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Lu M, Penzel T, Thomas RJ. Cardiopulmonary Coupling. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1384:185-204. [PMID: 36217085 DOI: 10.1007/978-3-031-06413-5_11] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Cardiopulmonary coupling (CPC) is a technique that generates sleep spectrogram by calculating the cross-spectral power and coherence of heart rate variability and respiratory tidal volume fluctuations. There are several forms of CPC in the sleep spectrogram, which may provide information about normal sleep physiology and pathological sleep states. Since CPC can be calculated from any signal recording containing heart rate and respiration information, such as photoplethysmography (PPG) or blood pressure, it can be widely used in various applications, including wearables and non-contact devices. When derived from PPG, an automatic apnea-hypopnea index can be calculated from CPC-oximetry as PPG can be obtained from oximetry alone. CPC-based sleep profiling reveals the effects of stable and unstable sleep on sleep apnea, insomnia, cardiovascular regulation, and metabolic disorders. Here, we introduce, with examples, the current knowledge and understanding of the CPC technique, especially the physiological basis, analytical methods, and its clinical applications.
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Affiliation(s)
- Mi Lu
- Department of Otolaryngology-Head and Neck Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
- Interdisciplinary Center of Sleep Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.
| | - Thomas Penzel
- Interdisciplinary Center of Sleep Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Robert J Thomas
- Division of Pulmonary and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
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2
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Sivam S, Wang D, Wong KKH, Piper AJ, Zheng YZ, Gauthier G, Hockings C, McGuinness O, Menadue C, Melehan K, Cooper S, Hilmisson H, Phillips CL, Thomas RJ, Yee BJ, Grunstein RR. Cardiopulmonary coupling and serum cardiac biomarkers in obesity hypoventilation syndrome and obstructive sleep apnea with morbid obesity. J Clin Sleep Med 2021; 18:1063-1071. [PMID: 34879904 DOI: 10.5664/jcsm.9804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
STUDY OBJECTIVES The main cause of death in patients with obesity hypoventilation syndrome (OHS) is cardiac rather than respiratory failure. Here, we investigated autonomic-respiratory coupling and serum cardiac biomarkers in patients with OHS and obstructive sleep apnea (OSA) with comparable body mass index (BMI) and apnea-hypopnea index (AHI). METHODS Cardiopulmonary coupling (CPC) and cyclic variation of heart rate (CVHR) analysis was performed on the electrocardiogram signal from the overnight polysomnogram. Cardiac serum biomarkers were obtained in patients with OHS and OSA with a BMI > 40kg/m2. Samples were obtained at baseline and after 3 months of positive airway pressure (PAP) therapy in both groups. RESULTS Patients with OHS (n=15) and OSA (n=36) were recruited. No group differences in CPC, CVHR and serum biomarkers were observed at baseline and after 3 months of PAP therapy. An improvement in several CPC metrics, including the sleep apnea index, unstable sleep (low frequency coupling and elevated low frequency coupling narrow band [e-LFCNB]) and CVHR were observed in both groups with PAP use. However, distinct differences in response characteristics were noted. e-LFCNB coupling correlated with highly sensitive troponin (hs-troponin-T, p<0.05) in the combined cohort. Baseline hs-troponin-T inversely correlated with awake oxygen saturation in the OHS group (p<0.05). CONCLUSIONS PAP therapy can significantly improve CPC stability in obese patients with OSA or OHS, with key differences. e-LFCNB may function as a surrogate biomarker for early subclinical cardiac disease. Low awake oxygen saturation could also increase this biomarker in OHS. CLINICAL TRIAL REGISTRATION Registry: Australian New Zealand Clinical Trials Registry; Name: Obesity Hypoventilation Syndrome and Neurocognitive Dysfunction; URL: https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=367492; Identifier: ACTRN12615000122550.
