The Effect of AI-assisted cEEG Diagnosis on the Administration of Antiseizure Medication in Neonatal Seizures

Last updated: April 3, 2023
Sponsor: Children's Hospital of Fudan University
Overall Status: Active - Recruiting

Phase

N/A

Condition

N/A

Treatment

N/A

Clinical Study ID

NCT05036395
CHFudanU_NNICU17
  • Ages < 6
  • All Genders

Study Summary

This is a prospective randomised clinical trial study to test an artificial intelligence (AI)-assisted continuous electroencephalogram(cEEG) diagnostic tool for optimizing the administration of antiseizure medication (ASM) in neonatal intensive care units(NICUs).

Eligibility Criteria

Inclusion

Inclusion Criteria:

  • Postnatal age < or = 28 days;
  • cEEG monitoring at least 24hours monitoring;
  • Suspected seizures；
  • Abnormal movement;
  • Brain infarction；
  • Risk of Intracranial hemorrhage;
  • Abnormality of brain MRI or ultrasound;
  • Hypoxic-ischemic encephalopathy or suspected Hypoxic-ischemic encephalopathy;
  • Central nervous system (CNS) or systemic infections;
  • Suspected genetic diseases or Positive genetic diagnoses;

Exclusion

Exclusion Criteria:

  • The neonates with head scalp defect, scalp hematoma, edema and other contraindicationswhich are not suitable for cEEG monitoring during hospitalization.

Study Design

Total Participants: 1000
Study Start date:
March 16, 2022
Estimated Completion Date:
March 10, 2024

Study Description

The occurrence of neonatal seizures may be the first, and perhaps the only, clinical sign of a central nervous system disorder in the newborn infant. The promoted treatment of seizures can limit the secondary injury to the brain and positively affect the infant's long-term neurological development. However, the current antiseizure medication (ASM) are both overused and underused. Studies indicated that early automated seizure detection tool had a high diagnostic accuracy of neonatal seizures. However, there is little evidence that early automated seizure detection tool could the optimize the administration of ASM and improved the neurological outcomes in neonatal seizures. Therefore, the primary study aim is to investigate whether the utility of AI assisted cEEG diagnostic tool could optimize the administration of ASM in NICUs.

This project will enroll the neonates with suspected or high risk of seizures who will receive at least 72 hours cEEG monitoring during hospitalization. All the cEEG monitoring methodology is standardized across recruiting hospitals.

The intervention will be an artificial intelligence (AI)-assisted continues electroencephalogram (cEEG) diagnostic tool.

The individuals were randomly allocated to one of the two groups using a predetermined randomisation sequence and block randomisation generator (block of 4). The group 1 will be monitored with cEEG and the cEEG recording will be assessed by neonatologists with AI assisted cEEG diagnostic tool in real time during cEEG monitoring. The group 2 will be monitored with cEEG and the cEEG recording will be assessed by neonatologists when as routine during cEEG monitoring. Both groups will follow the standard clinical protocols for ASM administration of the recruiting hospitals The reference standard is the electrographic seizures interpreted by 3 clinicians who had attended the uniformly training program and were certified by the Chinese Anti-Epilepsy Association. These 3 clinicians are blinded to the group allocation.

Connect with a study center

  • Henan Children's Hospital

    Zhengzhou, Henan
    China

    Active - Recruiting

  • Children Hospital of Fudan University

    Shanghai, Shanghai 201102
    China

    Site Not Available

  • Chengdu Women's and Children's Central Hospital

    Chengdu, Sichuan
    China

    Active - Recruiting

Not the study for you?

Let us help you find the best match. Sign up as a volunteer and receive email notifications when clinical trials are posted in the medical category of interest to you.