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Assessing vaginal microbiome through Vaginal Microecology Evaluation System as a predictor for in vitro fertilization outcomes: a retrospective study

  • Quan Tian
  • , Shengxi Jin
  • , Guangmin Zhang
  • , Yujie Liu
  • , Jianxin Liu
  • , Xiuming Tang
  • , Yufeng Li
  • , Jiane Liu
  • , Yifei Liu
  • , Zheng Wang

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: This study aims to evaluate the effectiveness of the Vaginal Microecology Evaluation System (VMES) in assessing the dynamics of the vaginal microbiome (VM) throughout the process of in vitro fertilization and embryo transfer (IVF-ET). Furthermore, it seeks to explore the potential correlation between distinct types of VM ecology and the success rate of IVF-ET. Methods: This study employed VMES to ascertain the composition of the VM. Data were collected from infertile women who underwent their initial IVF-ET treatment for tubal factor between January 2018 and December 2021. A retrospective analysis of pregnancy outcomes resulting from their fresh embryo transfer was conducted to determine the predictive significance of the vaginal microenvironment. Results: We demonstrate that VMES is able to predict IVF-ET outcomes in patients diagnosed with Bacterial Vaginosis (BV). Notably, a discernible shift in the VM was observed in a decent subset of patients following Controlled Ovarian Stimulation (COS), though this phenomenon was not universal across all participants. Specifically, there was a noteworthy increase in the proportion of patients exhibiting BV and uncharacterized dysbiosis subsequent to COS. Furthermore, our investigation revealed a significant correlation between VM and both the live birth rate and early miscarriage rate. Employing a multivariable logistic regression model, we identified that VM status pre-COS, VM status post-COS, patient age, and the number of embryos transferred emerged as independent predictors of the live birth rate. Conclusion: Our study suggests that, during IVF-ET treatment, the VMES can effectively detect changes in the VM, which are strongly correlated with the pregnancy outcome of IVF-ET procedures.

Original languageEnglish (US)
Article number1380187
JournalFrontiers in Endocrinology
Volume15
DOIs
StatePublished - 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Endocrinology, Diabetes and Metabolism

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