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. 2020 Jul;88(1):91-99.
doi: 10.1038/s41390-019-0693-0. Epub 2019 Dec 10.

Assessment of neonatal EEG background and neurodevelopment in full-term small for their gestational age infants

José R Castro Conde  1   2 , Candelaria González Campo  3 , Nieves L González González  4   5 , Beatriz Reyes Millán  6 , Desiré González Barrios  7 , Alejandro Jiménez Sosa  8 , Itziar Quintero Fuentes  9
Affiliations

Assessment of neonatal EEG background and neurodevelopment in full-term small for their gestational age infants

José R Castro Conde et al. Pediatr Res. 2020 Jul.

Abstract

Background: Delayed brain function development in small-gestational-age (SGA) infants has been reported. We aimed to quantify rates of immature neonatal EEG patterns and their association with neurodevelopment in SGA full-term neonates.

Methods: Using a cohort design, 50 SGA (birthweight <10th percentile) and 44 appropriate-gestational-age (AGA) term neonates underwent continuous video-EEG recordings lasting >3 h. Seventy-three of them were assessed at 2-years-old using Bayley-III-Scales. For EEG analysis, several segments of discontinuous/alternating EEG tracings were selected.

Main outcomes measured: (1) Visual analysis (patterns of EEG maturity); (2) Power spectrum in δ, θ, α and β frequency bands; and (3) scores in motor, cognitive and language development.

Results: (1) SGA infants, compared to AGA, showed: (a) higher percentages of discontinuous EEG, both asynchrony and interhemispheric asymmetry, and bursts with delta-brushes, longer interburst-interval duration and more transients/hour; (b) lower relative power spectrum in δ and higher in α; and (c) lower scores on motor, language and cognitive neurodevelopment. (2) Asymmetry >5%, interburst-interval >5 s, discontinuity >11%, and bursts with delta-brushes >11% were associated with lower scores on Bayley-III.

Conclusions: In this prospective study, SGA full-term neonates showed high rates of immature EEG patterns. Low-birthweight and immaturity EEG were both correlated with low development scores.

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Conflict of interest statement

The authors have no conflicts of interest to declare. There are no prior publications or submissions with any overlapping information, including study data and patients in an abstract or poster. McLean Language School (MLS) provides a translation, editing and review service to papers to be published by staff members of the Universidad de La Laguna (ULL). MLS declares no competing interest in relation to this article.

Figures

Fig. 1
Fig. 1. Examples the EEG variables studied in the visual and spectral analysis in an SGA term infant.
a and b Discontinuous EEG tracings showing interhemispheric asynchrony and asymmetry, respectively, with transient rolandic sharp waves (vertical arrow), interburst interval (two-headed arrow) and delta brushes in the bursts (Inclined arrows). c Interhemispheric asymmetry of the bursts on the EEG background with tracé alternant and transient temporal sharp waves (vertical arrow). d Graphs and topographic maps of absolute power spectrum in the δ, θ and α frequency bands; the values in the color scale represent absolute power spectrum in µV2.
Fig. 2
Fig. 2. Flow chart of children included in the study sample.
*It was necessary to practice more than one EEG recording of different days in 17 newborns. † His parents refused a new EEG recording. ‡ In none of them could a new EEG recording be repeated. § The EEG recording was repeated in four of them. # There were three SGA children and four other AGA children who did not collaborate.
Fig. 3
Fig. 3. Main results of visual and spectral analysis.
Box plots represent medians, interquartile ranges (P25 to P75), and min-max (whiskers) of the main results of the visual EEG analysis (a) and of the relative power spectrum (b). *P < 0.05; †P < 0.01.
See this image and copyright information in PMC

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