Association of Veterinary Hematology and Transfusion Medicine (AVHTM) Transfusion Reaction Small Animal Consensus Statement (TRACS) Part 2: Prevention and monitoring
Bibliographic record
Abstract
OBJECTIVE: To systematically review available evidence to develop guidelines for the prevention of transfusion reactions and monitoring of transfusion administration in dogs and cats. DESIGN: Evidence evaluation of the literature (identified through Medline searches through Pubmed and Google Scholar searches) was carried out for identified transfusion reaction types in dogs and cats. Evidence was evaluated using PICO (Population, Intervention, Comparison, Outcome) questions generated for each reaction type. Evidence was categorized by level of evidence (LOE) and quality (Good, Fair, or Poor). Guidelines for prevention and monitoring were generated based on the synthesis of the evidence. Consensus on the final recommendations and a proposed transfusion administration monitoring form was achieved through Delphi-style surveys. Draft recommendations and the monitoring form were made available through veterinary specialty listservs and comments were incorporated. RESULTS: Twenty-nine guidelines and a transfusion administration monitoring form were formulated from the evidence review with a high degree of consensus CONCLUSIONS: This systematic evidence evaluation process yielded recommended prevention and monitoring guidelines and a proposed transfusion administration form. However, significant knowledge gaps were identified, demonstrating the need for additional research in veterinary transfusion medicine.
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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 | 0.086 | 0.161 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.011 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".