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Record W4388655672 · doi:10.1128/spectrum.03116-23

The diagnostic accuracy of the GeneXpert ESBL- <i>ampC</i> prototype assay for rapid PCR-based detection of extended-spectrum beta-lactamase genes directly from urine

2023· article· en· W4388655672 on OpenAlexaff
Sofie C. M. Tops, Claire Schapendonk, Jordy P. M. Coolen, Fred C. Tenover, Isabella A. Tickler, Willem J. G. Melchers, Heiman Wertheim

Bibliographic record

VenueMicrobiology Spectrum · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGeneXpert MTB/RIFUrineMicrobiologyBeta-lactamaseCephalosporinBiologyAntibioticsMedicineVirologyGeneTuberculosisInternal medicineEscherichia coliGeneticsSputumPathology

Abstract

fetched live from OpenAlex

ABSTRACT The emerging prevalence of extended-spectrum beta-lactamase (ESBL) producing Enterobacterales has implications for the empirical treatment of common infections, such as complicated urinary tract infections. To provide adequate treatment, while avoiding empirical therapy with last resort carbapenems, rapid identification of ESBL-containing pathogens is desirable. Routine urine samples were collected between February and July 2021 in two Dutch clinical medical microbiology laboratories according to a predefined list containing certain culture characteristics. All urine samples were screened for the presence of ESBL genes ( bla CTX-M2 , bla CTX-M14 , and bla CTX-M15 ) with random-access quantitative PCR (qPCR) using the Cepheid GeneXpert ESBL- ampC prototype assay. The qPCR and microbiological culture results were compared. After the calculation of the sensitivity and specificity, discrepancies were investigated by whole-genome sequencing. In total, 276 urine samples were available for ESBL analysis (94 ESBL culture positive and 182 ESBL culture negative). The sensitivity and specificity for detection of ESBL genes were 90.4% and 98.4%, respectively. In nine samples (9.6%), no ESBL genes were detected with GeneXpert, while in the microbiological culture, an ESBL-positive organism was isolated. This was mainly explained by non-GeneXpert ESBL genes: bla SHV -family ( n = 6; 75.0%), bla TEM -family ( n = 1; 12.5%), and bla SRT -family ( n = 1; 12.5%). The positive and negative predictive values in a hypothetical clinical scenario with a 15% ESBL prevalence were 0.91 and 0.98, respectively. Regarding ampC , the specificity appears to be satisfactory, but the sensitivity is low. The Cepheid GeneXpert ESBL assay could be beneficial for the fast and accurate detection of ESBL genes in regions where the epidemiology of ESBL genes coincides with the targets in the panel. IMPORTANCE Early identification of complicated urinary tract infections caused by ESBL-producing Enterobacterales has the potential to limit the use of carbapenems to those patients without alternative antibiotic options and avoid the empirical use of carbapenems in patients without ESBL-producing bacteria. The purpose for such a test will differ by setting and ESBL prevalence rates. Countries with low ESBL rates and cephalosporins as empiric treatment (e.g., The Netherlands) will need a rule-in test to decide to use carbapenems, while countries with high ESBL rates and empiric carbapenem treatment will need a rule-out test for ESBLs to de-escalate therapy early. Anyway, such as a test would—at least theoretically—improve patient care and reduce selective pressure for the emergence of carbapenem resistance.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.776

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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 designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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