Clinical Research Directory

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

Sponsor: Assistance Publique - Hôpitaux de Paris

Summary

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.

Official title: Retrospective Multicenter Validation of a Conventional EEG-Based Decision-Support Algorithm to Discriminate Mild Versus Moderate/Severe Hypoxic-Ischemic Encephalopathy in Term Newborns (Newborn Neuro Digital Project)

Key Details

Conditions