Evaluation of the Clinical Effect of an Artificial Intelligence-assisted Diagnosis and Treatment System for Neonatal Seizures in the Real World: a Multicenter Clinical Study Protocol

Overview

Journal Zhongguo Dang Dai Er Ke Za Zhi

Specialty Pediatrics

Date 2022 Feb 25

PMID 35209986

Authors

Tian-Tian Xiao

Ya-Lan Dou

De-Yi Zhuang

Xu-Hong Hu

Wen-Qing Kang

Lin Guo

Xiao-Fen Zhao

Peng Zhang

Kai Yan

Wei-Li Yan

Guo-Qiang Cheng

Wen-Hao Zhou

Affiliations

Soon will be listed here.

Abstract

Neonatal seizures are the most common clinical manifestations of critically ill neonates and often suggest serious diseases and complicated etiologies. The precise diagnosis of this disease can optimize the use of anti-seizure medication, reduce hospital costs, and improve the long-term neurodevelopmental outcomes. Currently, a few artificial intelligence-assisted diagnosis and treatment systems have been developed for neonatal seizures, but there is still a lack of high-level evidence for the diagnosis and treatment value in the real world. Based on an artificial intelligence-assisted diagnosis and treatment systems that has been developed for neonatal seizures, this study plans to recruit 370 neonates at a high risk of seizures from 6 neonatal intensive care units (NICUs) in China, in order to evaluate the effect of the system on the diagnosis, treatment, and prognosis of neonatal seizures in neonates with different gestational ages in the NICU. In this study, a diagnostic study protocol is used to evaluate the diagnostic value of the system, and a randomized parallel-controlled trial is designed to evaluate the effect of the system on the treatment and prognosis of neonates at a high risk of seizures. This multicenter prospective study will provide high-level evidence for the clinical application of artificial intelligence-assisted diagnosis and treatment systems for neonatal seizures in the real world.

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