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Measuring Cardiac Autonomic Nervous System (ANS) Activity in Children
Published on: April 29, 2013
ECG-derived cardiopulmonary analysis of pediatric sleep-disordered breathing
Dan Guo1, Chung-Kang Peng, Hui-Li Wu
1Sleep Disorders Center, Meitan General Hospital, Beijing, China. public_scenery@163.com
Insights
Cardiopulmonary coupling (CPC) analysis of ECG signals shows promise for diagnosing pediatric sleep-disordered breathing (SDB). This method correlates well with traditional scoring, offering a potential screening tool for children with SDB.
Area of Science:
- Cardiology
- Pulmonology
- Pediatrics
- Sleep Medicine
Background:
- Pediatric sleep-disordered breathing (SDB) diagnosis relies on resource-intensive polysomnography.
- ECG-derived cardiopulmonary coupling (CPC) sleep spectrogram analysis shows potential for evaluating SDB severity and sleep-modulated autonomic function in adults.
- The study investigates CPC's utility in pediatric SDB assessment.
Purpose of the Study:
- To evaluate the correlation between CPC algorithm-derived metrics and traditional nasal pressure-based apnea-hypopnea scoring in children.
- To determine if CPC analysis can accurately assess SDB severity in pediatric patients.
Main Methods:
- Sixty-three children (mean age 6.2 years) underwent both CPC analysis and conventional cardiorespiratory recordings with nasal flow and desaturation monitoring.
- CPC indices were analyzed for their correlation with standard SDB scoring methods.
Main Results:
- High-frequency coupling (HFC), a CPC marker for stable sleep, decreased with increasing SDB severity.
- HFC durations negatively correlated with respiratory disturbance index (RDI) and oxygen desaturation index.
- CPC-derived RDI (CPC-RDI) strongly correlated with conventional nasal-flow RDI, achieving 85.7% diagnostic accuracy overall in identifying SDB severity.
Conclusions:
- ECG-derived CPC sleep spectrogram metrics correlate with nasal flow-derived respiratory abnormalities in pediatric SDB.
- CPC analysis demonstrates potential as a screening tool for pediatric SDB.
- This method may also aid in monitoring treatment effects, particularly in children with severe SDB.
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.
