Using Vaginal Microbiota Analysis to Predict Premature Birth in Pregnant Women at Risk

What this Trial Is About

Researchers are studying pregnant women at risk of premature birth to evaluate if analyzing the vaginal microbiota using the RiboTaxa algorithm combined with neural network learning can help predict preterm delivery. This study addresses the lack of reliable clinical or biological methods for early diagnosis of premature birth by identifying specific vaginal microbiota signatures during pregnancy. Participants will have vaginal swabs taken as part of their routine care at Clermont-Ferrand University Hospital. During the swabbing procedure, two samples will be collected simultaneously one for standard diagnosis and another for microbiota analysis. The study involves longitudinal follow-up of the women from 14 weeks of gestation onward, with a case-control comparison after birth based on whether premature birth occurs. Throughout the study, biological samples will be collected and analyzed, focusing on vaginal microbiota changes. Outcome measures include early diagnosis of preterm birth using vaginal microbiota analysis at birth. Participants are expected to provide informed consent and be covered by French social security. The study includes safety and follow-up until delivery, and participation lasts through the pregnancy period until birth.

Early Diagnosis of Premature Births by Analysis of the Vaginal Microbiota