作者
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
发表日期
2021/11
期刊
Microbiology Spectrum
卷号
9
期号
3
页码范围
e00913-21
出版商
American Society for Microbiology
简介
Enterococcus faecium is a clinically important pathogen that can cause significant morbidity and death. In this study, we aimed to develop a machine learning (ML) algorithm-based rapid susceptibility method to distinguish vancomycin-resistant E. faecium (VREfm) and vancomycin-susceptible E. faecium (VSEfm) strains. A predictive model was developed and validated to distinguish VREfm and VSEfm strains by analyzing the matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) mass spectrometry (MS) spectra of unique E. faecium isolates from different specimen types. The algorithm used 5,717 mass spectra, including 2,795 VREfm and 2,922 VSEfm mass spectra, and was externally validated with 2,280 mass spectra of isolates (1,222 VREfm and 1,058 VSEfm strains). A random forest-based algorithm demonstrated overall good classification performances for the isolates from the specimens, with …
引用总数
20202021202220232024114102