Effect of carprofen on hemostatic variables in dogs
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect of carprofen on hemostatic variables in clinically normal dogs. ANIMALS: 12 clinically normal Labrador Retrievers. PROCEDURE: 10 dogs (6 females, 4 males) received carprofen (2.2 mg/kg of body weight, PO, q 12 h) for 5 days. Two dogs (untreated control group; 1 female, 1 male) did not receive carprofen. Hemostatic variables (platelet count, activated partial thromboplastin time, prothrombin time, fibrinogen, platelet aggregation, and bleeding time) were assessed for all dogs prior to treatment, on day 5 of treatment, and 2 and 7 days after discontinuation of the drug (days 7 and 12). Serum biochemical variables and Hct were assessed prior to treatment and on days 5 and 12. RESULTS: In dogs receiving carprofen, platelet aggregation was significantly decreased, and onset of aggregation was significantly delayed on days 5, 7, and 12, compared with pretreatment values. Activated partial thromboplastin time was significantly increased on days 5, 7, and 12 over pretreatment values in treated dogs, but values remained within reference ranges. Significant differences were not detected in buccal mucosal bleeding time, other serum biochemical and hemostatic variables, or Hct, compared with pretreatment values and the internal control group. CONCLUSIONS AND CLINICAL RELEVANCE: Administration of carprofen for 5 days causes minor but not clinically important alterations in hemostatic and serum biochemical variables in clinically normal Labrador Retrievers. Carprofen is commonly used to treat osteoarthritis and chronic pain in dogs, but prior to this study, its effect on platelet aggregation and hemostatic variables was unknown.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".