Effects of Prednisone on Blood Lactate Concentrations in Healthy Dogs
Bibliographic record
Abstract
BACKGROUND: Glucocorticoids affect carbohydrate and lactate metabolism. HYPOTHESIS: Administration of prednisone to healthy dogs will result in clinically relevant hyperlactatemia. ANIMALS: Twelve healthy adult Beagle dogs. METHODS: Prospective, controlled experimental study. Twelve healthy adult Beagles were divided into 2 groups (3 of each sex per group). One group served as control. The other group received 2 treatments: low, 1 mg/kg prednisone PO q24h for 2 weeks; high, 4 mg/kg prednisone PO q24h for 2 weeks. A washout period of 6 weeks separated the treatments. Blood samples were drawn for whole blood lactate measurement on day (D) 0, D4, and D14 and measured in duplicate. RESULTS: Compared with the control group, low and high groups had significantly higher blood lactate concentrations at D4 and D14. There was no difference at D0. There was no effect of time within the control group. In the low and high groups, blood lactate concentration was increased at D4 and D14 versus D0. Blood lactate concentration was greater in the high group than the low group at D14 only. CONCLUSIONS AND CLINICAL IMPORTANCE: Dogs treated with prednisone experience statistically significant increases in blood lactate concentrations, which can result in type B hyperlactatemia. In such cases, improving tissue perfusion, treatment for the commonest form of hyperlactatemia (type A) would be unnecessary.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".