Retrospective analysis of antibacterial susceptibility of Staphylococcus spp. isolated from clinical samples of dogs in Ontario, Canada
Bibliographic record
Abstract
<p style="text-align:justify">Antimicrobial resistance has developed as a major threat worldwide causing a serious risk to global public health. Infections with drug-resistant bacteria are quite challenging to treat with recommended antimicrobials. This retrospective study was conducted to analyse the antibacterial susceptibility pattern of Staphylococcus spp. bacteria isolated from canine patients from two veterinary hospitals in the Niagara Region in Ontario, Canada, from January 2015 to December 2021. The data included 1370 bacterial culture reports received from IDEXX laboratories, out of which 306 specimens (22.3%) were positive for Staphylococcus spp. The results showed that the most prevalent strain of Staphylococcus isolated is Staphylococcus pseudintermedius (48%), followed by methicillin-resistant Staphylococcus spp. (33%), Staphylococcus schleiferi (10%), Staphylococcus aureus (7%) and other Staphylococcus species (2%). The antibiotic susceptibility test results of Staphylococcal isolates revealed a high resistance pattern for beta-lactam antibiotics (32-80%), followed by tetracycline antibiotics (21-47%), macrolides (35-40%), chloramphenicol (15%), fluoroquinolones (28-29%) and the least resistance for amikacin (1%). The results also documented a high prevalence of multi-drug resistance in 55% of the Staphylococcus strains isolated. This study illustrates the antimicrobial resistance among Staphylococcus spp. from dogs in Ontario, Canada. Hence, the strict measures of antibiotic stewardship and judicious use of antimicrobials are highly mandated.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".