Evidence map›Paper›PMID 39071545›Full record

ArticleNature and science of sleep2024

Quantitative Electroencephalography in Term Neonates During the Early Postnatal Period Across Various Sleep States.

Ruijie Zhang, Xinran Dong, Lu Zhang, Xinao Lin, Xuefeng Wang, Yan Xu, Chuyan Wu, Feng Jiang, Jimei Wang

Abstract read
In one paragraph

Article in Nature and science of sleep, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Ruijie Zhang *Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, People's Republic of China.
Xinran Dong *Center for Molecular Medicine, Children's Hospital of Fudan University, Shanghai, People's Republic of China.
Lu Zhang *Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, People's Republic of China.
Xinao LinDepartment of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, People's Republic of China.ORCID 0000-0001-5120-7077
Xuefeng WangDepartment of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, People's Republic of China.
Yan XuDepartment of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, People's Republic of China.
Chuyan WuDepartment of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.ORCID 0000-0002-5622-6020
Feng JiangDepartment of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, People's Republic of China.ORCID 0000-0002-3525-8752
Jimei WangDepartment of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Neonatal sleep is pivotal for their growth and development, yet manual interpretation of raw images is time-consuming and labor-intensive. Quantitative Electroencephalography (QEEG) presents significant advantages in terms of objectivity and convenience for investigating neonatal sleep patterns. However, research on the sleep patterns of healthy neonates remains scarce. This study aims to identify QEEG markers that distinguish between different neonatal sleep cycles and analyze QEEG alterations across various sleep stages in relation to postmenstrual age. Methods: From September 2023 to February 2024, full-term neonates admitted to the neonatology department at the Obstetrics and Gynecology Hospital of Fudan University were enrolled in this study. Electroencephalographic (EEG) recordings were obtained from neonates aged 37-42 weeks, within 1-7 days post-birth. The ROC curve was employed to evaluate QEEG features related to amplitude, range EEG (rEEG), spectral density, and connectivity across different sleep stages. Furthermore, regression analyses were performed to investigate the association between these QEEG characteristics and postmenstrual age. Results: The alpha frequency band's spectral_diff_F3 emerged as the most potent discriminator between active sleep (AS) and quiet sleep (QS). In distinguishing AS from wakefulness (W), the theta frequency's spectral_diff_C4 was the most effective, whereas the delta frequency's spectral_diff_P4 excelled in differentiating QS from W. During AS and QS phases, there was a notable increase in entropy within the delta frequency band across all monitored brain regions and in the spectral relative power within the theta frequency band, correlating with postmenstrual age (PMA). Conclusion: Spectral difference showcases the highest discriminative capability across awake and various sleep states. The observed patterns of neonatal QEEG alterations in relation to PMA are consistent with the maturation of neonatal sleep, offering insights into the prediction and evaluation of brain development outcomes.

Indexed as

neonatespostmenstrual agequantitative EEGsleep

Identifiers

PMID39071545
PMCPMC11282454

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.