imbrication of the joint capsule. RESULTS: The heifer presented nonweight-bearing lameness of the left hind limb (5/5 lameness score). Unilateral grade IV lateral patellar luxation was diagnosed based on physical examination and radiography. Arthroscopic examination of the stifle showed synovitis and cartilage eburnation of the medial articular surface of the patella and of the lateral trochlear ridge of the femur. Lateral release of the patella and medial imbrication of the joint capsule was performed. The heifer remained lame (4.5/5 lameness score) and developed severe disuse muscle atrophy after surgery. By day 112, the heifer was walking easily and was completely weight bearing on the left hindlimb but did have a gait alteration (2/5 lameness score). On day 229, the heifer calved for the first time and lameness was no longer evident. CONCLUSION: This report documents successful surgical treatment of traumatic lateral patellar luxation in a large heifer but additional case evaluation is required to provide an accurate prognosis for this condition and treatment in large cattle.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".