Condition: Premature Birth · Vaginal Flora · Sponsor: University Hospital, Clermont-Ferrand
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).
This description comes directly from the study's public registry record.
Lise Laclautre · 334.73.754.963 · promo_interne_drci@chu-clermontferrand.fr
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| CHU de Clermont-Ferrand | Clermont-Ferrand, France | Recruiting |
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Source record: clinicaltrials.gov/study/NCT06265740