Effect of prednisone administration on coagulation variables in healthy<scp>B</scp>eagle dogs
Bibliographic record
Abstract
BACKGROUND: Long-term corticosteroid therapy has been associated with increased risk of thrombotic disease in dogs. OBJECTIVE: The purpose of this prospective study was to use thrombelastography (TEG) and thrombin generation (TG) to detect development of a hypercoagulable state in healthy Beagle dogs receiving oral prednisone. We hypothesized that administration of corticosteroids would result in a hypercoagulable profile on TEG tracings and an increase in TG. METHODS: Six healthy adult Beagles from the University of Montreal's research colony were used to conduct a prospective longitudinal study in which all dogs received 1 mg/kg of prednisone orally once daily for 2 weeks, followed by a 6-week washout period, and then 4 mg/kg of prednisone orally once daily for 2 weeks. TEG tracings on citrated whole blood and TG measurements on frozen-thawed platelet-poor plasma were obtained before prednisone administration (baseline), at the end of the washout period, and at the end of both corticosteroid trials. RESULTS: Significant differences compared with baseline values were obtained for K, α, and MA, with tracings compatible with a hypercoagulable profile following both corticosteroid trials. There was a significant increase in endogenous thrombin potential only after low-dose (1 mg/kg) prednisone. CONCLUSION: Administration of prednisone to healthy Beagles resulted in hypercoagulability as indicated by TEG tracings, whereas the effect on TG was more variable. Further studies are needed to determine the underlying mechanisms of hypercoagulability and its clinical impact.
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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) | 0.001 | 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".