Characterization of carbapenem-resistant <i>Pseudomonas aeruginosa</i> in Canadian hospitals: 6 years of the CANWARD study (2018–23)
Bibliographic record
Abstract
OBJECTIVES: Antimicrobial resistance in Pseudomonas aeruginosa is of increasing concern in Canada, leading to limited treatment options and poor clinical outcomes. Herein we characterized carbapenem-resistant P. aeruginosa identified through the Canadian national surveillance program CANWARD. METHODS: Antimicrobial susceptibility for 1725 P. aeruginosa isolates was assessed using broth microdilution and 2024 CLSI breakpoints. WGS of carbapenem-resistant isolates was used to identify STs, resistance and virulence markers. Genetic relatedness was further assessed using cgMLST for select STs. RESULTS: From 2018 to 2023, CANWARD collected 1725 P. aeruginosa isolates, of which 371 (21.5%) were carbapenem-resistant. The majority of carbapenem-resistant P. aeruginosa were isolated from respiratory specimens of male patients aged 18-65 years living in central Canada. Only 0.8% (n = 3) of the carbapenem-resistant isolates harboured a carbapenemase gene. WGS identified mutations associated with OprD dysfunction, MexAB-OprM efflux and AmpC overexpression in 73.6%, 1.1% and 4.9% of isolates, respectively. Most isolates (98.1%) harboured at least one of the following class D β-lactamase genes: OXA-2, OXA-5, OXA-10 or OXA-50-like subfamily. Wide genetic diversity was observed with 151 different STs identified. The most common STs were ST17 (4.6%), ST27 (4.6%) and high-risk clones ST235 (4.3%), ST244 (3.5%), ST253 (6.4%) and ST357 (2.7%). cgMLST clusters were identified amongst 34.9% of the high-risk clones, suggesting clonal dissemination. CONCLUSIONS: Currently, >20% of clinical isolates of P. aeruginosa in Canada are carbapenem-resistant. Genetic evidence indicates that clonal dissemination of high-risk clones is occurring in Canada. High-risk clones are virulent and often MDR. Continued surveillance of P. aeruginosa is important.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".