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Anwar AI, Byrne S, Sharma A, Sands S, Wellman A, Redeker NS, Yaggi H, Zinchuk AV. Novel physiologic predictors of positive airway pressure effectiveness (NICEPAP) study: rationale, design and methods. Sleep Breath 2024:10.1007/s11325-024-03099-w. [PMID: 38995327 DOI: 10.1007/s11325-024-03099-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 06/10/2024] [Accepted: 06/28/2024] [Indexed: 07/13/2024]
Abstract
PURPOSE Continuous positive airway pressure (CPAP) is the primary therapy for obstructive sleep apnea (OSA); however the effectiveness of CPAP remains suboptimal. We describe the Novel PhysIologiC prEdictors of Positive Airway Pressure Effectiveness (NICEPAP) study. Its purpose is to determine whether physiological traits of OSA contribute to CPAP effectiveness. METHODS NICEPAP (NCT05067088) is a prospective, observational cohort study conducted at an academic sleep center. Adults newly diagnosed with OSA (n = 267) are assessed for OSA traits of loop gain, arousal threshold, pharyngeal collapsibility, and muscle compensation from baseline polysomnography. We perform a comprehensive assessment of covariates relevant to CPAP adherence, efficacy, and patient-centered outcomes. Participants are followed for 12 months. Primary outcomes include (1) CPAP adherence (hours/night), (2) CPAP efficacy (apneas-hypopneas/hour), and (3) quality of life at six months measured by objective CPAP data and Functional Outcomes of Sleep Questionnaire. Secondary outcomes include sleep quality, sleepiness, insomnia, and neurocognitive function. RESULTS Data on covariates, including demographics, sleep symptoms, medical history, medications, sleep quality, OSA and treatment self-efficacy, decisional balance, and socio-economic and social and partner support, are collected using validated instruments. The analysis for primary outcomes includes a generalized linear mixed model for an outcome (e.g., CPAP adherence) with OSA traits as exposures followed by the addition of relevant covariates. CONCLUSION The findings of the NICEPAP study will inform research aimed to enhance CPAP effectiveness. Understanding the role of physiological OSA traits in CPAP effectiveness is a crucial step toward a precision medicine approach to OSA.
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Affiliation(s)
- Andira I Anwar
- Department of Medicine, Yale University School of Medicine, 300 Cedar Street, New Haven, Connecticut, CT, 06443, USA
| | - Sean Byrne
- Department of Medicine, Yale University School of Medicine, 300 Cedar Street, New Haven, Connecticut, CT, 06443, USA
| | - Akanksha Sharma
- University of Pittsburgh Medical Center Mercy, Pittsburgh, PA, USA
| | - Scott Sands
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrew Wellman
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Nancy S Redeker
- University of Connecticut School of Nursing, Connecticut, USA
| | - Henry Yaggi
- Department of Medicine, Yale University School of Medicine, 300 Cedar Street, New Haven, Connecticut, CT, 06443, USA
| | - Andrey V Zinchuk
- Department of Medicine, Yale University School of Medicine, 300 Cedar Street, New Haven, Connecticut, CT, 06443, USA.
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2
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Thomas RJ. REM sleep breathing: Insights beyond conventional respiratory metrics. J Sleep Res 2024:e14270. [PMID: 38960862 DOI: 10.1111/jsr.14270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Accepted: 05/29/2024] [Indexed: 07/05/2024]
Abstract
Breathing and sleep state are tightly linked. The traditional approach to evaluation of breathing in rapid eye movement sleep has been to focus on apneas and hypopneas, and associated hypoxia or hypercapnia. However, rapid eye movement sleep breathing offers novel insights into sleep physiology and pathology, secondary to complex interactions of rapid eye movement state and cardiorespiratory biology. In this review, morphological analysis of clinical polysomnogram data to assess respiratory patterns and associations across a range of health and disease is presented. There are several relatively unique insights that may be evident by assessment of breathing during rapid eye movement sleep. These include the original discovery of rapid eye movement sleep and scoring of neonatal sleep, control of breathing in rapid eye movement sleep, rapid eye movement sleep homeostasis, sleep apnea endotyping and pharmacotherapy, rapid eye movement sleep stability, non-electroencephalogram sleep staging, influences on cataplexy, mimics of rapid eye movement behaviour disorder, a reflection of autonomic health, and insights into cardiac arrhythmogenesis. In summary, there is rich clinically actionable information beyond sleep apnea encoded in the respiratory patterns of rapid eye movement sleep.
