Antimicrobial Drug Use in Veterinary Medicine
Bibliographic record
Abstract
Abstract Recognizing the importance of antimicrobial resistance and the need for veterinarians to aid in efforts for maintaining the usefulness of antimicrobial drugs in animals and humans, the Board of Regents of the American College of Veterinary Internal Medicine charged a special committee with responsibility for drafting this position statement regarding antimicrobial drug use in veterinary medicine. The Committee believes that veterinarians are obligated to balance the well-being of animals under their care with the protection of other animals and public health. Therefore, if an animal's medical condition can be reasonably expected to improve as a result of treatment with antimicrobial drugs, and the animal is under a veterinarian's care with an appropriate veterinarian-client-patient relationship, veterinarians have an obligation to offer antimicrobial treatment as a therapeutic option. Veterinarians also have an obligation to actively promote disease prevention efforts, to treat as conservatively as possible, and to explain the potential consequences associated with antimicrobial treatment to animal owners and managers, including the possibility of promoting selection of resistant bacteria. However, the consequences of losing usefulness of an antimicrobial drug that is used as a last resort in humans or animals with resistant bacterial infections might be unacceptable from a public or population health perspective. Veterinarians could therefore face the difficult choice of treating animals with a drug that is less likely to be successful, possibly resulting in prolonged or exacerbated morbidity, to protect the good of society. The Committee recommends that voluntary actions be taken by the veterinary profession to promote conservative use of antimicrobial drugs to minimize the potential adverse effects on animal or human health. The veterinary profession must work to educate all veterinarians about issues related to conservative antimicrobial drug use and antimicrobial resistance so that each individual is better able to balance ethical obligations regarding the perceived benefit to their patients versus the perceived risk to public health. Specific means by which the veterinary profession can promote stewardship of this valuable resource are presented and discussed in this document.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".