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

NCT07764315 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 310

Last updated 2026-08-13

No results posted yet for this study

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.

Conditions

  • Hypoxic-Ischemic Encephalopathy
  • Perinatal Asphyxia
  • Neonatal Brain Injury

Sponsors & Collaborators

  • BPI

    collaborator UNKNOWN

  • Assistance Publique - Hôpitaux de Paris

    lead OTHER

Eligibility

Min Age
0 Days
Max Age
1 Day
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-09-16
Primary Completion
2027-01-16
Completion
2027-02-16

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07764315 on ClinicalTrials.gov