Consensus on the Rational Use of Antithrombotics in Veterinary Critical Care (CURATIVE): Domain 3—Defining antithrombotic protocols
Bibliographic record
Abstract
OBJECTIVES: To systematically examine the evidence for use of a specific protocol (dose, frequency, route) of selected antithrombotic drugs, in comparisons to no therapy or to other antithrombotic therapies, to reduce the risk of complications or improve outcomes in dogs and cats at risk for thrombosis. DESIGN: Standardized, systematic evaluation of the literature, categorization of relevant articles according to level of evidence (LOE) and quality (Good, Fair, or Poor), and development of consensus on conclusions via a Delphi-style survey for application of the concepts to clinical practice. SETTINGS: Academic and referral veterinary medical centers. RESULTS: Databases searched included Medline via PubMed and CAB abstracts. Eight different antithrombotic drugs were investigated using a standardized Patient, Intervention, Comparison, Outcome (PICO) question format both for dogs and cats, including aspirin, clopidogrel, warfarin, unfractionated heparin (UFH), dalteparin, enoxaparin, fondaparinux, and rivaroxaban, generating a total of 16 worksheets. Most studies identified were experimental controlled laboratory studies in companion animals (LOE 3) with only four randomized controlled clinical trials in companion animals (LOE 1). CONCLUSIONS: Overall, evidence-based recommendations concerning specific protocols could not be formulated for most antithrombotic drugs evaluated, either because of the wide range of dosage reported (eg, aspirin in dogs) or the lack of evidence in the current literature. However, clopidogrel administration in dogs and cats at risk of arterial thrombosis, notably in cats at risk of cardiogenic thromboembolism, is supported by the literature, and specific protocols were recommended. Comparably, aspirin should not be used as a sole antithrombotic in cats with cardiomyopathy. Using the available safety profile information contained in the literature, the panel reached consensus on suggested dosage schemes for most antithrombotics. Significant knowledge gaps were highlighted, which will hopefully drive novel research.
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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 | 0.371 | 0.408 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.015 | 0.008 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".