Published ahead of print on December 10, 2004, doi:10.1164/rccm.200408-1056OC
© 2005 American Thoracic Society doi: 10.1164/rccm.200408-1056OC
Electroencephalographic Changes during Respiratory Cycles Predict Sleepiness in Sleep ApneaSleep Disorders Center and Department of Neurology, University of Michigan; and Altarum Institute, Ann Arbor, Michigan Correspondence and requests for reprints should be addressed to Ronald D. Chervin, M.D., M.S., Michael S. Aldrich Sleep Disorders Laboratory, University Hospital, 8D8702, P.O. Box 0117, 1500 E. Medical Center Drive, Ann Arbor, MI 48109-0117. E-mail: chervin{at}umich.edu Common polysomnographic measures of sleep-disordered breathing have shown a disappointing ability to predict important consequences such as excessive daytime sleepiness. Using novel analytic techniques, this study tested the hypothesis that numerous, brief disruptions in cortical activity could occur on a breath-to-breath basis during nonapneic sleep. Spectral analysis proved the existence of respiratory cycle-related electroencephalographic changes in each of 38 adult patients evaluated by polysomnography for sleep-disordered breathing. Furthermore, the tendency for sigma (13–15 Hz) electroencephalographic power to vary with the respiratory cycle predicted next-day sleepiness as measured by the multiple sleep latency test. The predictive value was enhanced when the analysis was limited to those 27 patients who had sleep-disordered breathing (more than 5 apneas or hypopneas per hour of sleep). In contrast, nocturnal rates of apneas and hypopneas, as well as minimal oxygen saturation, did not predict sleepiness as well. On average, sigma power increased notably during inspiration, whereas delta (1–4 Hz) power showed a simultaneous decrease. We conclude that electroencephalographic activity shows detectable changes during nonapneic respiratory cycles in adults evaluated for sleep-disordered breathing. Quantification of these changes, which may reflect numerous inspiratory microarousals, could prove useful in prediction of excessive daytime sleepiness.
Key Words: disorders of excessive somnolence • polysomnography • respiratory cycle-related electroencephalographic changes • signal processing, computer assisted • sleep apnea, obstructive This article has been cited by other articles:
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