NCT05036395

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

AI-assisted cEEG Diagnosis of Neonatal Seizures to Optimize the Administration of Antiseizure Medication: a Multicenter, Randomised, Controlled Trial

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 1,000 (estimated)
• Sponsor: Children's Hospital of Fudan University · Academic / Other
• Sex: All
• Age: 0 Days – 6 Months
• Healthy volunteers: Not accepted

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).

Detailed 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.

Conditions

• Neonatal Seizure

Interventions

Type	Name	Description
OTHER	The routine assessment protocol and AI-assisted cEEG Diagnostic tool	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.
OTHER	The routine assessment protocol	The routine assessment protocol is that the neonatologists will evaluate the neonates by clinical conditions, real-time cEEG and amplitude-integrated EEG traces.

Timeline

• Start date: 2022-03-16
• Primary completion: 2024-03-10
• Completion: 2024-03-10
• First posted: 2021-09-05
• Last updated: 2023-04-04

Locations

3 sites across 1 country: China