Evaluation of urine sucrose concentration for detection of gastric ulcers in horses
Bibliographic record
Abstract
OBJECTIVE: To evaluate the use of sucrose permeability testing to detect ulcers in the gastric squamous mucosa of horses. ANIMALS: 13 adult horses ranging from 5 to 19 years of age. PROCEDURE: Following induction of gastric ulcers by intermittent feed deprivation, horses underwent sucrose permeability testing (administration of sucrose by nasogastric intubation followed by collection of urine at 2 and 4 hours after intubation) and gastric endoscopy. Squamous ulcers were assigned a severity score (range, 0 to 3) by use of an established scoring system. Horses were subsequently administered omeprazole for 21 days, and sucrose testing and endoscopy were repeated. Pair-wise comparisons of urine sucrose concentration were made between horses with induced ulcers before and after omeprazole treatment. Urine sucrose concentrations also were compared on the basis of ulcer severity score. RESULTS: Urine sucrose concentrations and ulcer severity scores were significantly higher in horses with induced ulcers before omeprazole treatment than after treatment. Urine sucrose concentrations were significantly higher for horses with ulcer severity scores > 1. Use of a cut-point value of 0.7 mg/mL revealed that the apparent sensitivity and specificity of sucrose permeability testing to detect ulcers with severity scores > 1 was 83% and 90%, respectively. Results were similar after adjusting sucrose concentrations for urine osmolality. CONCLUSIONS AND CLINICAL RELEVANCE: Urine sucrose concentration appears to be a reliable but imperfect indicator of gastric squamous ulcers in horses. Sucrose permeability testing may provide a simple, noninvasive test to detect and monitor gastric ulcers in horses.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".