Clinical and polysomnographic characteristics of excessive daytime sleepiness in children
Abstract
PURPOSE: This study aimed to delineate the clinical and polysomnography (PSG) characteristics of sleep disorders in children with excessive daytime sleepiness (EDS).
METHODS: Between February 2002 and June 2015, 622 pediatric patients with EDS were evaluated with overnight PSG and the Multiple Sleep Latency Test at the Samsung Medical Center. The medical records; questionnaire responses about depression, sleepiness, sleep habits; and sleep study data of 133 patients without obstructive sleep apnea (OSA) were reviewed retrospectively.
RESULTS: The patients (63 girls, 70 boys) slept for an average of 7 h 30 min and 8 h 44 min on weekdays and weekends, respectively. The mean Epworth Sleepiness Scale score was 11.01 ± 4.09 and did not differ significantly among sleep disorders. Among the 102 patients who completed the depression questionnaire, 53 showed depressive feelings, which were moderate or severe in 39, with no significant differences among specific sleep disorders. Thirty-four patients exhibited normal PSG results. Seventeen of them were concluded as not having any sleep disorders, and the others as having delayed sleep phase disorder (DSPD). Narcolepsy (n = 78) was the most common disorder, followed by DSPD (n = 17) and idiopathic hypersomnia (n = 12).
CONCLUSIONS: Pediatric patients with EDS had various sleep disorders and some did not have any sleep disorder despite EDS. More than half the patients with EDS showed depressive feelings affecting their daily lives. For…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 133 participants or records.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.