MétaCan
Menu
Back to cohort
Record W3096182404 · doi:10.1017/ice.2020.693

Clinical and Genetic Characteristics of Extended-Spectrum Beta-Lactamase–Producing Enterobacteriaceae Among Canadian Children

2020· article· en· W3096182404 on OpenAlexaffabout
Nisha Thampi, Jennifer Bowes, Roberto G. Melano, Nathalie Tijet, Robert Slinger

Bibliographic record

VenueInfection Control and Hospital Epidemiology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsPublic Health OntarioAgricultural Research Institute of OntarioChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsInterquartile rangeMultilocus sequence typingCephalosporinEnterobacteriaceaeMedicineBeta-lactamaseIncidence (geometry)AntibioticsInfection controlFecesMicrobiologyInternal medicineBiologyGenotypeEscherichia coliIntensive care medicineGenetics

Abstract

fetched live from OpenAlex

Background: Infections with extended-spectrum β-lactamase–producing Enterobacteriaceae (ESBL-E) in nonoutbreak settings have not demonstrated the presence of dominant strains. Our objective was to determine the incidence, clinical characteristics, and genetic characteristics of ESBL-E infections among a group of Canadian children. Methods: From 2012 through 2017, patients aged ≤18 years with first-episode ESBL-E infections who presented at a pediatric center were reviewed. All clinical isolates were phenotypically identified in the laboratory as ESBL-producers. Demographic and clinical data were collected, including comorbid conditions, presence of devices, and previous antibacterial exposure. Community-associated infection was defined as a positive culture from a sterile site within the first 48 hours of hospital admission and no healthcare exposure during the preceding year. Isolates were sent to the Public Health Ontario Laboratory for whole-genome sequencing. Multilocus sequence typing was used to determine clonal relationship. Results: During the study period, 102 patients were identified with first-episode ESBL-E infection, and the proportion of ESBL-E isolates among all clinical isolates of E. coli and Klebsiella spp increased from 0.6% to 2.6% between 2012 and 2017, respectively (P = .001). The median age was 1 year (interquartile range, 0.8–5 years). Women comprised 66% of cases. No comorbid conditions were noted among 58 patients (57%), and 24% had previous antibiotic exposure, most frequently a cephalosporin (16%). ESBL-E was most frequently isolated in the urine (91%) and least frequently in the blood (2.2%) and was predominantly Escherichia coli (90%). Infection was most frequently diagnosed in the outpatient setting (61%); there were 11 healthcare-associated infections. Whole-genome sequencing of ESBL-E isolates revealed predominance of blaCTX-M-15 (63 isolates, 62%) and blaCTX-M-27 (16%) genes, and sequence type (ST) 131 (41%). Mutations conferring fluoroquinolone nonsusceptibility were noted among 62 isolates (61%), most frequently associated with ST131 (38 of 62 isolates, 61%) and among all 5 isolates with ST1193, an emerging multidrug-resistant E. coli clone. In addition, 15 patients had recurrence of ESBL-E infection at median of 113 days (IQR, 26–208); blaCTX-M-27 was found in 33% of recurrent infections compared to 12% of primary infections (P = 0.045). Conclusions: This study is the first in Canada to provide whole-genome sequencing data regarding ESBL-E in a pediatric population. The gene blaCTX-M-15 and ST131 clone were predominant. More than 60% of infections were community associated and demonstrated cross resistance to fluoroquinolones. With 76% of infections in antibiotic-naïve children, ESBL-E is a public health concern, and a One Health approach is critical to understanding the epidemiology and curbing the spread of multidrug-resistant Enterobacteriaceae. Funding: None Disclosures: None

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)0.000
metaresearch head score (Gemma)0.002
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 score0.066
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.011
GPT teacher head0.259
Teacher spread0.248 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueInfection Control and Hospital EpidemiologySame topicAntibiotic Resistance in BacteriaFrench-language works237,207