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Affiliation(s)
- Robert Joseph Thomas
- Department of Medicine, Division of Pulmonary Critical Care & Sleep Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, Massachusetts, USA
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3
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Shah AJ, Vaccarino V, Goldberg J, Huang M, Ko YA, Ma X, Levantsevych OM, Smith NL, Alagar N, Mousselli I, Johnson DA, Clifford GD, Bremner JD, Bliwise DL. Posttraumatic Stress Disorder and Obstructive Sleep Apnea in Twins. JAMA Netw Open 2024; 7:e2416352. [PMID: 38913378 PMCID: PMC11197451 DOI: 10.1001/jamanetworkopen.2024.16352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 03/13/2024] [Indexed: 06/25/2024] Open
Abstract
Importance Obstructive sleep apnea (OSA) is a common condition in older adult (aged >65 years) populations, but more mechanistic research is needed to individualize treatments. Previous evidence has suggested an association between OSA and posttraumatic stress disorder (PTSD) but is limited by possible selection bias. High-quality research on this association with a careful evaluation of possible confounders may yield important mechanistic insight into both conditions and improve treatment efforts. Objective To investigate the association of current PTSD symptoms and PTSD diagnosis with OSA. Design, Setting, and Participants This cross-sectional study of twin pairs discordant for PTSD, which allows for adjustment for familial factors, was conducted using in-laboratory polysomnography from March 20, 2017, to June 3, 2019. The study sample comprised male veteran twins recruited from the Vietnam Era Twin Registry. The data analysis was performed between June 11, 2022, and January 30, 2023. Exposure Symptoms of PTSD in twins who served in the Vietnam War. Diagnosis of PTSD was a secondary exposure. Main Outcomes and Measures Obstructive sleep apnea was assessed using the apnea-hypopnea index (AHI) (≥4% oxygen saturation criterion as measured by events per hour) with overnight polysomnography. Symptoms of PTSD were assessed using the PTSD Checklist (PCL) and structured clinical interview for PTSD diagnosis. Results A total of 181 male twins (mean [SD] age, 68.4 [2.0] years) including 66 pairs discordant for PTSD symptoms and 15 pairs discordant for a current PTSD diagnosis were evaluated. In models examining the PCL and OSA within pairs and adjusted for body mass index (BMI) and other sociodemographic, cardiovascular, and psychiatric risk factors (including depression), each 15-point increase in PCL was associated with a 4.6 (95% CI, 0.1-9.1) events-per-hour higher AHI. Current PTSD diagnosis was associated with an adjusted 10.5 (95% CI, 5.7-15.3) events-per-hour higher AHI per sleep-hour. Comparable standardized estimates of the association of PTSD symptoms and BMI with AHI per SD increase (1.9 events per hour; 95% CI, 0.5-3.3 events per hour) were found. Conclusions and Relevance This cross-sectional study found an association between PTSD and sleep-disordered breathing. The findings have important public health implications and may also enhance understanding of the many factors that potentially affect OSA pathophysiology.
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Affiliation(s)
- Amit J. Shah
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
- Department of Medicine, Emory University School of Medicine, Atlanta, Georgia
- Atlanta Veterans Affairs Healthcare System, Decatur, Georgia
| | - Viola Vaccarino
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
- Department of Medicine, Emory University School of Medicine, Atlanta, Georgia
| | - Jack Goldberg
- Seattle Epidemiologic Research and Information Center, Office of Research and Development, Department of Veterans Affairs, Seattle, Washington
- Department of Epidemiology, University of Washington, Seattle
| | - Minxuan Huang
- Department of Pediatrics, Stanford University, California
| | - Yi-An Ko
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Xin Ma
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York
| | - Oleksiy M. Levantsevych
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Nicholas L. Smith
- Seattle Epidemiologic Research and Information Center, Office of Research and Development, Department of Veterans Affairs, Seattle, Washington
- Department of Epidemiology, University of Washington, Seattle
| | - Nikila Alagar
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Iman Mousselli
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Dayna A. Johnson
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Gari D. Clifford
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, Georgia
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
| | - J. Douglas Bremner
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Donald L. Bliwise
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia
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Vennard H, Buchan E, Davies P, Gibson N, Lowe D, Langley R. Paediatric sleep diagnostics in the 21st century: the era of "sleep-omics"? Eur Respir Rev 2024; 33:240041. [PMID: 38925792 PMCID: PMC11216690 DOI: 10.1183/16000617.0041-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 04/16/2024] [Indexed: 06/28/2024] Open
Abstract
Paediatric sleep diagnostics is performed using complex multichannel tests in specialised centres, limiting access and availability and resulting in delayed diagnosis and management. Such investigations are often challenging due to patient size (prematurity), tolerability, and compliance with "gold standard" equipment. Children with sensory/behavioural issues, at increased risk of sleep disordered breathing (SDB), often find standard diagnostic equipment difficult.SDB can have implications for a child both in terms of physical health and neurocognitive development. Potential sequelae of untreated SDB includes failure to thrive, cardiopulmonary disease, impaired learning and behavioural issues. Prompt and accurate diagnosis of SDB is important to facilitate early intervention and improve outcomes.The current gold-standard diagnostic test for SDB is polysomnography (PSG), which is expensive, requiring the interpretation of a highly specialised physiologist. PSG is not feasible in low-income countries or outwith specialist sleep centres. During the coronavirus disease 2019 pandemic, efforts were made to improve remote monitoring and diagnostics in paediatric sleep medicine, resulting in a paradigm shift in SDB technology with a focus on automated diagnosis harnessing artificial intelligence (AI). AI enables interrogation of large datasets, setting the scene for an era of "sleep-omics", characterising the endotypic and phenotypic bedrock of SDB by drawing on genetic, lifestyle and demographic information. The National Institute for Health and Care Excellence recently announced a programme for the development of automated home-testing devices for SDB. Scorer-independent scalable diagnostic approaches for paediatric SDB have potential to improve diagnostic accuracy, accessibility and patient tolerability; reduce health inequalities; and yield downstream economic and environmental benefits.
