EEG-Based Decision-Support Algorithm for Hypoxic-Ischemic Encephalopathy in Term Newborns
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age0-1
SponsorAssistance Publique - Hôpitaux de Paris
About this trial
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.
Eligibility criteria
Qualifiers
No parental opposition to the use of the child's medical data within 1 month of the mailed information notice
Gestational age ≥ 36 weeks of amenorrhea
Birth weight ≥ 1800 g
Born in a context of perinatal asphyxia (any cause) leading to suspected HIE, with EITHER biological signs of metabolic acidosis (pH ≤ 7 or base deficit ≥ 16 mmol/L or lactate ≥ 11 mmol/L within the first hour of life, any blood sample) OR a history of asphyxia with Apgar ≤ 5 at 10 minutes or need for ventilatory resuscitation continued at 10 minutes of life
Disqualifiers
Participation in a therapeutic biomedical research liable to modify the EEG tracing
Fewer than 20 minutes of artifact-free EEG recording
Signal from active electrodes Fp1, Fp2, T3 and T4 not exploitable
Trial design
Treatments tested in this trial
- Not listed
Trial groups
310 Participants
are grouped into 1 trial groupLocations
Sponsors and collaborators
Assistance Publique - Hôpitaux de Paris
Lead sponsor
BPI
Collaborator
Source ClinicalTrials.gov