Investigation of antimicrobial use and the impact of antimicrobial use guidelines in a small animal veterinary teaching hospital: 1995–2004
Bibliographic record
Abstract
OBJECTIVE: To evaluate patterns of antimicrobial use and the impact of antimicrobial use guidelines at a small animal veterinary teaching hospital. DESIGN: Retrospective study. SAMPLE POPULATION: All antimicrobial prescriptions for dogs and cats admitted to the hospital in 1995 through 2004. PROCEDURE: Pharmacy records were reviewed, and antimicrobial prescriptions for all dogs and cats admitted during the study period were recorded. Amounts of individual drugs dispensed directly to the intensive care and surgical units were determined. Changes in antimicrobial use during the study period were assessed; changes in antimicrobial use patterns in 2000 through 2004 were evaluated to assess the impact of implementation of antimicrobial use guidelines in 2001. RESULTS: There was a significant decrease in prescriptions/1,000 admissions during the study period. From 1995 to 2004, the use of first-generation cephalosporins, fluoroquinolones, penicillins, and trimethoprim-sulfonamides decreased, whereas the use of metronidazole increased. The use of first-generation cephalosporins, fluoroquinolones, and penicillins decreased from 2000 to 2004. First-line drugs accounted for 90.7% of prescriptions during the study period. The use of third-line drugs decreased from 2000 to 2004. CONCLUSIONS AND CLINICAL RELEVANCE: Characterization of antimicrobial use is an important step in defining and evaluating the prudent use of antimicrobials. Whereas the true effect of antimicrobial use guidelines is unclear, these results suggest that the guidelines may have had an effect on antimicrobial prescription patterns in this small animal veterinary teaching hospital. Analysis of objective data regarding antimicrobial use and changes in antimicrobial use patterns over time is important in veterinary practices.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".