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Affiliation(s)
- Hannah Vennard
- College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
- Department of Paediatric Respiratory and Sleep Medicine, Royal Hospital for Children, Glasgow, UK
| | - Elise Buchan
- Department of Paediatric Respiratory and Sleep Medicine, Royal Hospital for Children, Glasgow, UK
| | - Philip Davies
- Department of Paediatric Respiratory and Sleep Medicine, Royal Hospital for Children, Glasgow, UK
| | - Neil Gibson
- Department of Paediatric Respiratory and Sleep Medicine, Royal Hospital for Children, Glasgow, UK
| | - David Lowe
- College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Ross Langley
- College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
- Department of Paediatric Respiratory and Sleep Medicine, Royal Hospital for Children, Glasgow, UK
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Cheng WJ, Finnsson E, Ágústsson JS, Sands SA, Hang LW. Endotypic traits of supine position and supine-predominant obstructive sleep apnoea in Asian patients. Eur Respir J 2024; 63:2301660. [PMID: 38212076 DOI: 10.1183/13993003.01660-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 12/22/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND Over half of all cases of obstructive sleep apnoea (OSA) are classified as supine-related OSA; however, the pathological endotype during supine position is not fully understood. This study aims to investigate the endotypic traits of supine-predominant OSA and explore the variations in endotypic traits between the supine and lateral positions. METHODS We prospectively recruited 689 adult patients with OSA from a single sleep centre between April 2020 and December 2022. Endotypic traits, namely arousal threshold, collapsibility, loop gain and upper airway muscle compensation, were retrieved from polysomnographic signals. We identified spOSA by a supine to non-supine apnoea-hypopnoea index (AHI) ratio >2. We cross-sectionally compared demographic and endotypic traits between supine-predominant OSA and non-positional OSA and examined the associations between supine-predominant OSA and endotypic traits. Additionally, we compared the changes in endotypic traits between supine and lateral positions in patients with supine-predominant OSA and non-positional OSA. RESULTS In our study sample, 75.8% of patients were identified as having supine-predominant OSA. Compared to non-positional OSA, supine-predominant OSA was associated with low collapsibility (β= -3.46 %eupnoea, 95% CI -5.93- -1.00 %eupnoea) and reduced compensation (β= -6.79 %eupnoea, 95% CI -10.60- -2.99 %eupnoea). When transitioning from the lateral to supine position, patients with supine-predominant OSA had a substantial decrease in compensation compared to those with non-positional OSA (-11.98 versus -6.28 %eupnoea). CONCLUSIONS Supine-predominant OSA is the prevalent phenotype of OSA in Asian patients. Inadequate upper airway compensation appears to be a crucial underlying pathology in patients with supine-predominant OSA.
