NCT05036395

Brief 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).

Trial Health

43
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
1,000

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Mar 2022

Typical duration for not_applicable

Geographic Reach
1 country

3 active sites

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

August 24, 2021

Completed
12 days until next milestone

First Posted

Study publicly available on registry

September 5, 2021

Completed
6 months until next milestone

Study Start

First participant enrolled

March 16, 2022

Completed
2 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

March 10, 2024

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

March 10, 2024

Completed
Last Updated

April 4, 2023

Status Verified

April 1, 2023

Enrollment Period

2 years

First QC Date

August 24, 2021

Last Update Submit

April 3, 2023

Conditions

Neonatal Seizure

Outcome Measures

Primary Outcomes (1)

  • The percentage of the individuals with the inappropriate administration of ASM

    The inappropriate administration of ASM is defined: (1) the administration of an ASM before the electrographic seizure episode; or (2) an ASM is given to the neonates without electrographic seizure episode.

    Immediately after the end of cEEG monitoring

Secondary Outcomes (3)

  • Gesell Developmental Schedules (GDS)

    at corrected gestational age of 6 months

  • Total electrographic seizure times per hour (second/hour)

    Immediately after the end of cEEG monitoring

  • The mortality of neonates

    Immediately after discharge

Study Arms (2)

The neonates evaluated by the routine assessment protocol and AI-assisted cEEG Diagnostic tool

EXPERIMENTAL

This group will be monitored by cEEG with standard operating procedure. The cEEG recording will be evaluated by neonatologists with the routine assessment protocol and AI assisted cEEG diagnostic tool in real time during cEEG monitoring. Both real-time cEEG and amplitude-integrated EEG traces are displayed at the bedside for clinical review. This group will follow the standard clinical protocols of the recruiting hospitals for ASM administration after the neonatologists' review.

Other: The routine assessment protocol and AI-assisted cEEG Diagnostic tool

The neonates evaluated by the routine assessment protocol

ACTIVE COMPARATOR

This group will be monitored by cEEG with standard operating procedure. The cEEG recording will be evaluated by neonatologists with the routine assessment protocol during cEEG monitoring. Both real-time cEEG and amplitude-integrated EEG traces are displayed at the bedside for clinical review. This group will follow the standard clinical protocols of the recruiting hospitals for ASM administration after the neonatologists' review.

Other: The routine assessment protocol

Interventions

The routine assessment protocol and AI-assisted cEEG Diagnostic toolOTHER

The AI-assisted cEEG diagnostic tool is an automated seizure reporting system, including a quantitively EEG neural signal processing pipeline to extract features from the original signal datasets, machine learning models based on gradient boosted model for prediction. The tool can report electrographic seizures in real time during cEEG monitoring. The neonatologists will evaluate the neonates by AI-assisted cEEG diagnostic tool, clinical conditions, real-time cEEG and amplitude-integrated EEG traces. The investigators will make a decision after review the neonates clinical conditions, AI-assisted cEEG diagnostic report, the cEEG and amplitude-integrated EEG.

The neonates evaluated by the routine assessment protocol and AI-assisted cEEG Diagnostic tool
The routine assessment protocolOTHER

The routine assessment protocol is that the neonatologists will evaluate the neonates by clinical conditions, real-time cEEG and amplitude-integrated EEG traces.

The neonates evaluated by the routine assessment protocol

Eligibility Criteria

Age0 Days - 6 Months
Sexall
Healthy VolunteersNo
Age GroupsChild (0-17)

You may qualify if:

  • 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;

You may not qualify if:

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

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (3)

Henan Children's Hospital

Zhengzhou, Henan, China

RECRUITING

Children Hospital of Fudan University

Shanghai, Shanghai Municipality, 201102, China

NOT YET RECRUITING

Chengdu Women's and Children's Central Hospital

Chengdu, Sichuan, China

RECRUITING

Related Publications (3)

  • Rennie JM, de Vries LS, Blennow M, Foran A, Shah DK, Livingstone V, van Huffelen AC, Mathieson SR, Pavlidis E, Weeke LC, Toet MC, Finder M, Pinnamaneni RM, Murray DM, Ryan AC, Marnane WP, Boylan GB. Characterisation of neonatal seizures and their treatment using continuous EEG monitoring: a multicentre experience. Arch Dis Child Fetal Neonatal Ed. 2019 Sep;104(5):F493-F501. doi: 10.1136/archdischild-2018-315624. Epub 2018 Nov 24.

    PMID: 30472660RESULT

  • Shellhaas RA, Chang T, Tsuchida T, Scher MS, Riviello JJ, Abend NS, Nguyen S, Wusthoff CJ, Clancy RR. The American Clinical Neurophysiology Society's Guideline on Continuous Electroencephalography Monitoring in Neonates. J Clin Neurophysiol. 2011 Dec;28(6):611-7. doi: 10.1097/WNP.0b013e31823e96d7. No abstract available.

    PMID: 22146359RESULT

  • Hoodbhoy Z, Masroor Jeelani S, Aziz A, Habib MI, Iqbal B, Akmal W, Siddiqui K, Hasan B, Leeflang M, Das JK. Machine Learning for Child and Adolescent Health: A Systematic Review. Pediatrics. 2021 Jan;147(1):e2020011833. doi: 10.1542/peds.2020-011833. Epub 2020 Dec 15.

    PMID: 33323492RESULT

Study Officials

  • Wenhao Zhou

    Children's Hospital of Fudan University

    STUDY CHAIR

Central Study Contacts

Wenhao Zhou, Ph.D

CONTACT

+86-21-64931913zhouwenhao@fudan.edu.cn

Tiantian Xiao, M.D

CONTACT

xiao13671814745@163.com

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
DOUBLE
Who Masked
PARTICIPANT, OUTCOMES ASSESSOR
Purpose
OTHER
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

August 24, 2021

First Posted

September 5, 2021

Study Start

March 16, 2022

Primary Completion

March 10, 2024

Study Completion

March 10, 2024

Last Updated

April 4, 2023

Record last verified: 2023-04

Locations

CN(3)