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Sleep EEG Characteristics in Young and Elderly Patients with Obstructive Sleep Apnea Syndrome

Overview of attention for article published in Psychiatry Investigation, March 2016
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Title
Sleep EEG Characteristics in Young and Elderly Patients with Obstructive Sleep Apnea Syndrome
Published in
Psychiatry Investigation, March 2016
DOI 10.4306/pi.2016.13.2.217
Pubmed ID
Authors

Yu Jin Lee, Jong Won Kim, Yu-Jin G. Lee, Do-Un Jeong

Abstract

In the present study, it was hypothesized that the sleep electroencephalogram (EEG) characteristics of young (<30 yrs) and elderly (>55 yrs) OSAS patients would differ. We analyzed 76 sleep EEG recordings from OSAS patients (young group: n=40, mean age: 24.3±4.9 yrs; elderly group: n=36, mean age: 59.1±4.9 yrs), which were obtained during nocturnal polysomnography. The recordings were assessed via spectral analysis in the delta (0.5-4.5 Hz), theta (4.5-8 Hz), alpha (8-12 Hz), beta (12-32 Hz), slow sigma (11-13 Hz), and fast sigma (13-17 Hz) frequency bands. Apnea Hypopnea Index (AHI) and sleep efficiency (%) did not differ significantly between the two groups (19.8±14.4 vs. 25.9±16.0, p=0.085; 84.4±12.6 vs. 80.9±11.0, p=0.198, respectively). After adjusting for gender, the slow/fast sigma ratio was not significantly correlated with AHI in the elderly group (r=-0.047, p=0.790) but AHI was inversely correlated with the slow/fast sigma ratio in the young group (r=-0.423, p=0.007). A multiple linear regression analysis revealed that a higher AHI was related with a lower slow/fast sigma ratio in the young group (β=-0.392, p=0.028) but not the elderly. In the present study, sleep EEG activity differed between young and elderly OSAS patients. The slow/fast sigma ratio was associated with OSAS severity only in young patients, suggesting that young OSAS patients may have a distinctive brain plasticity compared with elderly patients.

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The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 20%
Student > Ph. D. Student 2 20%
Other 1 10%
Student > Doctoral Student 1 10%
Student > Master 1 10%
Other 1 10%
Unknown 2 20%
Readers by discipline Count As %
Medicine and Dentistry 3 30%
Engineering 2 20%
Neuroscience 1 10%
Biochemistry, Genetics and Molecular Biology 1 10%
Unknown 3 30%