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Affiliation(s)
- Wan-Ju Cheng
- Department of Psychiatry, China Medical University Hospital, Taichung, Taiwan
- Department of Public Health, China Medical University, Taichung, Taiwan
- National Center for Geriatrics and Welfare Research, National Health Research Institutes, Miaoli, Taiwan
| | | | | | - Scott A Sands
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Liang-Wen Hang
- College of Medicine, China Medical University, Taichung, Taiwan
- Sleep Medicine Center, Department of Pulmonary and Critical Care Medicine, China Medical University Hospital, Taichung, Taiwan
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Cohen O, Kundel V, Robson P, Al-Taie Z, Suárez-Fariñas M, Shah NA. Achieving Better Understanding of Obstructive Sleep Apnea Treatment Effects on Cardiovascular Disease Outcomes through Machine Learning Approaches: A Narrative Review. J Clin Med 2024; 13:1415. [PMID: 38592223 PMCID: PMC10932326 DOI: 10.3390/jcm13051415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 02/13/2024] [Accepted: 02/17/2024] [Indexed: 04/10/2024] Open
Abstract
Obstructive sleep apnea (OSA) affects almost a billion people worldwide and is associated with a myriad of adverse health outcomes. Among the most prevalent and morbid are cardiovascular diseases (CVDs). Nonetheless, randomized controlled trials (RCTs) of OSA treatment have failed to show improvements in CVD outcomes. A major limitation in our field is the lack of precision in defining OSA and specifically subgroups with the potential to benefit from therapy. Further, this has called into question the validity of using the time-honored apnea-hypopnea index as the ultimate defining criteria for OSA. Recent applications of advanced statistical methods and machine learning have brought to light a variety of OSA endotypes and phenotypes. These methods also provide an opportunity to understand the interaction between OSA and comorbid diseases for better CVD risk stratification. Lastly, machine learning and specifically heterogeneous treatment effects modeling can help uncover subgroups with differential outcomes after treatment initiation. In an era of data sharing and big data, these techniques will be at the forefront of OSA research. Advanced data science methods, such as machine-learning analyses and artificial intelligence, will improve our ability to determine the unique influence of OSA on CVD outcomes and ultimately allow us to better determine precision medicine approaches in OSA patients for CVD risk reduction. In this narrative review, we will highlight how team science via machine learning and artificial intelligence applied to existing clinical data, polysomnography, proteomics, and imaging can do just that.
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Affiliation(s)
- Oren Cohen
- Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; (O.C.); (V.K.)
| | - Vaishnavi Kundel
- Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; (O.C.); (V.K.)
| | - Philip Robson
- Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Zainab Al-Taie
- Center for Biostatistics, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; (Z.A.-T.); (M.S.-F.)
| | - Mayte Suárez-Fariñas
- Center for Biostatistics, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; (Z.A.-T.); (M.S.-F.)
| | - Neomi A. Shah
- Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; (O.C.); (V.K.)
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7
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Korkalainen H, Kainulainen S, Islind AS, Óskarsdóttir M, Strassberger C, Nikkonen S, Töyräs J, Kulkas A, Grote L, Hedner J, Sund R, Hrubos-Strom H, Saavedra JM, Ólafsdóttir KA, Ágústsson JS, Terrill PI, McNicholas WT, Arnardóttir ES, Leppänen T. Review and perspective on sleep-disordered breathing research and translation to clinics. Sleep Med Rev 2024; 73:101874. [PMID: 38091850 DOI: 10.1016/j.smrv.2023.101874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 09/18/2023] [Accepted: 11/09/2023] [Indexed: 01/23/2024]
Abstract
Sleep-disordered breathing, ranging from habitual snoring to severe obstructive sleep apnea, is a prevalent public health issue. Despite rising interest in sleep and awareness of sleep disorders, sleep research and diagnostic practices still rely on outdated metrics and laborious methods reducing the diagnostic capacity and preventing timely diagnosis and treatment. Consequently, a significant portion of individuals affected by sleep-disordered breathing remain undiagnosed or are misdiagnosed. Taking advantage of state-of-the-art scientific, technological, and computational advances could be an effective way to optimize the diagnostic and treatment pathways. We discuss state-of-the-art multidisciplinary research, review the shortcomings in the current practices of SDB diagnosis and management in adult populations, and provide possible future directions. We critically review the opportunities for modern data analysis methods and machine learning to combine multimodal information, provide a perspective on the pitfalls of big data analysis, and discuss approaches for developing analysis strategies that overcome current limitations. We argue that large-scale and multidisciplinary collaborative efforts based on clinical, scientific, and technical knowledge and rigorous clinical validation and implementation of the outcomes in practice are needed to move the research of sleep-disordered breathing forward, thus increasing the quality of diagnostics and treatment.
