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Intelligent Physiological Monitoring to Predict Preterm Brain Injury
Sponsor: University College Cork
Summary
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.
Official title: Intelligent Physiological Monitoring of Preterm Infants to Predict Brain Injury Associated With CP and With Confirmed CP in the First Days After Birth
Key Details
Gender
All
Age Range
Any - 5 Days
Study Type
OBSERVATIONAL
Enrollment
413
Start Date
2026-04-13
Completion Date
2029-10
Last Updated
2026-10-19
Healthy Volunteers
No
Conditions
Interventions
EEG
During the first 72 hours after birth
NIRS
During the first 72 hours after birth
Locations (1)
University College Cork
Cork, Cork, Ireland