Effects of dexmedetomidine on glucose homeostasis in healthy cats
Bibliographic record
Abstract
Objectives Alpha(α)2-agonist administration has been documented to increase blood glucose concentrations in many species. The aim of this study was to further describe the effect of dexmedetomidine on glucose and its regulatory hormones in healthy cats. Methods A randomized crossover study using eight healthy cats with a 14 day washout period was used to assess the effect of dexmedetomidine (10 μg/kg IV) and saline on glucose, cortisol, insulin, glucagon and non-esterified fatty acid (NEFA) concentrations at 0, 20, 60, 120 and 180 mins post-administration. Glucose:insulin ratios were calculated for each time point. Results Within the dexmedetomidine group, significant differences ( P <0.05) were detected: increased median (range) blood glucose concentrations at 60 mins (11.55 mmol/l [5.9–16.6 mmol/l]) and 120 mins (12.0 mmol/l [6.1–13.8 mmol/l]) compared with baseline (6.05 mmol/l [4.8–13.3 mmol/l]); decreased glucagon concentrations at 120 mins (3.8 pmol/l [2.7–8.8 pmol/l]) and 180 mins (4.7 pmol/l [2.1–8.2 pmol/l]) compared with baseline (11.85 pmol/l [8.3–17.2 pmol/l]); decreased NEFA concentrations at 60 mins (0.281 mmol/l [0.041–1.357 mmol/l]) and 120 mins (0.415 mmol/l [0.035–1.356 mmol/l]) compared with baseline (0.937 mmol/l [0.677–1.482 mmol/l]); and significantly larger ( P <0.05) glucose:insulin ratios at 60 mins compared with baseline. Insulin and cortisol concentrations were not significantly changed after dexmedetomidine administration. Conclusions and relevance Feline practitioners should be aware of the endocrine effects associated with the use of α2-agonists, particularly when interpreting blood glucose concentrations. The transient effects of dexmedetomidine on glucose homeostasis are unlikely to significantly affect clinical practice.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".