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Affiliation(s)
- Henri Korkalainen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland.
| | - Samu Kainulainen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Anna Sigridur Islind
- Department of Computer Science, Reykjavik University, Reykjavik, Iceland; Reykjavik University Sleep Institute, Reykjavik University, Reykjavik, Iceland
| | - María Óskarsdóttir
- Department of Computer Science, Reykjavik University, Reykjavik, Iceland
| | - Christian Strassberger
- Centre for Sleep and Wake Disorders, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden
| | - Sami Nikkonen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Juha Töyräs
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia; Science Service Center, Kuopio University Hospital, Kuopio, Finland
| | - Antti Kulkas
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Department of Clinical Neurophysiology, Seinäjoki Central Hospital, Seinäjoki, Finland
| | - Ludger Grote
- Centre for Sleep and Wake Disorders, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden; Sleep Disorders Centre, Pulmonary Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Jan Hedner
- Centre for Sleep and Wake Disorders, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden; Sleep Disorders Centre, Pulmonary Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Reijo Sund
- School of Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Harald Hrubos-Strom
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Ear, Nose and Throat Surgery, Akershus University Hospital, Lørenskog, Norway
| | - Jose M Saavedra
- Reykjavik University Sleep Institute, Reykjavik University, Reykjavik, Iceland; Physical Activity, Physical Education, Sport and Health (PAPESH) Research Group, Department of Sports Science, Reykjavik University, Reykjavik, Iceland
| | | | | | - Philip I Terrill
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia
| | - Walter T McNicholas
- School of Medicine, University College Dublin, and Department of Respiratory and Sleep Medicine, St Vincent's Hospital Group, Dublin Ireland
| | - Erna Sif Arnardóttir
- Reykjavik University Sleep Institute, Reykjavik University, Reykjavik, Iceland; Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland
| | - Timo Leppänen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland; School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia
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8
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Cheng WJ, Finnsson E, Ágústsson JS, Sands SA, Hang LW. Continuous positive airway pressure and adherence in patients with different endotypes of obstructive sleep apnea. J Sleep Res 2024; 33:e13999. [PMID: 37452710 PMCID: PMC10788376 DOI: 10.1111/jsr.13999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 05/26/2023] [Accepted: 06/27/2023] [Indexed: 07/18/2023]
Abstract
Determining the endotypes of obstructive sleep apnea (OSA) has potential implications for precision interventions. Here we assessed whether continuous positive airway pressure (CPAP) treatment outcomes differ across endotypic subgroups. We conducted a retrospective analysis of data obtained from 225 patients with moderate-to-severe OSA from a single sleep centre. Polysomnographic and CPAP titration study data were collected between May 2020 and January 2022. One-month CPAP treatment adherence was followed. Obstructive sleep apnea endotypes, namely arousal threshold, collapsibility, loop gain, and upper airway gain were estimated from polysomnography and dichotomised as high versus low. We examined associations between endotypic subgroups and (1) optimal CPAP titration pressure, (2) CPAP-related improvements in sleep architecture (proportions of slow-wave and rapid eye movement (REM) sleep), and (3) CPAP adherence. We observed that patients with high collapsibility required a higher CPAP pressure than those with low collapsibility (∆ = 0.4 cmH2 O, 95% confidence interval [CI] = 0.3-1.7). A larger increase in slow-wave sleep and in REM sleep proportions after CPAP treatment were observed in patients with a high arousal threshold, high collapsibility, high loop gain, or high upper airway gain than in those with low levels of endotypes. High loop gain and high collapsibility were independently associated with longer CPAP use hours per night (∆ = 0.6 h, 95% CI = 0.2-1.5 and ∆ = 0.3 h, 95% CI = 0.03-1.5, respectively). In conclusion, different endotypic subgroups of OSA exhibit a difference in outcomes of CPAP treatment. Knowledge of endotypes may help clinicians to understand which patients are expected to benefit most from CPAP therapy prior to its administration.
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Affiliation(s)
- Wan-Ju Cheng
- Department of Psychiatry, China Medical University Hospital, Taichung, Taiwan
- Department of Public Health, China Medical University, Taichung, Taiwan
- National Center for Geriatrics and Welfare Research, National Health Research Institutes, 35 Keyan Road, Miaoli, Taiwan
| | | | | | - Scott A. Sands
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Liang-Wen Hang
- School of Nursing & Graduate Institute of Nursing, China Medical University, Taichung, Taiwan
- Sleep Medicine Center, Department of Pulmonary and Critical Care Medicine, China Medical University Hospital, Taichung, Taiwan
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9
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Kiley JP, Brown MK, Freemer M, Lin S, Stefan M, Noel P. Research Accomplishments in Pulmonary, Critical Care, and Sleep: A Retrospective Review. Am J Respir Crit Care Med 2023; 208:1268-1270. [PMID: 37966304 PMCID: PMC10765391 DOI: 10.1164/rccm.202311-2047pp] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 11/15/2023] [Indexed: 11/16/2023] Open
