The effects of aging on hydromorphone-induced thermal antinociception in healthy female cats
Bibliographic record
Abstract
INTRODUCTION: This study aimed to evaluate the effects of aging on hydromorphone-induced thermal antinociception in cats. METHODS: In a prospective, randomized, blinded, controlled design, 10 healthy female cats received each of the following treatments intramuscularly: hydromorphone (0.1 mg/kg) and 0.9% saline (0.05 mL/kg) with a 1-week washout between treatments at 6, 9, and 12 months of age. Skin temperature and thermal thresholds (TTs) were recorded before and up to 12 hours after injection. Data were analyzed using a repeated-measures linear mixed model (α = 0.05). RESULTS: After saline treatment, TT was not significantly different from baseline at any time point for any age group. After hydromorphone treatment, TT was significantly higher than baseline at 6 months for up to 1 hour, and at 9 and 12 months for up to 4 hours. Peak TT at 6, 9, and 12 months were 50.4 ± 2.7, 50.9 ± 2.0, and 53.6 ± 2.0°C at 0.5, 1, and 1 hours, respectively. Mean TT was significantly higher after hydromorphone treatment when compared with saline treatment at 9 and 12 months for up to 4 hours but not at 6 months. Magnitude of antinociception was consistently larger at 12 months when compared with 6 months of age. Hydromorphone provided a shorter duration and smaller magnitude of antinociception at 6 months when compared with 9 and 12 months. CONCLUSION: Pediatric cats may require more frequent dosing of hydromorphone than adults.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".