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Affiliation(s)
- Sheila Sivam
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia.,Woolcock Institute of Medical Research, Sleep and Circadian Research Group, Sydney, Australia
| | - David Wang
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia.,Woolcock Institute of Medical Research, Sleep and Circadian Research Group, Sydney, Australia
| | - Keith K H Wong
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia.,Woolcock Institute of Medical Research, Sleep and Circadian Research Group, Sydney, Australia
| | - Amanda J Piper
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia.,Woolcock Institute of Medical Research, Sleep and Circadian Research Group, Sydney, Australia
| | - Yi Zhong Zheng
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia.,Woolcock Institute of Medical Research, Sleep and Circadian Research Group, Sydney, Australia
| | - Gislaine Gauthier
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Christine Hockings
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Olivia McGuinness
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Collette Menadue
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Kerri Melehan
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Sara Cooper
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia.,Woolcock Institute of Medical Research, Sleep and Circadian Research Group, Sydney, Australia
| | | | - Craig L Phillips
- Faculty of Medicine and Health, University of Sydney, Sydney, Australia.,Woolcock Institute of Medical Research, Sleep and Circadian Research Group, Sydney, Australia
| | - Robert J Thomas
- Department of Medicine, Division of Pulmonary, Critical Care & Sleep Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Brendon J Yee
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia.,Woolcock Institute of Medical Research, Sleep and Circadian Research Group, Sydney, Australia
| | - Ronald R Grunstein
- Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, Australia.,Woolcock Institute of Medical Research, Sleep and Circadian Research Group, Sydney, Australia
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Al Ashry HS, Ni Y, Thomas RJ. Cardiopulmonary Sleep Spectrograms Open a Novel Window Into Sleep Biology-Implications for Health and Disease. Front Neurosci 2021; 15:755464. [PMID: 34867165 PMCID: PMC8633537 DOI: 10.3389/fnins.2021.755464] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 10/08/2021] [Indexed: 02/05/2023] Open
Abstract
The interactions of heart rate variability and respiratory rate and tidal volume fluctuations provide key information about normal and abnormal sleep. A set of metrics can be computed by analysis of coupling and coherence of these signals, cardiopulmonary coupling (CPC). There are several forms of CPC, which may provide information about normal sleep physiology, and pathological sleep states ranging from insomnia to sleep apnea and hypertension. As CPC may be computed from reduced or limited signals such as the electrocardiogram or photoplethysmogram (PPG) vs. full polysomnography, wide application including in wearable and non-contact devices is possible. When computed from PPG, which may be acquired from oximetry alone, an automated apnea hypopnea index derived from CPC-oximetry can be calculated. Sleep profiling using CPC demonstrates the impact of stable and unstable sleep on insomnia (exaggerated variability), hypertension (unstable sleep as risk factor), improved glucose handling (associated with stable sleep), drug effects (benzodiazepines increase sleep stability), sleep apnea phenotypes (obstructive vs. central sleep apnea), sleep fragmentations due to psychiatric disorders (increased unstable sleep in depression).
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Affiliation(s)
- Haitham S Al Ashry
- Division of Pulmonary and Sleep Medicine, Elliot Health System, Manchester, NH, United States
| | - Yuenan Ni
- Division of Pulmonary, Critical Care and Sleep Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Robert J Thomas
- Division of Pulmonary and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States
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Malhotra A, Ayappa I, Ayas N, Collop N, Kirsch D, Mcardle N, Mehra R, Pack AI, Punjabi N, White DP, Gottlieb DJ. Metrics of sleep apnea severity: beyond the apnea-hypopnea index. Sleep 2021; 44:zsab030. [PMID: 33693939 PMCID: PMC8271129 DOI: 10.1093/sleep/zsab030] [Citation(s) in RCA: 173] [Impact Index Per Article: 57.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 01/31/2021] [Indexed: 12/13/2022] Open
Abstract
Obstructive sleep apnea (OSA) is thought to affect almost 1 billion people worldwide. OSA has well established cardiovascular and neurocognitive sequelae, although the optimal metric to assess its severity and/or potential response to therapy remains unclear. The apnea-hypopnea index (AHI) is well established; thus, we review its history and predictive value in various different clinical contexts. Although the AHI is often criticized for its limitations, it remains the best studied metric of OSA severity, albeit imperfect. We further review the potential value of alternative metrics including hypoxic burden, arousal intensity, odds ratio product, and cardiopulmonary coupling. We conclude with possible future directions to capture clinically meaningful OSA endophenotypes including the use of genetics, blood biomarkers, machine/deep learning and wearable technologies. Further research in OSA should be directed towards providing diagnostic and prognostic information to make the OSA diagnosis more accessible and to improving prognostic information regarding OSA consequences, in order to guide patient care and to help in the design of future clinical trials.