Affiliation(s)
- James P Kiley
- Division of Lung Diseases, NHLBI, Bethesda, Maryland
| | | | | | - Sara Lin
- Division of Lung Diseases, NHLBI, Bethesda, Maryland
| | | | - Patricia Noel
- Division of Lung Diseases, NHLBI, Bethesda, Maryland
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10
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Edwards BA, O'Driscoll DM, Brooker EJ, Landry SA. A deep dive into the physiological differences responsible for obstructive sleep apnea between races. Sleep 2023; 46:zsad186. [PMID: 37429581 DOI: 10.1093/sleep/zsad186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Indexed: 07/12/2023] Open
Affiliation(s)
- Bradley A Edwards
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
- Department of Physiology, Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Denise M O'Driscoll
- Department of Respiratory and Sleep Medicine, Eastern Health, Melbourne, VIC, Australia
- Eastern Health Clinical School, Monash University, Melbourne, VIC, Australia
| | - Elliot J Brooker
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Shane A Landry
- Department of Physiology, Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
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11
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Ayas N, Pépin JL. Pharmacologic Therapy for Obstructive Sleep Apnea: Are We Seeing Some Light at the End of the Tunnel? Am J Respir Crit Care Med 2023; 208:1263-1264. [PMID: 37939168 PMCID: PMC10765387 DOI: 10.1164/rccm.202310-1778ed] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 11/08/2023] [Indexed: 11/10/2023] Open
Affiliation(s)
- Najib Ayas
- UBC, Medicine, Vancouver, British Columbia, Canada;
| | - Jean-Louis Pépin
- Centre Hospitalier Universitaire de Grenoble, 36724, Grenoble, France
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12
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Gasa M, Salord N, Fontanilles E, Pérez Ramos S, Prado E, Pallarés N, Santos Pérez S, Monasterio C. Polysomnographic Phenotypes of Obstructive Sleep Apnea in a Real-Life Cohort: A Pathophysiological Approach. Arch Bronconeumol 2023; 59:638-644. [PMID: 37516558 DOI: 10.1016/j.arbres.2023.07.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 07/10/2023] [Accepted: 07/11/2023] [Indexed: 07/31/2023]
Abstract
INTRODUCTION Obstructive sleep apnea (OSA) is heterogeneous and complex, but its severity is still based on the apnea-hypoapnea index (AHI). The present study explores using cluster analysis (CA), the additional information provided from routine polysomnography (PSG) to optimize OSA categorization. METHODS Cross-sectional study of OSA subjects diagnosed by PSG in a tertiary hospital sleep unit during 2016-2020. PSG, demographical, clinical variables, and comorbidities were recorded. Phenotypes were constructed from PSG variables using CA. Results are shown as median (interquartile range). RESULTS 981 subjects were studied: 41% females, age 56 years (45-66), overall AHI 23events/h (13-42) and body mass index (BMI) 30kg/m2 (27-34). Three PSG clusters were identified: Cluster 1: "Supine and obstructive apnea predominance" (433 patients, 44%). Cluster 2: "Central, REM and shorter-hypopnea predominance" (374 patients, 38%). Cluster 3: "Severe hypoxemic burden and higher wake after sleep onset" (174 patients, 18%). Based on classical OSA severity classification, subjects are distributed among the PSG clusters as severe OSA patients (AHI≥30events/h): 46% in cluster 1, 17% in cluster 2 and 36% in cluster 3; moderate OSA (15≤AHI<30events/h): 57% in cluster 1, 34% in cluster 2 and 9% in cluster 3; mild OSA (5≤AHI<15events/h): 28% in cluster 1, 68% in cluster 2 and 4% in cluster 3. CONCLUSIONS The CA identifies three specific PSG phenotypes that do not completely agree with classical OSA severity classification. This emphasized that using a simplistic AHI approach, the OSA severity is assessed by an incorrect or incomplete analysis of the heterogeneity of the disorder.
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Affiliation(s)
- Mercè Gasa
- Sleep Unit, Respiratory Department, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Section of Respiratory Medicine, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Department of Medicine, Campus Bellvitge, Universitat de Barcelona, L'Hospitalet de Llobregat, Spain.
| | - Neus Salord
- Sleep Unit, Respiratory Department, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Section of Respiratory Medicine, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain
| | - Eva Fontanilles
- Sleep Unit, Respiratory Department, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Section of Respiratory Medicine, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain
| | - Sandra Pérez Ramos
- Sleep Unit, Respiratory Department, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain
| | - Eliseo Prado
- Sleep Unit, Respiratory Department, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain
| | - Natalia Pallarés
- Biostatistics Unit, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain
| | - Salud Santos Pérez
- Sleep Unit, Respiratory Department, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Section of Respiratory Medicine, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Department of Medicine, Campus Bellvitge, Universitat de Barcelona, L'Hospitalet de Llobregat, Spain
| | - Carmen Monasterio
- Sleep Unit, Respiratory Department, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain; Section of Respiratory Medicine, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain.
