<i>In vitro</i> activity and resistance rates of topical antimicrobials fusidic acid, mupirocin and ozenoxacin against skin and soft tissue infection pathogens obtained across Canada (CANWARD 2007–18)
Bibliographic record
Abstract
BACKGROUND: Current antimicrobial susceptibility/resistance data versus skin and soft tissue infection (SSTI) pathogens help to guide empirical treatment using topical antimicrobials. OBJECTIVES: To assess the in vitro activity and resistance rates of fusidic acid, mupirocin, ozenoxacin and comparator agents against pathogens isolated from patients with SSTIs in Canada. METHODS: SSTI isolates of MSSA (n = 422), MRSA (n = 283) and Streptococcus pyogenes (n = 46) obtained from CANWARD 2007-18 were tested using CLSI broth microdilution. Fusidic acid low-level resistance was defined as an MIC of ≥2 mg/L and high-level resistance as an MIC ≥512 mg/L. Mupirocin high-level resistance was defined as an MIC ≥512 mg/L and low-level resistance was an MIC of 2-256 mg/L. RESULTS: Low-level and high-level fusidic acid resistance in MSSA was 10.9% and 1.7%, respectively. Low-level and high-level fusidic acid resistance in MRSA was 10.6% and 3.5%, respectively. High-level mupirocin resistance was identified in 1.4% of MSSA and 14.1% of MRSA, respectively. Versus MSSA, ozenoxacin demonstrated MIC50 and MIC90 of 0.004 and 0.25 mg/L, respectively. Against MRSA, ozenoxacin inhibited all isolates at an MIC of ≤0.5 mg/L, including isolates with ciprofloxacin MICs >2 mg/L, clarithromycin-resistant, clindamycin-resistant, high-level fusidic acid-resistant and high-level mupirocin-resistant isolates. CONCLUSIONS: We conclude that fusidic acid low-level resistance exceeded 10% for both MSSA and MRSA while fusidic acid high-level resistance was ≤3.5%. Mupirocin high-level resistance exceeded 10% in MRSA. Ozenoxacin is active versus SSTI pathogens including MRSA resistant to fluoroquinolones, macrolides, clindamycin, fusidic acid and mupirocin.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".