Detecting pediatric sleep apnea: consistency on cardiopulmonary coupling and oximetry measurement

Authors:
Y. Ma, J. Yeh, S. Sun, J. Qiao, C. Peng

Reference:
​Sleep Medicine Volume 14, Supplement 1, December 2013, Page e189

Objectives:
Cardiopulmonary coupling (CPC) analysis is an approach of data extracted from a single channel of ECG, and is highly correlated with the actual respiration. There have been an increasing number of papers evaluating CPC or using CPC as a clinical measurement. It has been recommended, based on several studies, to be a screening tool for sleep disorders, especially sleep related breathing disorders (SDB). Previous studies have suggested that adding oximetry would improve the reliability of clinical evaluation. This study was designed to investigate the consistency rate between CPC sleep spectrogram and Oximetry results on detecting sleep apneas.

Conclusions:
CPC can be used for clinical evaluation, such as detecting sleep apneas. It has advantage for screening sleep on pediatric populations. In addition to its simplicity and cost-effectiveness, the reliable results and acceptability can make it practical. Adding actigraphy and/or oximetry will improve its clinical applications. More and better designed clinical studies are worth expecting in the future.

Practical Significance:
Materials and methods

Target subjects are children with OSA, 2–8 yr, who have full-night oximetry and ECG-recorded data with at least 80% qualified data for analysis. All data was time synchronized with ECG data. Value of SpO2 and pulse rate was collected from full night oximetry, and sensors were placed on the fingertips. Based on the sleep physiology and mechanism of CPC, High frequency coupling (HFC) and low-frequency coupling (LFC) are the marker of stable sleep and unstable sleep respectively. Fragmented sleep is characterized by coupled low-frequency behaviors across numerous sleep based physiological stream.

Results

37 children (14 girls and 23 boys, 5.0±1.7 yr, BMI:16.10±2.25) were included with recorded SPO2 min (77.94±7.69)% and the total consistency rate between CPC sleep spectrogram and Oximetry result was (78.17±11.46)%. With mild OSA, 5 children (3 girls and 2 boys, 5.6±2.2 yr, BMI:15.47±1.20) showed SPO2 min with (91.64±2.04)% and consistency rate (87.05±6.43)%. With moderate OSA, 9 children (5 girls and 4 boys, 5.6 ±1.6 yr, BMI:15.65±2.00) were recorded with SPO2min (84.12±2.1)% and consistency rate was (79.07±14.80)%. With sever OSA, 23 children (5 girls and 17 boys, 4.7±1.6 yr, BMI:16.77±2.44) showed SPO2min (72.81±2.48)% and consistency rate (77.93±10.44)%.

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ECG-derived Cardiopulmonary Analysis of Pediatric Sleep-Disordered Breathing

Authors:
Guo D, Peng CK, Wu H, L,Mietus JE, Liu Y, Sun RS, Thomas RJ

Reference:
Sleep Medicine 2011;12(4): 384-389

Objectives:
An ECG-derived sleep spectrogram, based on CPC analysis previously described in adults, can provide information about the severity of sleep disordered breathing (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.

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 children with severe SDB

Practical Significance:
The high correlation between CPC metrics and nasal flow derived metrics in pediatric SDB patients demonstrates an opportunity to screen for SDB and track treatment effects.

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Measuring sleep quality after adenotonsillectomy in pediatric sleep apnea.

Authors:
Lee SH, Choi JH, Park IH, Lee SH, Kim TH, Lee HM, Park HK, Thomas RJ, Shin C, Yun CH.

Reference:
Laryngoscope. 2012 Sep;122(9):2115-21.

Objectives:
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.

Conclusions:
Adenotonsillectomy led to a significant change in CPC parameters (HFC, LFC), which was paralleled by significant improvements in the apnea-hypopnea and arousal index. Polysomnographic sleep stage parameters other than the arousal index did not reflect postoperative resolution of OSA.

Practical Significance:
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.

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

Authors:
Hilmisson, H., Lange, N. & Magnusdottir, S.

Reference:
Sleep Breath (2019).

Objectives:
Background
We hypothesized that cardiopulmonary coupling (CPC) sleep quality reflects cardiovascular and cardiometabolic health, in healthy weight children.

Methods
Retrospective signal analysis of existing ECG data utilizing CPC, FDA cleared, software as medical device (SaMD). ECG signals were extracted from baseline polysomnography studies in the prospective Childhood Adenotonsillectomy Trial database, multicenter, single-blind, randomized controlled trial of 5.0–9.9-year-old children identified with obstructive sleep apnea syndrome without severe hypoxemia. Healthy weight was defined as age and gender-specific BMI in the 5th–85th percentile range and overweight above the 85th percentile. The cohort was stratified based on CPC sleep quality Index (SQI) defined as high sleep quality (SQI  ≥ 80) or low sleep quality (SQI < 60). Cardiovascular, cardiometabolic, quality of life, and cognition were compared between the sleep quality groups.

Conclusions:
CPC sleep quality offers insights into pediatric sleep and how it affects cardiovascular and cardiometabolic health. ECG is simple signal to collect, which makes this method practical for testing sleep, over multiple nights, and on multiple occasions providing information on sleep dynamics not possible before.

Practical Significance:
Healthy weight children with low sleep quality had more fragmented sleep with significantly higher arousal index (10.0 ± 4.3 vs.7.2 ± 3.1; p = 0.00) and eLFCBB (12.4 ± 4.9 vs. 0.9 ± 1.0; p < 0.001) CPC indicator of sleep fragmentation, higher average heart rate during sleep (84.5 ± 10.6 vs. 79.4 ± 7.1; p = 0.03) and worse insulin/glucose ratio (1.7 ± 1.6 vs. 1.1 ± 1.1; p = 0.03) and fasting insulin levels (7.9 ± 7.2 vs.5.3 ± 5.5; p = 0.05) when compared to healthy weight children with high sleep quality. SQI significantly correlates with average heart rate during sleep, insulin and triglyceride levels; for a unit increase in SQI, there is 0.154 unit decrease in average heart rate during sleep, 0.109 unit in insulin levels and 0.332 unit in triglyceride levels, respectively.

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