Characterization of carbapenem-resistant and XDR Pseudomonas aeruginosa in Canada: results of the CANWARD 2007–16 study
Bibliographic record
Abstract
OBJECTIVES: Carbapenem-resistant Pseudomonas aeruginosa are emerging worldwide with increasing reports of carbapenemase-producing isolates. Carbapenem-resistant isolates may also be XDR. This study characterized carbapenem-resistant and XDR P. aeruginosa isolated from patients receiving care at Canadian hospitals from 2007 to 2016. METHODS: Antimicrobial susceptibility testing was performed using CLSI broth microdilution methods. PCR was used to detect carbapenemases (GES, KPC, NDM, IMP, VIM, OXA-48) and other resistance markers; specific carbapenemase gene variants were identified by DNA sequencing. Genetic relatedness was assessed by MLST and PFGE. RESULTS: From 2007 to 2016, 3864 isolates of P. aeruginosa were collected; 466 (12.1%) isolates were carbapenem resistant. The prevalence of carbapenem-resistant P. aeruginosa reached a peak of 17.3% in 2014. Colistin (94% susceptible) and ceftolozane/tazobactam (92.5%) were the most active agents against carbapenem-resistant P. aeruginosa. XDR P. aeruginosa comprised 4.5% of isolates; they were found to be genetically diverse and remained susceptible to colistin and ceftolozane/tazobactam. Only 4.3% (n = 20) of carbapenem-resistant P. aeruginosa harboured a carbapenemase; most were blaGES-5 (35%, n = 7). Wide genetic diversity was observed among carbapenem-resistant P. aeruginosa with >200 different sequence types identified. CONCLUSIONS: Although the prevalence of carbapenem-resistant P. aeruginosa in Canada spiked in 2014 and 2015, carbapenemase-producing P. aeruginosa remain rare with only 20 (4.3%) isolates identified over a 10 year period. Broad genetic diversity was observed among both carbapenem-resistant and XDR phenotypes of P. aeruginosa. Pan-drug-resistant P. aeruginosa have not yet been identified 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".