Distribution and antimicrobial susceptibility profile of pathogens recovered from the bloodstream of Canadian patients: results from the CANWARD study (2007–23)
Bibliographic record
Abstract
OBJECTIVES: Bloodstream infections are associated with significant morbidity and mortality. The purpose of this study was to determine the most common pathogens causing bacteraemia among Canadian patients and to evaluate their antimicrobial susceptibility profiles. METHODS: Annually from 2007 to 2023, bloodstream isolates from patients admitted to or evaluated at Canadian hospitals were collected by sentinel laboratories (CANWARD surveillance study). Antimicrobial susceptibility testing was performed by broth microdilution. RESULTS: In total, 26 067 bloodstream isolates were obtained over 17 years of the CANWARD study (14 954 from inpatients, 11 107 from outpatients, no patient location for six isolates). The five most common pathogens were Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Staphylococcus epidermidis and Streptococcus pneumoniae. There was little variation in pathogen distribution over time but certain pathogens were more common among inpatients (e.g. Candida albicans, Enterobacter cloacae, Pseudomonas aeruginosa) while others were more common among outpatients (e.g. Streptococcus pyogenes, Streptococcus agalactiae). The proportion of ESBL-producing E. coli increased from 4.5% (2007-09) to 12.7% (2019-23). The proportion of ESBL-producing K. pneumoniae increased from 2.0% (2007-09) to 7.1% (2018-23). Vancomycin susceptibility among Enterococcus faecium decreased from 84.9% (2007-09) to 69.0% (2019-23). In contrast, the proportions of S. aureus that were MRSA and P. aeruginosa that had a difficult-to-treat resistance phenotype were relatively stable. CONCLUSIONS: There has been little variation in the pathogens commonly causing bacteraemia among Canadian patients over the course of the CANWARD study, but some resistant phenotypes (e.g. ESBL-producing E. coli, ESBL-producing K. pneumoniae, VRE) are being encountered more frequently in recent years.
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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 | 0.001 |
| 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".