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Record W2982092853 · doi:10.1093/ofid/ofz360.203

128. Adequacy of Commonly Prescribed Antimicrobials for Empiric Coverage of Gram-Negative Bacterial Pathogens Recovered from the Bloodstream of Patients Attending Emergency Rooms in Canada: Analysis of Data from the CANWARD Study, 2007 to 2018

2019· article· en· W2982092853 on OpenAlexaffabout
Andrew Walkty, Heather J. Adam, Melanie Baxter, Amina Henni, Philippe Lagacé‐Wiens, James A. Karlowsky, George G. Zhanel

Bibliographic record

VenueOpen Forum Infectious Diseases · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsUniversity of ManitobaManitoba Health
Fundersnot available
KeywordsMeropenemMedicinePiperacillinMicrobiologyEnterobacter cloacaePiperacillin/tazobactamTazobactamBroth microdilutionProteus mirabilisAntimicrobialCeftriaxoneEmpiric therapyCefepimeEnterobacterCiprofloxacinPseudomonas aeruginosaKlebsiella pneumoniaeAntibioticsAntibiotic resistanceBiologyEscherichia coliMinimum inhibitory concentrationBacteriaImipenem

Abstract

fetched live from OpenAlex

Abstract Background Inadequate empiric antimicrobial therapy for Gram-negative bacteremia is associated with adverse clinical outcomes. The purpose of this study was to evaluate the proportion of Gram-negative bacterial isolates recovered from the bloodstream of patients attending Canadian emergency rooms (ERs) that remain susceptible to commonly prescribed antimicrobials. Methods Annually from 2007 to 2018, sentinel hospitals across Canada collected bloodstream isolates from patients attending ERs as part of the CANWARD study. Susceptibility testing was performed using broth microdilution as described by CLSI (data analysis limited to Gram-negative bacteria in the top 10 pathogens), with current CLSI breakpoints applied. Extended-spectrum β-lactamase (ESBL)-producing isolates were confirmed using the CLSI disk diffusion method. Results Gram-negative bacteria among the top 10 bloodstream pathogens for patients seen at ERs across Canada were: Escherichia coli (n = 2,414), Klebsiella pneumoniae (n = 573), Pseudomonas aeruginosa (n = 211), Proteus mirabilis (n = 119), and Enterobacter cloacae (n = 114). Aggregate susceptibility of these isolates to common antimicrobials was as follows (% susceptible [S]): meropenem 99.4% S, piperacillin–tazobactam 98.5% S, gentamicin 93.3% S, ceftriaxone 88.1% S, ciprofloxacin 81.4% S, TMP-SMX 73.5% S. The most active antimicrobials evaluated vs. E. coli were meropenem (100% S), piperacillin–tazobactam (98.8% S), and ceftriaxone (93.3% S). Ceftriaxone susceptibility among E. coli isolates declined from 95.4% in 2007 to 89.8% in 2018. The average proportion of E. coli isolates that harbored an ESBL enzyme increased from 3.4% in the first three study years to 8.4% in the last three study years. The most active antimicrobials evaluated vs. K. pneumoniae isolates were meropenem (99.7% S), piperacillin–tazobactam (98.8% S), gentamicin (97.7% S), and ceftriaxone (96.9% S). Conclusion The most consistently active antimicrobials for empiric treatment of patients at Canadian ERs with Gram-negative bacteremia are meropenem and piperacillin–tazobactam. Ceftriaxone susceptibility among E. coli has declined over the last 12 years, mostly related to an increase in ESBL-producing isolates. Disclosures All authors: No reported disclosures.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.042
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.023
GPT teacher head0.278
Teacher spread0.255 · 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".

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Citations0
Published2019
Admission routes2
Has abstractyes

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