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Semi-Automatic Analysis of Specific Electroencephalographic Patterns during NREM2 Sleep in a Pediatric Population after SARS-CoV-2 Infection

Authors :
Paolo Di Bella
Anna Gaia Attardi
Ambra Butera
Arianna Mancini
Nunzia Calabrò
Elisa Giuseppa Lo Re
Giuseppe Trimarchi
Antonio Gennaro Nicotera
Gabriella Di Rosa
Daniela Lo Giudice
Source :
Journal of Personalized Medicine, Vol 14, Iss 2, p 152 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

The post-COVID-19 condition is defined by the World Health Organization as the persistence of symptoms or development of new symptoms three months after the initial SARS-CoV-2 infection, lasting for at least two months without a clear explanation. Neuropsychiatric disorders associated with this condition include asthenia, memory and concentration problems, and sleep disturbances. Our study aims to investigate sleep patterns following SARS-CoV-2 infection using EEG findings and a sleep quality questionnaire completed by parents (Sleep Disturbance Scale for Children—SDSC). Notably, our investigation is based on a convenience sample. The patients in our sample, aged 1 to 14 years, are not currently taking any medications; rather, they are undergoing follow-up assessments at the Child Neuropsychiatry department of the University Hospital of Messina for neurodevelopmental evaluations. Specifically, we are analyzing amplitude and power spectrum data in the first five minutes of NREM2 sleep, calculated from EEG recordings obtained via bipolar leads within three months after the onset of the disease. These results will be compared with controls performed on the same subjects in the six months preceding the infection. The focus of the study was sleep spindles, which are generated by the thalamocortical systems and play a role in sleep modulation, memory, and learning. Preliminary analysis suggests a predominant increase in the slow component of the spindles in the right-frontal lead.

Details

Language :
English
ISSN :
20754426
Volume :
14
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Journal of Personalized Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.58c3b9a6b00c4fc294d97923c8dab6fc
Document Type :
article
Full Text :
https://doi.org/10.3390/jpm14020152