Use of Computed Tomography for Diagnosis and Management of Lumbar Spine Stress Fractures in Two Quarter Horse Racehorses
Bibliographic record
Abstract
Lumbar vertebrae pathology has been recognized as a source of pain and poor performance in racehorses. Imaging of this area was considered unattainable, which limits recognition and management of pathologies. Lumbar spine fractures mainly occur due to repetitive overuse of pre-existing injuries during high-speed racing and are not typically related to external trauma. A 4-year-old Quarter Horse racehorse gelding (case 1) and a 2-year-old Quarter Horse racehorse filly (case 2) were referred to Caesars Entertainment Equine Specialty Hospital for evaluation of acute onset of hind limb paralysis during racing. Case 1 presented clinical signs in the Fall of 2021, after being rested over the winter, the horse was referred for a CT of the lumbar area before returning to racing. The CT revealed a chronic fracture of the opposing endplates of lumbar vertebrae L5 and L6, as well as bilateral spondylosis partially obstructing both intervertebral foramina. Case 2 showed clinical signs in October 2022. Besides the acute bilateral hind limb paralysis, there was also gluteal muscle atrophy, urinary incontinence, and loss of anal and tail tone. A lumbar pathology was suspected, which prompted the decision to perform a CT. Similarly, CT images revealed a displaced, comminuted fracture of the opposing endplates of L5 and L6. This series highlights the importance of CT to diagnose pathology in an area which has been thought inaccessible, and in which a final diagnosis was only reached postmortem. By obtaining this early diagnosis, the veterinarian can make inform decisions on the horse's athletic future. Acknowledgements: There was no proprietary interest or funding provided for this project. Publication History Article published online: 16 September 2024 Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".