Method for detection of respiratory cycle-related EEG changes in sleep-disordered breathing

• Published in: Sleep (New York, N.Y.) Vol. 27; no. 1; pp. 110 - 115
• Main Authors: CHERVIN, Ronald D, BURNS, Joseph W, SUBOTIC, Nikolas S, ROUSSI, Christopher, THELEN, Brian, RUZICKA, Deborah L
• Format: Journal Article
• Language: English
• Published: Rochester, MN American Academy of Sleep Medicine 01-02-2004
• Subjects: Adenoidectomy; Apnea - complications; Biological and medical sciences; Child; Electroencephalography; Fundamental and applied biological sciences. Psychology; Humans; Male; Medical sciences; Methodology. Experimentation; Non tumoral diseases; Otorhinolaryngology. Stomatology; Periodicity; Polysomnography; Postoperative Period; Preoperative Care; Psychology. Psychoanalysis. Psychiatry; Psychology. Psychophysiology; Psychometrics. Statistics. Methodology; Respiration; Retrospective Studies; Sleep Apnea Syndromes - diagnosis; Sleep Apnea Syndromes - etiology; Tonsillectomy; Upper respiratory tract, upper alimentary tract, paranasal sinuses, salivary glands: diseases, semeiology; Human; Vigilance; Methodology; Upper respiratory tract; Infant; Electroencephalography; Algorithm; Case study; Apnea; Sleep; Tonsillectomy; ENT disease; Developmental stage; Measurement method
• DOI: 10.1093/sleep/27.1.110
• EISSN: 1550-9109
• ISSN: 0161-8105

In sleep-disordered breathing (SDB), visual or computerized analysis of electroencephalogram (EEG) signals shows that disruption of sleep architecture occurs in association with apneas and hypopneas. We developed a new signal analysis algorithm to investigate whether brief changes in cortical activity can also occur with individual respiratory cycles.
Retrospective.
University sleep laboratory.
A 6 year-old boy with SDB.
Polysomnography before and after clinically indicated adenotonsillectomy.
For the first 3 hours of nocturnal sleep, a computer algorithm divided nonapneic respiratory cycles into 4 segments and, for each, computed mean EEG powers within delta, theta, alpha, sigma, and beta frequency ranges. Differences between segment-specific EEG powers were tested by analysis of variance. Respiratory cycle-related EEG changes (RCREC) were quantified.
Preoperative RCREC were statistically significant in delta (P < .0001), theta (P < .001), and sigma (P < .0001) but not alpha or beta (P > .01) ranges. One year after the operation, RCREC in all ranges showed statistical significance (P < .01), but delta, theta, and sigma RCREC had decreased, whereas alpha and beta RCREC had increased. Preoperative RCREC also were demonstrated in a sequence of 101 breaths that contained no apneas or hypopneas (P < .0001). Several tested variations in the signal-analysis approach, including analysis of the entire nocturnal polysomnogram, did not meaningfully improve the significance of RCREC.
In this child with SDB, the EEG varied with respiratory cycles to a quantifiable extent that changed after adenotonsillectomy. We speculate that RCREC may reflect brief but extremely numerous microarousals.