Early Diagnosis of Premature Births by Analysis of the Vaginal Microbiota
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).
- EligibilityCriteria: 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:  Patient under guardianship, curatorship or safeguard of justice Patient having received antibiotic therapy in the 2 weeks prior to admission - HealthyVolunteers: No - Gender: Female - MinimumAge: 18 Years - StdAgeList: Adult, Older Adult