Literature DB >> 21396891

ECG-derived cardiopulmonary analysis of pediatric sleep-disordered breathing.

Dan Guo1, Chung-Kang Peng, Hui-Li Wu, Joseph E Mietus, Yanhui Liu, Ru-Shan Sun, Robert J Thomas.   

Abstract

BACKGROUND: The diagnosis of sleep-disordered breathing (SDB) and evaluation of sleep quality in the pediatric population is dependent on resource intensive attended polysomnography. An ECG-derived cardiopulmonary coupling sleep spectrogram (CPC) analysis previously described in adults can provide information about the severity of SDB and coupled interactions of sleep modulated autonomic drive and respiration. We hypothesized that CPC algorithm-derived metrics will correlate with nasal pressure-based apnea-hypopnea scoring in pediatric population.
METHODS: A total of 63 subjects (mean 6.2 years; range 2-12 years) were analyzed by both CPC and conventional nasal flow and desaturation scoring obtained during cardiorespiratory recordings. The characteristics of CPC indices and correlation with conventional SDB scoring were computed.
RESULTS: High-frequency coupling (HFC), the CPC marker of stable sleep state, is reduced in proportion to SDB. The HFC durations are negatively correlated with the nasal flow-derived respiratory disturbance index (RDI), a CPC-derived RDI (CPC-RDI), and the 3% oxygen desaturation index (correlation coefficient -0.60, -0.78 and -0.54, respectively). CPC-RDI has a strong positive correlation with the conventional nasal-flow RDI (correlation coefficient 0.70). In this group with a mean nasal-flow RDI 36.1/h, the percentage of correct CPC diagnosis was 85.7% in total, 40% in the non-severe group (10 subjects, RDI <20/h) and 94.3% in the severe group (53 subjects, RDI >20/h).
CONCLUSIONS: ECG-derived sleep spectrogram metrics are correlated with nasal flow-derived respiratory abnormality in pediatric SDB. In suitable clinical contexts, this method may have screening utility and possibly allow tracking of treatment effects, specifically in the children with severe SDB.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 21396891     DOI: 10.1016/j.sleep.2010.09.011

Source DB:  PubMed          Journal:  Sleep Med        ISSN: 1389-9457            Impact factor:   3.492


  10 in total

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

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Authors:  Jie Chen; Shan He
Journal:  PLoS One       Date:  2019-02-22       Impact factor: 3.240

9.  Sleep Apnea Classification Algorithm Development Using a Machine-Learning Framework and Bag-of-Features Derived from Electrocardiogram Spectrograms.

Authors:  Cheng-Yu Lin; Yi-Wen Wang; Febryan Setiawan; Nguyen Thi Hoang Trang; Che-Wei Lin
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10.  Sleep Instabilities Assessed by Cardiopulmonary Coupling Analysis Increase During Childhood and Adolescence.

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  10 in total

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