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Affiliation(s)
- Atul Malhotra
- Department of Medicine, University of California San Diego, La Jolla, CA
| | - Indu Ayappa
- Department of Medicine, Mt. Sinai, New York, NY
| | - Najib Ayas
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Nancy Collop
- Department of Medicine, Emory University, Atlanta, GA
| | - Douglas Kirsch
- Department of Medicine, Atrium Health Sleep Medicine, Atrium Health, Charlotte, NC
| | - Nigel Mcardle
- Department of Medicine, The University of Western Australia, Perth, Australia
| | - Reena Mehra
- Department of Medicine, Cleveland Clinic, Cleveland, OH
| | - Allan I Pack
- Department of Medicine, University of Pennsylvania, Philadelphia, PA
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Seo MY, Han MS, Jeong YJ, Lee MK, Park S, Hwang SJ, Lee SH. Variation in Sleep Stability with Differences in Severity of Sleep-Disordered Breathing in Children. Laryngoscope 2020; 131:435-439. [PMID: 32473062 DOI: 10.1002/lary.28769] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 04/06/2020] [Accepted: 05/07/2020] [Indexed: 11/08/2022]
Abstract
OBJECTIVES The aim of this study was to analyze the association between obstructive sleep apnea (OSA) severity and various cardiopulmonary coupling (CPC) parameters in children with OSA. STUDY DESIGN Retrospective cross-sectional study. METHODS A cross-sectional study was conducted among 117 children (aged 7.96 ± 3.54 years, 86 male) who underwent both full-night polysomnography (PSG) and CPC for suspicion of sleep-disordered breathing (SDB). We analyzed the association between various CPC and PSG findings. RESULTS The apnea-hypopnea index (AHI) was negatively correlated with high frequency coupling (HFC, r = -0.374, P < .001) and very low frequency coupling (VLFC, r = -0.192, P = .038) and positively correlated with low frequency coupling (LFC, r = 0.503, P < .001), elevated low frequency coupling (e-LFC, r = 0.475, P < .001), and narrow and broad band e-LFC (e-LFCNB and e-LFCBB ; r = 0.221, P = .016 and r = 0.468, P < .001, respectively). The arousal index was negatively correlated with HFC (r = - 0.466, P < .001) and positively correlated with LFC, e-LFC, e-LFCNB , and e-LFCBB (r = 0.543, r = 0.460, r = 0.239, and r = 0.445, respectively; all P < .001). In addition, we also found a significant difference in various CPC values according to OSA severity. CONCLUSION CPC parameters accurately reflect sleep fragmentation and OSA severity in children. Thus, we can verify objective sleep quality using CPC analysis, which is a simple method of analyzing sleep stability in children with SDB. LEVEL OF EVIDENCE 4 Laryngoscope, 131:435-439, 2021.
