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Record W3096476086 · doi:10.1017/ice.2020.1156

Genomic Epidemiology of Carbapenemase-Producing Enterobacterales (CPE) in Toronto, Canada

2020· article· en· W3096476086 on OpenAlexaffabout
Alainna Jamal, Victoria Williams, Jerome A. Leis, Nathalie Tijet, Sandra Zittermann, Roberto G. Melano, Laura Mataseje, Michael R. Mulvey, Allison McGeer

Bibliographic record

VenueInfection Control and Hospital Epidemiology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentrePublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsPulsed-field gel electrophoresisMolecular epidemiologyEpidemiologySNPCluster (spacecraft)Transmission (telecommunications)Single-nucleotide polymorphismBiologyPopulationGenotypeGeneticsMedicineInternal medicineGeneEnvironmental health

Abstract

fetched live from OpenAlex

Objective: We investigated whether whole-genome sequencing (WGS) data altered interpretations of clonal transmission as determined by conventional epidemiology and pulsed-field gel electrophoresis (PFGE) at a tertiary-care hospital (hospital Z, HZ). Methods: We included all carbapenemase-producing Enterobacterales (CPE)–colonized or –infected patients identified via population-based surveillance from 2007 through 2018, who were admitted to HZ during and/or in the year prior to or following CPE detection. HZ reported clonal transmission clusters using epidemiology and PFGE for CPE identified at HZ or reported to HZ by other hospitals as potentially acquired at HZ. We assessed single-nucleotide polymorphism (SNP) phylogenies and case epidemiology. Results: Overall, 85 CPE-colonized or -infected patients were included: 50 were detected at HZ and 35 were detected at another local hospital but were admitted to HZ in the previous or following year. HZ reported 6 transmission clusters (Table 1). SNP analyses confirmed clusters B, C, E, and F. In cluster A, SNP analyses cast doubt on 2 of 9 cases (possibly representing plasmid transmission) but also identified 2 additional cases with isolates highly related (0–3 SNP differences) to other isolates. One case may be the index case: a travel-related case who stayed on the same unit as case 1, 4 months before case 1 detection. The second case stayed in a room previously occupied by 5 cluster A cases. In cluster D, SNP analyses found 1 additional case whose isolate was highly related (ie, 17–19 SNP differences) to other isolates. This case was identified a year before cluster D at another hospital that shares patients with HZ; however, the case’s admission to HZ was after all cluster D cases were detected and no direct epidemiologic link was identified. Conclusions: WGS data can identify cases belonging to transmission clusters that conventional epidemiologic methods missed. Funding: None Disclosures: Allison McGeer reports funds to her institution from Pfizer and Merck for projects for which she is the principal investigator. She also reports consulting fees from Sanofi-Pasteur, Sunovion, GSK, Pfizer, and Cidara

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.087
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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 teacher head, 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

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