Build a Decision Aid Tool to Help Emergency Intensive Care Specialists in the Context of Hypoxic Ischemic Encephalopathy (NewbornDS)

Assistance Publique - Hôpitaux de Paris

Status: Completed

Conditions: Encephalopathy

Treatments: Other: Decision of hypothermia

Study type: Observational

Funder types: Other

Identifiers

NCT05114070

APHP 210070

Details and patient eligibility

About

The project aims at designing a machine learning solution able to recognize characteristics signals patterns of brain damages in full term babies born within a context of Hypoxic Ischemic Encephalopathy (HIE)

Full description

Retrospective study based on a digital EEG signal library intending to design, train and test an efficient AI solution for hypothermia protocol start indications.

The output of the Project is to make available to pediatric resuscitation units an adequate tool to guide them in the decision of hypothermia protocol start in a general context of neurophysiologist competence scarcity. EEG signal that would allow the algorithm design will be based on several parameters of the conventional EEG and not only on signal amplitude

Enrollment: 106 patients

Sex: All

Ages: Under 2 days old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Full term (> 36 weeks)
• HIE context
• EEG recording before 6 hours of life

Exclusion criteria

-Opposition of parental authority holders of a patient born after 2015