Gastric Ulcers in Standardbred Racehorses: Prevalence, Lesion Description, and Risk Factors
Bibliographic record
Abstract
This study was performed to estimate the prevalence of gastric ulcers in Standardbred racehorses, to describe the lesion score and location, and to identify potential risk factors. Two hundred seventy-five (275) Standardbred horses from 5 training centers and 2 racetracks in Quebec, Canada, were studied. Historical data for the 2 months before examination were recorded for each horse, and the presence of gastric ulcers was determined by gastroscopy. A previously reported scoring system that used grades 0-3 for gastric lesions was used. Overall, 121 horses (44.0%; 95% CI, 38.1-50.1%) had gastric ulcers. The prevalence of gastric ulcers was significantly higher (P < .0001) in actively racing horses (63.3%; 95% CI, 54.7-71.2%) than in horses at rest. Multivariate analysis defined that horses in racing (OR = 9.29; 95% CI, 3.55-24.3) were significantly more likely to have gastric ulcers than horses at rest and that trotters (OR = 2.23; 95% CI, 1.28-3.86) were more likely to have gastric ulcers than pacers. The number of lesion sites (P < .0001) and poor body condition (P < .0001) were significantly associated with lesion scores. Gastric ulcers are highly prevalent in Standardbred racehorses. Furthermore, actively racing horses and trotters are more likely to have gastric ulcers. Also, poor body condition in Standardbred racehorses may be an indication that gastric ulcers are present and that lesion scores are high. The cause-and-effect relationship between poor body condition and the presence of gastric ulcers is unclear.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".