Effects of aspirin, carprofen, deracoxib, and meloxicam on platelet function and systemic prostaglandin concentrations in healthy dogs
Bibliographic record
Abstract
OBJECTIVE: To determine effects of therapeutic dosages of aspirin, carprofen, deracoxib, and meloxicam on platelet function and systemic prostaglandin concentrations in healthy dogs. ANIMALS: 10 hound-crossbred dogs. PROCEDURES: Aspirin (10 mg/kg, PO, q 12 h), carprofen (4.4 mg/kg, PO, q 24 h), deracoxib (2 mg/kg, PO, q 24 h), meloxicam (0.1 mg/kg, PO, q 24 h), and a placebo were administered for 7 days in a random order to each of 10 healthy dogs; there was a 21-day washout period between subsequent treatments. One-stage prothrombin time (PT), activated partial thromboplastin time (aPTT), fibrinogen concentration, and plasma concentrations of thromboxane (TX)B(2) and 6-keto prostaglandin (PG)F(1alpha) were measured before and after treatment administration. Platelet function was assessed by use of a platelet-function analyzer and aggregation. RESULTS: Aspirin, carprofen, and meloxicam did not significantly affect platelet function. Deracoxib caused a mild decrease in platelet aggregation induced by 50microM ADP. Platelet number, Hct, PT, aPTT, and plasma TXB(2) and 6-keto PGF(1alpha) concentrations were unchanged after NSAID administration. Meloxicam administration resulted in a significant decrease in fibrinogen concentration, but results remained within the laboratory reference interval. CONCLUSIONS AND CLINICAL RELEVANCE: Oral administration of commonly used NSAIDs at therapeutic dosages in healthy dogs did not alter plasma TXB(2) and 6-keto PGF(1alpha) concentrations. Deracoxib administration resulted in a minor abnormality in platelet aggregation. Anti-inflammatory doses of aspirin did not affect platelet function as measured by use of optical aggregometry and a platelet-function analyzer. Further evaluation of the effects of aspirin and cyclooxygenase-2-selective inhibitors on hemostasis should be performed.
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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 | 0.001 |
| 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 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".