Comparative Plasma and Interstitial Fluid Pharmacokinetics of Meloxicam, Flunixin, and Ketoprofen in Neonatal Piglets
Bibliographic record
Abstract
Piglet castration and tail-docking are routinely performed in the United States without analgesia. Pain medications, predominately nonsteroidal anti-inflammatory drugs, are used in the EU/Canada to decrease pain associated with processing and improve piglet welfare, however, past studies have shown the efficacy and required dose remain controversial, particularly for meloxicam. This study assessed the pharmacokinetics of three NSAIDs (meloxicam, flunixin and ketoprofen) in piglets prior to undergoing routine castration and tail-docking. Five-day-old male piglets (8/group) received one of 3 randomized treatments; meloxicam (0.4 mg/kg), flunixin (2.2 mg/kg), ketoprofen (3.0 mg/kg). Two hours post-dose, piglets underwent processing. Drug concentrations were quantified in plasma and interstitial fluid (ISF) and pharmacokinetic parameters were generated by noncompartmental analysis. Time to peak concentration (Tmax) of meloxicam, flunixin and S(-)-ketoprofen in plasma were 1.21, 0.85 and 0.59h, compared to 2.81h, 3.64h and 2.98h in the ISF, respectively. The apparent terminal half-life of meloxicam, flunixin and S(-)-ketoprofen were 4.39, 7.69 and 3.50h, compared to 11.26h, 16.34h and 5.54h, respectively in the ISF. If drug concentrations in the ISF are more closely related to efficacy than the plasma, then the delay between the Tmax in plasma and ISF may be relevant to the timing of castration in order to provide the greatest analgesic effect.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".