A Prospective Study of Clopidogrel Therapy in Dogs with Primary Immune-Mediated Hemolytic Anemia
Bibliographic record
Abstract
BACKGROUND: A major cause of death in dogs with primary immune-mediated hemolytic anemia (pIMHA) is thrombotic disease. Ultralow-dose aspirin (ULDA) is commonly used to prevent thrombosis in dogs with pIMHA; however, the efficacy of antiplatelet agents in dogs with pIMHA is unknown. HYPOTHESIS: The use of clopidogrel (CL), alone or in combination with ULDA, would improve survival to discharge and at 90 days without important adverse effects compared with ULDA alone in dogs with pIMHA treated with standard immunosuppressive therapy. ANIMALS: Twenty-four client-owned dogs with pIMHA. METHODS: Prospective, positive-controlled, unmasked clinical trial with dogs randomized in 3 treatment groups to receive PO ULDA or CL or both. RESULTS: There was no identifiable adverse reaction, evidence of hemorrhage, or increase in transfusion requirements associated with CL therapy, either alone or combined with ULDA, compared with ULDA alone. There was no significant difference between treatment groups with respect to survival to discharge and at 90 days. CONCLUSIONS AND CLINICAL IMPORTANCE: This study suggests that CL therapy, alone or in combination with ULDA, was safe and had similar short-term survival compared with ULDA alone in a small group of dogs with pIMHA able to tolerate oral medications and treated with standard immunosuppressive treatment.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".