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.
No parental opposition to the use of the child's medical data within 1 month of... [+5]
Participation in a therapeutic biomedical research liable to modify the EEG trac... [+2]