Ex vivo COX‐1 and COX‐2 inhibition in equine blood by phenylbutazone, flunixin meglumine, meloxicam and firocoxib: Informing clinical NSAID selection
Bibliographic record
Abstract
Summary Newer cyclo‐oxygenase‐2 (COX‐2) selective nonsteroidal anti‐inflammatory drugs (NSAIDs), such as firocoxib, are proposed to reduce inhibition of cyclo‐oxygenase‐1 (COX‐1) and avoid undesirable side effects, while continuing to inhibit inflammation associated with COX‐2. However, COX selectivity is typically based on in vitro testing, which may not provide sufficient information critical for treatment selection. This study investigated the pharmacokinetics and ex vivo COX‐1 and COX‐2 inhibition of phenylbutazone, flunixin meglumine, meloxicam and firocoxib. Horses (n = 3) were administered one of the four drugs, in a randomised cross‐over design, with 3‐week washout periods. For each drug, three doses were given and sampling performed. Drug plasma concentrations, thromboxane B 2 (TXB 2 ) and prostaglandin E 2 (PGE 2 ) were determined. After one dose, TXB 2 and PGE 2 levels were significantly higher in horses administered firocoxib compared to flunixin meglumine. Following the third dose, TXB 2 levels in horses administered firocoxib and meloxicam were significantly higher compared to flunixin meglumine or phenylbutazone; all drugs reduced PGE 2 to a similar degree. The mean plasma half‐lives were 5.97 ± 0.47, 4.74 ± 0.14, 8.24 ± 3.74 and 47.42 ± 7.41 h for phenylbutazone, flunixin meglumine, meloxicam and firocoxib, respectively. Firocoxib and meloxicam exhibited significantly less COX‐1 inhibition compared to flunixin meglumine and phenylbutazone; all drugs inhibited COX‐2. The plasma half‐life of firocoxib was longer than the other NSAIDs, including meloxicam. Data from this study have important clinical relevance and should be used to inform practitioners’ drug selection of a COX‐1 sparing or traditional NSAID and dose selection and to provide knowledge of the duration for the four NSAIDs studied.
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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 | 0.001 | 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 | 0.000 |
| 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".