Obstructive sleep apnea alters sleep stage transition dynamics

• Published in: PloS one Vol. 5; no. 6; p. e11356
• Main Authors: Bianchi, Matt T, Cash, Sydney S, Mietus, Joseph, Peng, Chung-Kang, Thomas, Robert
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 28-06-2010; Public Library of Science (PLoS)
• Subjects: Aged; Apnea; Architecture; Chronic fatigue syndrome; Comparative analysis; Computational Biology; Continuity; Data processing; Decay; Decay rate; Dynamic stability; Dynamics; Emotional disorders; Eye; Eye movements; Female; Heart; Homeostasis; Humans; Interdisciplinary aspects; Kinetics; Male; Markov analysis; Mathematics/Statistics; Middle Aged; NREM sleep; Phenotyping; Physiology; Potassium; Power law; REM sleep; Respiratory Medicine/Sleep and Ventilation Disorders; Sleep; Sleep (NREM); Sleep (REM); Sleep and wakefulness; Sleep apnea; Sleep Apnea Syndromes - physiopathology; Sleep disorders; Sleep Stages; Sleepiness; Stability; Survival analysis; United States > US; Massachusetts
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0011356

Enhanced characterization of sleep architecture, compared with routine polysomnographic metrics such as stage percentages and sleep efficiency, may improve the predictive phenotyping of fragmented sleep. One approach involves using stage transition analysis to characterize sleep continuity.
We analyzed hypnograms from Sleep Heart Health Study (SHHS) participants using the following stage designations: wake after sleep onset (WASO), non-rapid eye movement (NREM) sleep, and REM sleep. We show that individual patient hypnograms contain insufficient number of bouts to adequately describe the transition kinetics, necessitating pooling of data. We compared a control group of individuals free of medications, obstructive sleep apnea (OSA), medical co-morbidities, or sleepiness (n = 374) with mild (n = 496) or severe OSA (n = 338). WASO, REM sleep, and NREM sleep bout durations exhibited multi-exponential temporal dynamics. The presence of OSA accelerated the "decay" rate of NREM and REM sleep bouts, resulting in instability manifesting as shorter bouts and increased number of stage transitions. For WASO bouts, previously attributed to a power law process, a multi-exponential decay described the data well. Simulations demonstrated that a multi-exponential process can mimic a power law distribution.
OSA alters sleep architecture dynamics by decreasing the temporal stability of NREM and REM sleep bouts. Multi-exponential fitting is superior to routine mono-exponential fitting, and may thus provide improved predictive metrics of sleep continuity. However, because a single night of sleep contains insufficient transitions to characterize these dynamics, extended monitoring of sleep, probably at home, would be necessary for individualized clinical application.