Characterization of antimicrobial-resistant <i>Escherichia coli</i> causing urinary tract infections in dogs: Passive surveillance in Saskatchewan, Canada 2014 to 2018
Bibliographic record
Abstract
Abstract Background Urinary tract infections (UTIs) are common in dogs and can be caused by multidrug-resistant Escherichia coli (E coli). Objective To describe the frequency and mechanisms of antimicrobial resistance (AMR) among E coli causing UTIs in dogs in Western Canada during a 4-year surveillance period. Animals Urine from 516 dogs. Methods From November 2014 to 2018, 516 nonduplicate E coli isolates from the urine of dogs were collected from a diagnostic laboratory. Susceptibility testing was determined for a panel of 14 antimicrobials belonging to 7 drug classes. Resistant isolates were screened for the presence of extended-spectrum beta-lactamases (ESBLs), AmpC β-lactamases, and plasmid-mediated quinolone resistance (PMQR) genes. Epidemiological relationships were assessed by MLST. Results 80.2% (414/516) of isolates were susceptible to all antimicrobials tested. There was no significant increase in the proportion of isolates resistant to any of the tested antimicrobials during the study period. Resistance to ampicillin was the most common (14.9%, 77/516). Overall, 12 isolates had blaCMY-2-type AmpC β-lactamases, and 7 produced CTX-M-type ESBLs. A single isolate had the aac(6′)-Ib-cr PMQR gene. The qnr and qepA determinants were not detected. A single isolate belonging to the pandemic lineage ST131 was identified. Conclusion Escherichia coli isolated from the urine of dogs in our region remain susceptible to first-line therapies, though resistance, particularly to the aminopenicillins, warrants monitoring. This is the first description of E coli ST131 from a companion animal in Canada.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".