Early Diagnosis of Premature Births by Analysis of the Vaginal Microbiota (PREMABIOTE)

University Hospital, Clermont-Ferrand

Status

Enrolling

Conditions

Vaginal Flora

Premature Birth

Treatments

Other: vaginal swab

Study type

Interventional

Funder types

Other

Identifiers

NCT06265740

2023-A02466-39 (Other Identifier)

RBHP 2023 GALLOT (PREMABIOTE)

Details and patient eligibility

About

Objectives: to assess the relevance of the RiboTaxa algorithm coupled with neural network learning based on analysis of vaginal microbiota metagenomic sequencing data for predicting prematurity in an identified at-risk population.

Study description: Longitudinal follow-up of a cohort of pregnant women, with collection of biological samples, and a posteriori case-control comparison based on the occurrence of an event (premature birth).

Full description

There is currently no reliable clinical or biological diagnosis to predict premature birth. Recent work using metagenomic data analysis coupled with artificial intelligence approaches suggests that there may be a vaginal microbiota signature during pregnancy that correlates with the occurrence of preterm birth. The aim of the study is to use biological samples to confirm the identification of these vaginal microbiota signatures as a means of predicting preterm birth.

Enrollment

150 estimated patients

Sex

Female

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

Pregnant women Admitted to the Clermont-Ferrand University Hospital maternity ward from 14 weeks' gestation onwards
For threat of preterm birth (PTB) characterized by contractile activity and/or cervical changes, or for premature rupture of fetal membranes (PROM)
And in need of vaginal swabbing
Single or multiple pregnancy
Able to understand and object to the study
Covered by a French social security scheme.
Give informed consent for the study

Exclusion criteria