Using Genetic Distance from Archived Samples for the Prediction of Antibiotic Resistance in Escherichia coli.

ABSTRACT: The rising rates of antibiotic resistance increasingly compromise empirical treatment. Knowing the antibiotic susceptibility of a pathogen's close genetic relative(s) may improve empirical antibiotic selection. Using genomic and phenotypic data for Escherichia coli isolates from three separate clinically derived databases, we evaluated multiple genomic methods and statistical models for predicting antibiotic susceptibility, focusing on potentially rapidly available information, such as lineage or genetic distance from archived isolates. We applied these methods to derive and validate the prediction of antibiotic susceptibility to common antibiotics. We evaluated 968 separate episodes of suspected and confirmed infection with Escherichia coli from three geographically and temp

SUBMITTER: MacFadden DR 

PROVIDER: S-EPMC7179619 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature