Background The electrical activity of the brain is sensitive to oxygen availability. However, no studies have yet reported on the brain electrical activity of newborns in plateau and plain regions. Methods Neonates were admitted to the Department of Neonatology at Kunming Children’s Hospital and Fudan University Children’s Hospital, where they underwent EEG monitoring (P3/P4/F3/F4) from January 2020 to December 2022. The inclusion criteria were as follows: absence of neurological symptoms and signs, no infection during hospitalization, no abnormal waveform and obvious pseudo-error of EEG, and the corrected gestational age ≥35 weeks at EEG monitoring. A total of 136 cases were recruited, with equal representation from both the plateau group (Kunming group, KM group) and the plain group (Fudan group, FD group) at the respective institutions. Each patient had one EEG monitoring recording, each with 410 quantitative electroencephalogram (qEEG) signal features extracted. Besides, demographic information (sex, birthweight, corrected gestational age) were included in the regression analysis for the sample group. qEEG signal features were used to predict corrected gestational age by Gradient Boosting Machine in each sample group. Results Twenty signal features in the KM group exhibited higher values compared to those in the FD group, whereas ten signal features were lower (p < 0.05) corrected by demographic information. Higher signal features tend to occur in individuals with less corrected GA (Pearson correlation coefficient −0.32, p value = 6.63e−11). The prediction model for the plains (FD model) demonstrated a coefficient of determination (R²) of 0.72 in FD group but reduced performance R² of 0.47 in KM group. Similarly, the plateau model (KM model) showed performance R² of 0.6 in KM group but 0.37 in FD group. Conclusion The results indicate that brain maturity in newborns from plateau regions may lag behind that of their peers from plain regions. Therefore, the brain maturity prediction model based on qEEG needs to be re-generated for different altitudes. Impact <UnorderedList Mark="Bullet"> <ItemContent> We first explored the healthy neonatal brain development from the moderate altitude and evaluated the differences of neonatal brain development between plateau and plain areas by quantitative electroencephalogram (qEEG) signals. </ItemContent> <ItemContent> We found the brain maturity in newborns from plateau regions may lag behind that of their peers from plain regions. </ItemContent> <ItemContent> The brain maturity prediction model based on qEEG needs to be re-generated for different altitudes. </ItemContent> </UnorderedList>

Newborn brain development comparison of plateau and plain regions: insights from quantitative EEG

期刊论文
发表日期：

2025年8月1日

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Xiaofen Zhao,
Bi Ze,
Jiaqi Li,
Linbo Huang,
Xi Tan,
Mifeng Yang,
Yangfang Li,
Xinran Dong,
Wenhao Zhou

摘要

Background

The electrical activity of the brain is sensitive to oxygen availability. However, no studies have yet reported on the brain electrical activity of newborns in plateau and plain regions.

Methods

Neonates were admitted to the Department of Neonatology at Kunming Children’s Hospital and Fudan University Children’s Hospital, where they underwent EEG monitoring (P3/P4/F3/F4) from January 2020 to December 2022. The inclusion criteria were as follows: absence of neurological symptoms and signs, no infection during hospitalization, no abnormal waveform and obvious pseudo-error of EEG, and the corrected gestational age ≥35 weeks at EEG monitoring. A total of 136 cases were recruited, with equal representation from both the plateau group (Kunming group, KM group) and the plain group (Fudan group, FD group) at the respective institutions. Each patient had one EEG monitoring recording, each with 410 quantitative electroencephalogram (qEEG) signal features extracted. Besides, demographic information (sex, birthweight, corrected gestational age) were included in the regression analysis for the sample group. qEEG signal features were used to predict corrected gestational age by Gradient Boosting Machine in each sample group.

Results

Twenty signal features in the KM group exhibited higher values compared to those in the FD group, whereas ten signal features were lower (p < 0.05) corrected by demographic information. Higher signal features tend to occur in individuals with less corrected GA (Pearson correlation coefficient −0.32, p value = 6.63e−11). The prediction model for the plains (FD model) demonstrated a coefficient of determination (R²) of 0.72 in FD group but reduced performance R² of 0.47 in KM group. Similarly, the plateau model (KM model) showed performance R² of 0.6 in KM group but 0.37 in FD group.

Conclusion

The results indicate that brain maturity in newborns from plateau regions may lag behind that of their peers from plain regions. Therefore, the brain maturity prediction model based on qEEG needs to be re-generated for different altitudes.

Impact

We first explored the healthy neonatal brain development from the moderate altitude and evaluated the differences of neonatal brain development between plateau and plain areas by quantitative electroencephalogram (qEEG) signals.

We found the brain maturity in newborns from plateau regions may lag behind that of their peers from plain regions.

The brain maturity prediction model based on qEEG needs to be re-generated for different altitudes.