Intelligent Physiological Monitoring to Predict Preterm Brain Injury

Study acronym: AI4NICU
StatusEnrolling by Invitation
PhaseNot specified
Started

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Record History

  1. Study First Submitted
Cerebral palsy (CP) remains prevalent among very (28-31 weeks) and extremely (\<28 weeks) preterm infants. Prematurity-related brain injuries (high-grade intraventricular haemorrhage, IVH or periventricular leukomalacia, PVL) develop usually during the first few days after birth and are a strong predictor of CP. Development of IVH or PVL have been linked to hemodynamic instability. Artificial intelligence (AI) provides an opportunity to detect patterns from continuous physiological monitoring data that are associated with prematurity-related brain injury. A dataset of extremely preterm infants will be collated from previous INFANT Research Centre study cohorts. A separate but aligned anonymous dataset will be obtained from the University of Graz. Continuous physiological monitoring data will be analyzed with AI algorithms to identify infants with the highest risk of brain injury.
Trial Details
NCT Number NCT07880431
Lead Sponsor University College Cork
Collaborators: Cerebral Palsy Foundation, Science Foundation Ireland
Conditions
(from sponsor)		 Cerebral Palsy (CP), Intraventricular Hemorrhage Neonatal, Periventricular Leukomalacia, Neurodevelopmental Delay
Related terms Cerebral Palsy, Leukomalacia, Periventricular
Enrollment 413 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov