Literature DB >> 22740041

Measuring sleep quality after adenotonsillectomy in pediatric sleep apnea.

Seung Hoon Lee1, Ji Ho Choi, Il Ho Park, Sang Hag Lee, Tae Hoon Kim, Heung Man Lee, Hee-Kwon Park, Robert J Thomas, Chol Shin, Chang-Ho Yun.   

Abstract

OBJECTIVES/HYPOTHESIS: The aim of this study was to demonstrate postoperative changes in sleep quality in children with obstructive sleep apnea (OSA), using both conventional sleep staging and electrocardiogram-based cardiopulmonary coupling (CPC) analysis. The hypothesis is that being electroencephalography (EEG)-independent, CPC may detect changes in sleep quality that traditional sleep architecture analysis cannot. STUDY
DESIGN: Retrospective outcome research.
METHODS: We included 37 children (aged 6.89 ± 2.76 years, 28 male) with OSA who underwent adenotonsillectomy, and analyzed standard polysomnography and CPC parameters from a full-night study before and after adenotonsillectomy. High-frequency coupling (HFC) and low-frequency coupling (LFC) were used as indices of stable and unstable sleep, respectively.
RESULTS: Adenotonsillectomy led to a significant change in CPC parameters (HFC, 50.3 ± 16.1% to 56.1 ± 14.7%, P = .03; LFC, 35.1 ± 14.5% to 27.3 ± 13.0%, P = .003), which was paralleled by improvements in the apnea-hypopnea (12.7 ± 13.7 to 1.0 ± 0.8, P < .001) and arousal index (20.8 ± 11.5 to 9.9 ± 3.9, P < .001). Polysomnographic sleep stage parameters other than the arousal index did not reflect postoperative resolution of OSA.
CONCLUSIONS: In pediatric OSA, postoperative improvement of sleep quality is more readily discernible by CPC analysis than EEG-based sleep staging. The CPC analysis may have potential advantages in the assessment of sleep quality in pediatric populations.
Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

Entities:  

Mesh:

Year:  2012        PMID: 22740041     DOI: 10.1002/lary.23356

Source DB:  PubMed          Journal:  Laryngoscope        ISSN: 0023-852X            Impact factor:   3.325


  7 in total

1.  Electrocardiogram-based sleep analysis for sleep apnea screening and diagnosis.

Authors:  Yan Ma; Shuchen Sun; Ming Zhang; Dan Guo; Arron Runzhou Liu; Yulin Wei; Chung-Kang Peng
Journal:  Sleep Breath       Date:  2019-06-21       Impact factor: 2.816

2.  Objective sleep quality and metabolic risk in healthy weight children results from the randomized Childhood Adenotonsillectomy Trial (CHAT).

Authors:  Hugi Hilmisson; Neale Lange; Solveig Magnusdottir
Journal:  Sleep Breath       Date:  2019-02-23       Impact factor: 2.816

3.  The effect of continuous positive airway pressure on cardiopulmonary coupling.

Authors:  Jae Hoon Cho; Hyun Jun Kim
Journal:  Sleep Breath       Date:  2016-10-08       Impact factor: 2.816

4.  Cardiopulmonary Coupling.

Authors:  Mi Lu; Thomas Penzel; Robert J Thomas
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 3.650

5.  Ambulatory screening tool for sleep apnea: analyzing a single-lead electrocardiogram signal (ECG).

Authors:  Solveig Magnusdottir; Hugi Hilmisson
Journal:  Sleep Breath       Date:  2017-09-07       Impact factor: 2.816

6.  Cardiopulmonary coupling analysis: changes before and after treatment with a mandibular advancement device.

Authors:  Woo Hyun Lee; Jae-Cheul Ahn; Jaewoon We; Chae-Seo Rhee; Chul Hee Lee; Pil-Young Yun; In-Young Yoon; Jeong-Whun Kim
Journal:  Sleep Breath       Date:  2014-04-04       Impact factor: 2.816

7.  Multicomponent Analysis of Sleep Using Electrocortical, Respiratory, Autonomic and Hemodynamic Signals Reveals Distinct Features of Stable and Unstable NREM and REM Sleep.

Authors:  Christopher Wood; Matt Travis Bianchi; Chang-Ho Yun; Chol Shin; Robert Joseph Thomas
Journal:  Front Physiol       Date:  2020-12-03       Impact factor: 4.566

  7 in total

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