Sleep state instabilities in major depressive disorder: Detection and quantification with electrocardiogram-based cardiopulmonary coupling analysis

Authors

  • Albert C. Yang,

    1. Department of Psychiatry, Chu-Tung Veterans Hospital, Hsin-Chu County, Taiwan
    2. Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
    3. Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan
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  • Cheng-Hung Yang,

    1. Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
    2. Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
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  • Chen-Jee Hong,

    1. Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
    2. Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
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  • Shih-Jen Tsai,

    1. Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
    2. Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
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  • Chung-Hsun Kuo,

    1. Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
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  • Chung-Kang Peng,

    1. Division of Interdisciplinary Medicine and Biotechnology and Margret and H. A. Rey Institute for Nonlinear Dynamics in Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA and Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA
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  • Joseph E. Mietus,

    1. Division of Interdisciplinary Medicine and Biotechnology and Margret and H. A. Rey Institute for Nonlinear Dynamics in Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA and Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA
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  • Ary L. Goldberger,

    1. Division of Interdisciplinary Medicine and Biotechnology and Margret and H. A. Rey Institute for Nonlinear Dynamics in Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA and Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA
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  • Robert J. Thomas

    1. Division of Pulmonary, Critical Care and Sleep, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA
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  • The authors wish to thank Shan-Ing Chen and Chen-Ru Wang for their excellent technical assistance. This work was supported by the National Science Council of Taiwan (NSC 95-2314-B-075-111), Taipei Veterans General Hospital (V96C1-083, V97C1-132, V97F-005), the G. Harold and Leila Y. Mathers Foundation, the James S. McDonnell Foundation, the NIH-sponsored Research Resource for Complex Physiologic Signals (UO1EB008577), and DynaDx Corporation, Mountain View, California. The algorithm used in the analysis is based on the cardiopulmonary coupling software developed at the Beth Israel Deaconess Medical Center, Boston, MA by CKP, JEM, ALG, and RJT and licensed to Embla, Inc. CKP and JEM have financial interest in DynaDx Corp.

Address correspondence to: Albert C. Yang, M.D., Department of Psychiatry, Chu-Tung Veterans Hospital, No. 81, Jhongfong Road, Sec. 1, Chu-Tung Township, Hsin-Chu County 31064, Taiwan. E-mail: ccyang@physionet.org

Abstract

Sleep disruption is an important aspect of major depressive disorder but lacks an objective and inexpensive means of assessment. We evaluated the utility of electrocardiogram (ECG)-based cardiopulmonary coupling analysis to quantify physiologic sleep stability in patients with major depression. Relative to controls, unmedicated depressed patients had a reduction in high-frequency coupling, an index of stable sleep, an increase in low-frequency coupling, an index of unstable sleep, and an increase in very-low-frequency coupling, an index of wakefulness/REM sleep. The medicated depressed group showed a restoration of stable sleep to a level comparable with that of the control group. ECG-based cardiopulmonary coupling analysis may provide a simple, cost-efficient point-of-care method to quantify sleep quality/stability and to objectively evaluate the severity of insomnia in patients with major depression.

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