Evaluation of antimicrobial prescriptions in dogs with suspected bacterial urinary tract disease
Bibliographic record
Abstract
BACKGROUND: Antimicrobials are commonly used to treat urinary tract disease in dogs. Understanding antimicrobial use is a critical component of antimicrobial stewardship efforts. HYPOTHESIS/OBJECTIVES: To evaluate antimicrobial prescriptions for dogs diagnosed with acute cystitis, recurrent cystitis, and pyelonephritis. ANIMALS: Dogs prescribed antimicrobials for urinary tract disease at veterinary practices in the United States and Canada. MATERIALS AND METHODS: A retrospective review of antimicrobial prescriptions was performed. RESULTS: The main clinical concerns were sporadic bacterial cystitis (n = 6582), recurrent cystitis (n = 428), and pyelonephritis (n = 326). Amoxicillin/clavulanic acid (2702, 41%), cefpodoxime (1024, 16%), and amoxicillin (874, 13%) were most commonly prescribed for sporadic bacterial cystitis. The median prescribed duration was 12 days (range, 3-60 days; interquartile range [IQR], 4 days). Shorter durations were used in 2018 (median, 10 days; IQR, 4 days) compared to both 2016 and 2017 (both median, 14 days; IQR, 4 days; P ≤ .0002). Amoxicillin/clavulanic acid (146, 33%), marbofloxacin (95, 21%), and cefpodoxime (65, 14%) were most commonly used for recurrent cystitis; median duration of 14 days (range, 3-77 days; IQR, 10.5 days). Amoxicillin/clavulanic acid (86, 26%), marbofloxacin (56, 17%), and enrofloxacin (36, 11%) were most commonly prescribed for pyelonephritis; however, 93 (29%) dogs received drug combinations. The median duration of treatment was 14 days (range, 3-77 days; IQR, 11 days). CONCLUSIONS AND CLINICAL IMPORTANCE: Decreases in duration and increased use of recommended first-line antimicrobials were encouraging. Common drug choices and durations should still be targets for antimicrobial stewardship programs that aim to optimize antimicrobial use, concurrently maximizing patient benefits while minimizing antimicrobial use and use of higher tier antimicrobials.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".