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Cheng WJ, Finnsson E, Arnardóttir E, Ágústsson JS, Sands SA, Hang LW. Relationship between Symptom Profiles and Endotypes among Patients with Obstructive Sleep Apnea: A Latent Class Analysis. Ann Am Thorac Soc 2023; 20:1337-1344. [PMID: 37321164 PMCID: PMC10502883 DOI: 10.1513/annalsats.202212-1054oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 06/15/2023] [Indexed: 06/17/2023] Open
Abstract
Rationale: Obstructive sleep apnea (OSA) is a heterogeneous syndrome with various endotypic traits and symptoms. A link among symptoms, endotypes, and disease prognosis has been proposed but remains unsupported by empirical data. Objectives: To link symptom profiles and endotypes by clustering endotypic traits estimated using polysomnographic signals. Methods: We recruited 509 patients with moderate to severe OSA from a single sleep center. Polysomnographic data were collected between May 2020 and January 2022. Endotypic traits, namely arousal threshold, upper airway collapsibility, loop gain, and upper airway muscle compensation, were retrieved using polysomnographic signals during non-rapid eye movement periods. We used latent class analysis to group participants into endotype clusters. Demographic and polysomnographic parameter differences were compared between clusters, and associations between endotype clusters and symptom profiles were examined using logistic regression analyses. Results: Three endotype clusters were identified, characterized by high collapsibility/loop gain, low arousal threshold, and low compensation, respectively. Patients in each cluster exhibited similar demographic characteristics, but those in the high collapsibility/loop gain cluster had the highest proportion of obesity and severe oxygen desaturation observed in polysomnographic studies. The low compensation cluster was characterized by fewer sleepy symptoms and exhibited a lower rate of diabetes mellitus. Compared with the excessively sleepy group, disturbed sleep symptoms were associated with the low arousal threshold cluster (odds ratio, 1.89; 95% confidence interval, 1.16-3.10). Excessively sleepy symptoms were associated with the high collapsibility/loop gain cluster (odds ratio, 2.16; 95% confidence interval, 1.39-3.37) compared with the minimally symptomatic group. Conclusions: Three pathological endotype clusters were identified among patients with moderate to severe OSA, each exhibiting distinct polysomnographic characteristics and clinical symptom profiles.
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Affiliation(s)
- Wan-Ju Cheng
- Department of Psychiatry and
- Department of Public Health and
- National Center for Geriatrics and Welfare Research, National Health Research Institutes, Miaoli, Taiwan
| | | | | | | | - Scott A. Sands
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Liang-Wen Hang
- Sleep Medicine Center, Department of Pulmonary and Critical Care Medicine, China Medical University Hospital, Taichung, Taiwan
- School of Nursing & Graduate Institute of Nursing, China Medical University, Taichung, Taiwan
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14
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Horner RL. Targets for obstructive sleep apnea pharmacotherapy: principles, approaches, and emerging strategies. Expert Opin Ther Targets 2023; 27:609-626. [PMID: 37494064 DOI: 10.1080/14728222.2023.2240018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 07/19/2023] [Indexed: 07/27/2023]
Abstract
INTRODUCTION Obstructive sleep apnea (OSA) is a common and serious breathing disorder. Several pathophysiological factors predispose individuals to OSA. These factors are quantifiable, and modifiable pharmacologically. AREAS COVERED Four key pharmacotherapeutic targets are identified and mapped to the major determinants of OSA pathophysiology. PubMed and Clinicaltrials.gov were searched through April 2023. EXPERT OPINION Target #1: Pharyngeal Motor Effectors. Increasing pharyngeal muscle activity and responsivity with noradrenergic-antimuscarinic combination is central to recent breakthrough OSA pharmacotherapy. Assumptions, knowledge gaps, future directions, and other targets are identified. #2: Upper Airway Sensory Afferents. There is translational potential of sensitizing and amplifying reflex pharyngeal dilator muscle responses to negative airway pressure via intranasal delivery of new potassium channel blockers. Rationales, advantages, findings, and potential strategies to enhance effectiveness are identified. #3: Chemosensory Afferents and Ventilatory Control. Strategies to manipulate ventilatory control system sensitivity by carbonic anhydrase inhibitors are supported in theory and initial studies. Intranasal delivery of agents to stimulate central respiratory activity are also introduced. #4: Sleep-Wake Mechanisms. Arousability is the fourth therapeutic target rationalized. Evolving automated tools to measure key pathophysiological factors predisposing to OSA will accelerate pharmacotherapy. Although not currently ready for general clinical settings, the identified targets are of future promise.
