Clinically Applicable System for Rapidly Predicting Enterococcus faecium Susceptibility to Vancomycin
Hsin-Yao Wang, Chia-Ru Chung, Chao-Jung Chen, Ko-Pei Lu, Yi-Ju Tseng, Tzu-Hao Chang, Min-Hsien Wu, Wan-Ting Huang, Ting-Wei Lin, Tsui-Ping Liu, Tzong-Yi Lee, Jorng-Tzong Horng, Jang-Jih Lu
Abstract
A modified binning method was incorporated to cluster MS shifting ions into a set of representative peaks based on a large-scale MS data set of clinical VRE fm and VSE fm isolates, including 2,795 VRE fm and 2,922 VSE fm isolates. Predictions with the algorithm were significantly more accurate than empirical antibiotic use, the accuracy of which was 0.50, based on the local epidemiology.
Topics & Concepts
Enterococcus faeciumEnterococcusMass spectrometryVancomycinMicrobiologyBiologySet (abstract data type)AlgorithmComputational biologyMass spectrumAntibioticsCluster (spacecraft)WorkflowComputer scienceStreptococcaceaePathogenData setGeneticsAntimicrobial Resistance in StaphylococcusBacterial Identification and Susceptibility TestingSepsis Diagnosis and Treatment