Comparative pharmacokinetics of meloxicam in clinically normal horses and donkeys
Bibliographic record
Abstract
OBJECTIVE: To determine the disposition of a bolus of meloxicam (administered IV) in horses and donkeys (Equus asinus) and compare the relative pharmacokinetic variables between the species. ANIMALS: 5 clinically normal horses and 5 clinically normal donkeys. PROCEDURES: Blood samples were collected before and after IV administration of a bolus of meloxicam (0.6 mg/kg). Serum meloxicam concentrations were determined in triplicate via high-performance liquid chromatography. The serum concentration-time curve for each horse and donkey was analyzed separately to estimate standard noncompartmental pharmacokinetic variables. RESULTS: In horses and donkeys, mean +/- SD area under the curve was 18.8 +/- 7.31 microg/mL/h and 4.6 +/- 2.55 microg/mL/h, respectively; mean residence time (MRT) was 9.6 +/- 9.24 hours and 0.6 +/- 0.36 hours, respectively. Total body clearance (CL(T)) was 34.7 +/- 9.21 mL/kg/h in horses and 187.9 +/- 147.26 mL/kg/h in donkeys. Volume of distribution at steady state (VD(SS)) was 270 +/- 160.5 mL/kg in horses and 93.2 +/- 33.74 mL/kg in donkeys. All values, except VD(SS), were significantly different between donkeys and horses. CONCLUSIONS AND CLINICAL RELEVANCE: The small VD(SS) of meloxicam in horses and donkeys (attributed to high protein binding) was similar to values determined for other nonsteroidal anti-inflammatory drugs. Compared with other species, horses had a much shorter MRT and greater CL(T) for meloxicam, indicating a rapid elimination of the drug from plasma; the even shorter MRT and greater CL(T) of meloxicam in donkeys, compared with horses, may make the use of the drug in this species impractical.
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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) | 0.000 | 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".