Vaginal microbiota molecular profiling and diagnostic performance of artificial intelligence-assisted multiplex PCR testing in women with bacterial vaginosis: a single-center experience.

Journal: Frontiers in cellular and infection microbiology
PMID: 38644962

Abstract

BACKGROUND: Bacterial vaginosis (BV) is a most common microbiological syndrome. The use of molecular methods, such as multiplex real-time PCR (mPCR) and next-generation sequencing, has revolutionized our understanding of microbial communities. Here, we aimed to use a novel multiplex PCR test to evaluate the microbial composition and dominant lactobacilli in non-pregnant women with BV, and combined with machine learning algorithms to determine its diagnostic significance.

Authors

  • Sihai Lu
    National Engineering Research Center for Miniaturized Detection Systems, Northwest University, Xi'an, China.
  • Zhuo Li
    Biostatistics Unit, Mayo Clinic, Jacksonville, FL, United States.
  • Xinyue Chen
    National Engineering Research Center for Miniaturized Detection Systems, Northwest University, Xi'an, China.
  • Fengshuangze Chen
    National Engineering Research Center for Miniaturized Detection Systems, Northwest University, Xi'an, China.
  • Hao Yao
    Department of Materials Physics and New Energy Device, School of Materials Science and Engineering, Hefei University of Technology, Hefei 230009, China.
  • Xuena Sun
    Department of Research and Development, Shaanxi Lifegen Co., Ltd., Xi'an, China.
  • Yimin Cheng
    Department of Obstetrics and Gynecology, The Hospital of Xi' an Shiyou University, Xi'an, China.
  • Liehong Wang
    Department of Obstetrics and Gynecology, Qinghai Red Cross Hospital, Qinghai, Xining, China.
  • Penggao Dai
    National Engineering Research Center for Miniaturized Detection Systems, Northwest University, Xi'an, China.

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