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Record W4413770268 · doi:10.1093/jac/dkaf217

Gram-negative pathogens from Canadian hospitals: 17 years of results from the CANWARD study (2007–23)

2025· article· en· W4413770268 on OpenAlexafffundabout
George G. Zhanel, Melanie Baxter, Philippe Lagacé‐Wiens, Andrew Walkty, Jeff Fuller, Ross Davidson, Joseph M. Blondeau, Susan M. Poutanen, Christian Lavallée, Laura Mataseje, George R. Golding, Frank Schweizer, Denice C. Bay, Andrew Denisuik, Jeremy Li, James A. Karlowsky, Heather J. Adam

Bibliographic record

VenueJournal of Antimicrobial Chemotherapy · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsSinai Health SystemPublic Health Agency of CanadaRoyal University HospitalQueen Elizabeth II Health Sciences CentreHôpital Maisonneuve-RosemontWestern UniversityUniversity of Manitoba
FundersSandoz CanadaMerck CanadaUniversity of ManitobaCell Science Research FoundationPfizer
KeywordsMedicinePathogenic organismMicrobiologyIntensive care medicineBiology

Abstract

fetched live from OpenAlex

OBJECTIVES: CANWARD is a Canadian Antimicrobial Resistance Alliance (CARA)/Health Canada partnered national surveillance study established in 2007 to annually assess the in vitro activities of commonly tested and recently approved antimicrobial agents for bacterial pathogens isolated from patients receiving care in Canadian hospitals. METHODS: In total, 34 155 Gram-negative pathogens were tested using the CLSI reference broth microdilution method. RESULTS: In total, 39.4%, 37.1%, 17.7% and 5.8% of isolates tested were from respiratory, blood, urine and wound specimens, respectively; 31.1%, 23.9%, 19.0%, 18.5% and 7.5% of isolates were from patients in medical wards, emergency rooms, ICUs, hospital clinics and surgical wards. In total, 51.8% of isolates were from male patients; and 10.1%, 40.7% and 49.2% of isolates were from patients aged ≤17, 18-64 and ≥65 years. The most common Gram-negative pathogens received were: Escherichia coli (34.9%), Pseudomonas aeruginosa (17.5%) and Klebsiella pneumoniae (11.6%). An ESBL-producing phenotype was identified in 8.4% of E. coli and 5.6% of K. pneumoniae isolates. Percent susceptible values for E. coli included: 100% for meropenem/vaborbactam and imipenem/relebactam; >99% for ceftazidime/avibactam, meropenem and ceftolozane/tazobactam; 95.6% for piperacillin/tazobactam; and 73.9% for ciprofloxacin. Percent susceptible values for K. pneumoniae included: >99% for meropenem/vaborbactam, imipenem/relebactam, ceftazidime/avibactam and meropenem; 97.4% for ceftolozane/tazobactam; 91.9% for piperacillin/tazobactam; and 87.0% for ciprofloxacin. Percent susceptible values for P. aeruginosa included: 96.6% for ceftolozane/tazobactam; 92.6% for ceftazidime/avibactam; 92.0% for imipenem/relebactam; 79.9% for piperacillin/tazobactam; ceftazidime 78.1%; 78.0% for meropenem; and 68.6% for ciprofloxacin. CONCLUSIONS: The CANWARD surveillance study has provided 17 years of reference antimicrobial susceptibility testing data.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.252

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.009
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.005
GPT teacher head0.240
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes3
Has abstractyes

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