Identification of multidrug- and carbapenem-resistant Acinetobacter baumannii in Canada: results from CANWARD 2007
Bibliographic record
Abstract
OBJECTIVES: Multidrug-resistant (MDR) Acinetobacter baumannii is a growing concern in many countries. This report describes patient demographics, antimicrobial susceptibilities and molecular characteristics of A. baumannii cases identified through the Canadian Ward Surveillance Study (CANWARD). In addition, clinical cases involving MDR carbapenem-resistant A. baumannii are also detailed in this report. METHODS: From January to December 2007, 12 hospital centres across Canada submitted pathogens from clinics, emergency rooms, intensive care units and medical/surgical wards as part of the CANWARD study. MICs were determined using microbroth dilution (CLSI). PCR and sequence analysis identified OXA genes among carbapenem-resistant isolates. PFGE was used to determine genetic relatedness and compare representatives of the Midlands 2 strain, OXA-23 clone 1 or 2, T strains and isolates collected from military sources. RESULTS: This study identified A. baumannii in 0.33% (n = 26) of infections. The majority of isolates remained susceptible to the antimicrobials tested, however, 7.7% (n = 2) displayed an MDR phenotype, including resistance to carbapenems. In one isolate bla(OXA-58) was found to be the likely cause of carbapenem resistance while the other isolate had an insertion sequence element upstream of its intrinsic bla(OXA-51). The clinical data of these two isolates suggest that one is travel-related while the source of the other remains unknown. CONCLUSIONS: A. baumannii infections from Canadian hospitals were relatively low. Carbapenem-resistant MDR A. baumannii were also rare and unrelated to previously observed isolates from military sources. Continued surveillance in Canada is suggested in order to determine if such organisms will become a problem.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| 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) | 0.001 | 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".