Diagnostic evaluation of urea nitrogen/creatinine ratio in dogs with gastrointestinal bleeding
Bibliographic record
Abstract
BACKGROUND: Urea nitrogen/creatinine ratio (UCR) is a marker for upper gastrointestinal bleeding (GIB) in people. OBJECTIVES: To assess the usefulness of UCR to predict occult GIB and distinguish upper from lower GIB in dogs. ANIMALS: Eighty-nine dogs with GIB and 65 clinically healthy dogs. Dogs were grouped according to 65 overt GIB and 24 occult GIB, and based on lesion localization (37 upper, 13 lower, and 8 both). METHODS: Seventy-four dogs were included retrospectively and 15 dogs prospectively. Serum urea nitrogen and creatinine concentrations, UCR, hemoglobin concentration, hematocrit, mean corpuscular volume, and mean corpuscular hemoglobin concentration were compared between groups. Logistic regression models were fitted to assess if variables could distinguish occult GIB from being healthy and upper from lower GIB. RESULTS: The UCR was significantly higher in dogs with overt GIB compared to control dogs (P = .02) and dogs with occult GIB (P = .05). The UCR was not significantly associated with occult GIB vs being healthy, or upper vs lower GIB (P > .05 each). Dogs with higher hemoglobin concentration and hematocrit had significantly lower odds of having occult GIB than being healthy (P < .0001 each). CONCLUSIONS AND CLINICAL IMPORTANCE: The UCR does not seem to be a clinically useful marker of occult GIB and appears to have poor discriminatory ability between upper and lower GIB. An increased UCR in a dog without signs of overt GIB, especially if its hematocrit is within the middle or upper reference interval, does not appear to warrant prompt prescription of gastrointestinal protectants.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.000 | 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".