EEG-Based Decision-Support Algorithm for Hypoxic-Ischemic Encephalopathy in Term Newborns

This retrospective, multicenter, observational study evaluates how well a decision-support algorithm can tell apart mild forms of hypoxic-ischemic encephalopathy (HIE) from moderate or severe forms in full-term newborns born after a lack of oxygen around birth (perinatal asphyxia). The algorithm reads the raw (non-compressed) EEG signal. Its output is compared with the reference reading of the full conventional EEG made by a panel of pediatric neurophysiologists together with the baby's clinical information. The study uses only medical data that already exists and asks nothing of the babies or their families.

NCT Number	NCT07764315
Lead Sponsor	Assistance Publique - Hôpitaux de Paris Collaborators: BPI
Conditions	Hypoxic-Ischemic Encephalopathy, Perinatal Asphyxia, Neonatal Brain Injury
Enrollment	310 participants
Start Date	2026-09-16
Primary Completion	2027-01-16 (estimated)
Study Completion	2027-02-16 (estimated)
Updated on ClinicalTrials.gov	2026-08-13