Using AI to predict necrotizing enterocolitis in premature babies through stool analysis
Official title: Predictive Diagnosis of Ulcero-Necrotizing EnteroColitis in Premature Babies Using an Artificial Intelligence Approach Based on Early Analysis of the Fecal Microbiota
Run by University Hospital, Clermont-Ferrand · NCT06727877 · Data updated 2026-11-12
This study is trying to see if using AI to analyze stool samples from premature babies can help predict who is at risk for necrotizing enterocolitis, so doctors can take steps to prevent it.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | Any age to 1 Day |
| Sex | All |
| Enrollment | 1000 (estimated) |
| Sponsor | University Hospital, Clermont-Ferrand Academic / other |
| Locations | 5 sites (Clermont-Ferrand and 4 other locations) |
| Status | Recruiting |
| Started | April 1, 2025 |
| Main results expected | June 1, 2027 |
| Study ends | June 1, 2027 |
| Registry record updated | April 6, 2026 |
| Trial ID | NCT06727877 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates for this study are premature infants born before 34 weeks of gestation who are hospitalized in neonatal intensive care units.
✕Probably not a fit
Patients who are not premature or those whose guardians are legally protected may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This study aims to develop a predictive diagnostic test for necrotizing enterocolitis (NEC) in premature infants by analyzing their fecal microbiota using artificial intelligence. Stool samples from infants up to 21 days old will be collected and analyzed through metagenomic sequencing to identify risk factors for NEC. The study will classify infants as at risk or not based on the analysis of their stool samples, allowing for personalized preventive measures. Clinicians will diagnose NEC according to the Bell classification, and follow-up will be conducted to monitor outcomes.
Why it matters
Potential benefit: If successful, this approach could significantly reduce the incidence and mortality of necrotizing enterocolitis in premature infants by enabling early intervention.
How similar studies have gone: While the use of artificial intelligence in microbiota analysis is a novel approach, similar studies have shown promise in predicting other conditions, indicating potential for success.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Child born prematurely (i.e. before 34 weeks of amenorrhea) in one of participating university hospitals and hospitalized in neonatal intensive care units of the AURA region's university hospitals * Child born outside CHU and transferred before 24h of life to the neonatal intensive care unit of one of thehospital participating in the study * Affiliated with a Social Security scheme Exclusion Criteria: * Child whose guardians are protected by law (guardianship, curatorship, safeguard of justice) * Children whose parents are under 18 years of age * Refusal of parental authority to participate
Where it's running
-
CHU de Clermont-Ferrand
Clermont-Ferrand, France Recruiting -
CHU Saint Etienne
Saint-Etienne, France Recruiting -
CHU Grenoble
Grenoble, France Not yet recruiting -
Hfme
Lyon, France Not yet recruiting -
Hopital Croix Rousse
Lyon, France Not yet recruiting
Study contacts
- Principal investigator: Maguelonne Pons — University Hospital, Clermont-Ferrand
- Study coordinator: Lise Laclautre
- Email: promo_interne_drci@chu-clermontferrand.fr
- Phone: 334.73.754.963
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.