An objective and simple aEEG parameter for predicting neurological outcomes in extremely preterm infants

Area of Science:

• Neonatal Neurology
• Neurodevelopmental Pediatrics
• Quantitative EEG Analysis

Background:

• Extremely low gestational-age newborns (ELGANs) face significant risks for adverse neurodevelopmental outcomes.
• Early identification of at-risk ELGANs is crucial for timely intervention.
• Amplitude-integrated electroencephalography (aEEG) is a bedside monitoring tool used in neonatal care.

Purpose of the Study:

• To evaluate the utility of the aEEG continuity index (CI) in predicting neurodevelopmental outcomes in ELGANs.
• To compare the predictive performance and interrater reliability of CI with the Burdjalov score (BS).

Main Methods:

• Prospective study of 80 newborns born before 28 weeks of gestational age (January 2020 - December 2022).
• aEEG analyzed using CI and BS from day 1 to week 4 of life.
• Short-term outcomes defined by mortality or neuroimaging abnormalities; long-term outcomes assessed using Bayley Scales Third Edition at 24-months-corrected-age.

Main Results:

• Both CI and BS predicted short- and long-term adverse outcomes, with peak differentiation on day 4.
• CI demonstrated superior interrater reliability (ICC 0.979) compared to BS (ICC 0.68).
• Lack of CI increase from days 1-4 and CI independence from sedation/IVH were significant predictors.

Conclusions:

• The aEEG CI is a valuable, quantitative, and easily calculable screening tool for identifying ELGANs at risk for adverse neurodevelopmental outcomes.
• CI's high reliability and independence from confounding factors support its clinical utility.
• This tool can aid in early risk stratification and targeted interventions for vulnerable newborns.