Eurosurveillance · 2019 · 58 citations · 27 references
Life SciencesInfectious DiseasesVeterinary MicrobiologyAntimicrobial ResistanceDiagnostic MicrobiologyMedical MicrobiologyAntibiotic ResistanceAntibiotic Resistance GeneticsAntimicrobial Resistance GenomicsResistance GenesResistance SurveillanceVeterinary Antimicrobial ResistanceAntimicrobial Resistance PatternsEscherichia ColiEscherichia Coli ResistanceMinimum Inhibitory Concentration DeterminationResistance Phenotype PredictionResistance Phenotype SurveillanceSwine Antimicrobial ResistanceWhole Genome Sequencing For Resistance Surveillance
Background Surveillance of commensal Escherichia coli , a possible reservoir of antimicrobial resistance (AMR) genes, is important as they pose a risk to human and animal health. Most surveillance activities rely on phenotypic characterisation, but whole genome sequencing (WGS) presents an alternative. Aim In this retrospective study, we tested 515 E. coli isolated from pigs to evaluate the use of WGS to predict resistance phenotype. Methods Minimum inhibitory concentration (MIC) was determined for nine antimicrobials of clinical and veterinary importance. Deviation from wild-type, fully-susceptible MIC was assessed using European Committee on Antimicrobial Susceptibility Testing (EUCAST) epidemiological cut-off (ECOFF) values. Presence of AMR genes and mutations were determined using APHA SeqFinder. Statistical two-by-two table analysis and Cohen’s kappa (k) test were applied to assess genotype and phenotype concordance. Results Overall, correlation of WGS with susceptibility to the nine antimicrobials was 98.9% for test specificity, and 97.5% for the positive predictive value of a test. The overall kappa score (k = 0.914) indicated AMR gene presence was highly predictive of reduced susceptibility and showed excellent correlation with MIC. However, there was variation for each antimicrobial; five showed excellent correlation; four very good and one moderate. Suggested ECOFF adjustments increased concordance between genotypic data and kappa values for four antimicrobials. Conclusion WGS is a powerful tool for accurately predicting AMR that can be used for national surveillance purposes. Additionally, it can detect resistance genes from a wider panel of antimicrobials whose phenotypes are currently not monitored but may be of importance in the future.
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Interrater reliability: the kappa statistic
Marry L. McHugh · Biochemia Medica · 2012 · 18.6K citations · Full text
Interrater reliability: the kappa statistic.
Mary L. McHugh · PubMed · 2012 · 9.2K citations · Full text
Identification of acquired antimicrobial resistance genes
Ea Zankari, Henrik Hasman, Salvatore Cosentino et al. · Journal of Antimicrobial Chemotherapy · 2012 · 5.2K citations · Full text