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Affiliation(s)
- Min Young Seo
- Division of Rhinology & Sleep Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, South Korea
| | - Mun Soo Han
- Division of Rhinology & Sleep Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, South Korea
| | - Yong Jun Jeong
- Division of Rhinology & Sleep Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, South Korea
| | - Min Kyu Lee
- Division of Rhinology & Sleep Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, South Korea
| | - Seongbin Park
- Division of Rhinology & Sleep Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, South Korea
| | - Sun Jin Hwang
- Division of Rhinology & Sleep Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, South Korea
| | - Seung Hoon Lee
- Division of Rhinology & Sleep Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, South Korea
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Cao W, Luo J, Xiao Y. A Review of Current Tools Used for Evaluating the Severity of Obstructive Sleep Apnea. Nat Sci Sleep 2020; 12:1023-1031. [PMID: 33239929 PMCID: PMC7680675 DOI: 10.2147/nss.s275252] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 10/08/2020] [Indexed: 12/21/2022] Open
Abstract
Obstructive sleep apnea (OSA) is a common and heterogeneous disease characterized by episodic collapse within the upper airways, which leads to reduced ventilation and adverse consequences, including hypoxia, hypercapnia, sleep fragmentation, and long-term effects such as cardiovascular comorbidities. The clinical diagnosis of OSA and its severity classification are often determined based on the apnea-hypopnea index (AHI), defining the number of apneic and hypopnea events per hour of sleep. However, the limitations of the AHI to assess disease severity have necessitated the exploration of other metrics for additional information to reflect the complexity of OSA. Novel parameters such as the hypoxic burden have the potential to better capture the main features of OSA by maximizing the information available from the polysomnogram. These emerging measures have described multidimensional qualities of sleep-disordered breathing events and breathing irregularity and will ultimately result in better management of OSA.
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Affiliation(s)
- Wenhao Cao
- Department of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China
| | - Jinmei Luo
- Department of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China
| | - Yi Xiao
- Department of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China
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Seo MY, Hwang SJ, Nam KJ, Lee SH. Significance of sleep stability using cardiopulmonary coupling in sleep disordered breathing. Laryngoscope 2019; 130:2069-2075. [PMID: 31750962 DOI: 10.1002/lary.28379] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 09/17/2019] [Accepted: 10/03/2019] [Indexed: 11/11/2022]
Abstract
OBJECTIVES The aim of this study was to assess the sleep quality and sleep stability according to the severity of obstructive sleep apnea (OSA) by using questionnaires and cardiopulmonary coupling (CPC) analysis. METHODS Two hundred and twenty-one adults were evaluated using subjective sleep questionnaires, CPC parameters, and respiratory parameters measured during full-night polysomnography. We measured the differences in the CPC parameters of each OSA group and the correlation between the apnea-hypopnea index (AHI) and CPC parameters. RESULTS AHI and CPC parameters were not associated with sleep questionnaires. AHI is negatively correlated with high frequency coupling (HFC, r = -0.725, P < 0.001) and very low frequency coupling (VLFC, r = -0.475, P < 0.001), but it is positively correlated with low frequency coupling (LFC, r = 0.786, P < 0.001) and narrow- and broadband-elevated low frequency coupling (e-LFCNB and e-LFCBB ; r = 0.522, P < 0.001 and r = 0.668, P < 0.001, respectively). We also found similar results regarding the correlation between the arousal index and CPC parameters. In addition, there were significant differences in HFC, LFC, VLFC, e-LFCNB , and e-LFCBB (all P < 0.001) between the severe OSA group and all other groups. CONCLUSION We found that CPC parameters significantly correlated with AHI. In addition, sleep stability-related parameters differ significantly based on OSA severity, and apneic parameters in the severe OSA group are significantly different from those in the other groups. LEVEL OF EVIDENCE 4 Laryngoscope, 130: 2069-2075, 2020.
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Affiliation(s)
- Min Young Seo
- Division of Rhinology & Sleep Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Korea University Ansan Hospital, Ansan, Korea University College of Medicine, Ansan-city, Gyeonggi-do, Republic of Korea
| | - Sun Jin Hwang
- Division of Rhinology & Sleep Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Korea University Ansan Hospital, Ansan, Korea University College of Medicine, Ansan-city, Gyeonggi-do, Republic of Korea
| | - Kuk Jin Nam
- Division of Rhinology & Sleep Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Korea University Ansan Hospital, Ansan, Korea University College of Medicine, Ansan-city, Gyeonggi-do, Republic of Korea
| | - Seung Hoon Lee
- Division of Rhinology & Sleep Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Korea University Ansan Hospital, Ansan, Korea University College of Medicine, Ansan-city, Gyeonggi-do, Republic of Korea
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