Antimicrobial Prescribing in Dogs and Cats in Australia: Results of the Australasian Infectious Disease Advisory Panel Survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Investigations of antimicrobial use in companion animals are limited. With the growing recognition of the need for improved antimicrobial stewardship, there is urgent need for more detailed understanding of the patterns of antimicrobial use in this sector. OBJECTIVES: To investigate antimicrobial use for medical and surgical conditions in dogs and cats by Australian veterinarians. METHODS: A cross-sectional study was performed over 4 months in 2011. Respondents were asked about their choices of antimicrobials for empirical therapy of diseases in dogs and cats, duration of therapy, and selection based on culture and susceptibility testing, for common conditions framed as case scenarios: 11 medical, 2 surgical, and 8 dermatological. RESULTS: A total of 892 of the 1,029 members of the Australian veterinary profession that completed the survey satisfied the selection criteria. Empirical antimicrobial therapy was more common for acute conditions (76%) than chronic conditions (24%). Overall, the most common antimicrobial classes were potentiated aminopenicillins (36%), fluoroquinolones (15%), first- and second-generation cephalosporins (14%), and tetracyclines (11%). Third-generation cephalosporins were more frequently used in cats (16%) compared to dogs (2%). Agreement with Australasian Infectious Disease Advisory Panel (AIDAP) guidelines (generated subsequently) was variable ranging from 0 to 69% between conditions. CONCLUSIONS AND CLINICAL IMPORTANCE: Choice of antimicrobials by Australian veterinary practitioners was generally appropriate, with relatively low use of drugs of high importance, except for the empirical use of fluoroquinolones in dogs, particularly for otitis externa and 3rd-generation cephalosporins in cats. Future surveys will determine whether introduction of the 2013 AIDAP therapeutic guidelines has influenced prescribing habits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it