Canine Cushing syndrome elevates oxidative stress that is attenuated by trilostane
Bibliographic record
Abstract
Objective: To evaluate oxidant-antioxidant status in hyperadrenocorticism (HAC) dogs at diagnosis and after trilostane (Adrestan). Methods: This study, conducted from June 2024 through March 2025, enrolled 25 dogs with HAC and 21 healthy control dogs. Serum malondialdehyde (MDA) concentration, superoxide dismutase (SOD) activity, total oxidant status (TOS), total antioxidant capacity (TAC), and oxidative stress index (OSI) were analyzed before and after treatment. Results: The study included 25 dogs with HAC (14 treated with trilostane, 1 mg/kg, twice daily for 45 days) and 21 healthy controls. At baseline, HAC dogs had significantly elevated oxidative stress markers (MDA, 10.28 μmol/L; TOS, 35.68 μmol H2O2 equivalent (Equiv)/L; OSI, 4.60 arbitrary units (AU)) compared to controls, whereas SOD (44.77 U/mL) and TAC (0.96 mmol/L) remained similar. After trilostane treatment, oxidative stress significantly improved, including decreases in MDA (7.91 → 4.28 μmol/L), TOS (30.82 → 17.85 μmol H2O2 Equiv/L), and OSI (3.61 → 2.14 AU); increased SOD (46.25 → 56.06 U/mL nonsignificant); but no change in TAC (0.97 → 0.94 mmol/L). Conclusions: These findings demonstrated elevated oxidative stress in HAC dogs that was effectively ameliorated by trilostane. Clinical Relevance: This study first provides comprehensive documentation of oxidative stress in dogs with HAC and its mitigation after trilostane treatment. Significant oxidative imbalance in canine HAC supports monitoring redox parameters as part of disease management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".