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Affiliation(s)
- Richard L Horner
- Departments of Physiology and Medicine, University of Toronto, Toronto, ON, Canada
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15
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Turnbull CD, Stradling JR. Endotyping, phenotyping and personalised therapy in obstructive sleep apnoea: are we there yet? Thorax 2023; 78:726-732. [PMID: 37217289 DOI: 10.1136/thorax-2023-220037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 05/02/2023] [Indexed: 05/24/2023]
Abstract
Obstructive sleep apnoea (OSA) was traditionally thought to be mainly caused by obesity and upper airway crowding, and hence OSA management was not personalised according to particular characteristics, with most symptomatic patients receiving continuous positive airway pressure therapy. Recent advances in our understanding have identified additional potential and distinct causes of OSA (endotypes), and subgroups of patients (phenotypes) with increased risk of cardiovascular complications. In this review, we discuss the evidence to date as to whether there are distinct clinically useful endotypes and phenotypes of OSA, and the challenges to the field in moving towards delivering personalised therapy in OSA.
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Affiliation(s)
- Chris D Turnbull
- Oxford Centre for Respiratory Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Respiratory Medicine, NIHR Oxford Biomedical Research Centre, Oxford, UK
- NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - John R Stradling
- NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
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16
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Sands SA, Edwards BA. Pro: can physiological risk factors for obstructive sleep apnea be determined by analysis of data obtained from routine polysomnography? Sleep 2023; 46:zsac310. [PMID: 36715219 PMCID: PMC10171624 DOI: 10.1093/sleep/zsac310] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Indexed: 01/31/2023] Open
Affiliation(s)
- Scott A Sands
- Division of Sleep Medicine, Brigham and Women’s Hospital and Harvard Medical School, 221 Longwood Avenue, Boston, MA 02115, USA
| | - Bradley A Edwards
- Department of Physiology, School of Biomedical Sciences and Biomedical Discovery Institute, Monash University, Melbourne, VIC, Australia
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
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17
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Bandyopadhyay A, Goldstein C. Clinical applications of artificial intelligence in sleep medicine: a sleep clinician's perspective. Sleep Breath 2023; 27:39-55. [PMID: 35262853 PMCID: PMC8904207 DOI: 10.1007/s11325-022-02592-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 01/25/2022] [Accepted: 03/02/2022] [Indexed: 12/27/2022]
Abstract
BACKGROUND The past few years have seen a rapid emergence of artificial intelligence (AI)-enabled technology in the field of sleep medicine. AI refers to the capability of computer systems to perform tasks conventionally considered to require human intelligence, such as speech recognition, decision-making, and visual recognition of patterns and objects. The practice of sleep tracking and measuring physiological signals in sleep is widely practiced. Therefore, sleep monitoring in both the laboratory and ambulatory environments results in the accrual of massive amounts of data that uniquely positions the field of sleep medicine to gain from AI. METHOD The purpose of this article is to provide a concise overview of relevant terminology, definitions, and use cases of AI in sleep medicine. This was supplemented by a thorough review of relevant published literature. RESULTS Artificial intelligence has several applications in sleep medicine including sleep and respiratory event scoring in the sleep laboratory, diagnosing and managing sleep disorders, and population health. While still in its nascent stage, there are several challenges which preclude AI's generalizability and wide-reaching clinical applications. Overcoming these challenges will help integrate AI seamlessly within sleep medicine and augment clinical practice. CONCLUSION Artificial intelligence is a powerful tool in healthcare that may improve patient care, enhance diagnostic abilities, and augment the management of sleep disorders. However, there is a need to regulate and standardize existing machine learning algorithms prior to its inclusion in the sleep clinic.
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Affiliation(s)
- Anuja Bandyopadhyay
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Cathy Goldstein
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
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18
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Hirani R, Smiley A. A Scoping Review of Sleep Apnea: Where Do We Stand? Life (Basel) 2023; 13:life13020387. [PMID: 36836743 PMCID: PMC9961756 DOI: 10.3390/life13020387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 01/11/2023] [Accepted: 01/28/2023] [Indexed: 02/01/2023] Open
Abstract
Obstructive sleep apnea (OSA), a condition in which there is a recurrent collapse of the upper airway while sleeping, is a widespread disease affecting 5% to 10% people worldwide. Despite several advances in the treatment modalities for OSA, morbidity and mortality remain a concern. Common symptoms include loud snoring, gasping for air during sleep, morning headache, insomnia, hypersomnia, attention deficits, and irritability. Obese individuals, male gender, older age (65+), family history, smoking, and alcohol consumption are well recognized risk factors of OSA. This condition holds the ability to increase inflammatory cytokines, cause metabolic dysfunction, and increase the sympathetic output, all of which exacerbate OSA due to their effect on the cardiovascular system. In this review, we discuss its brief history, risk factors, complications, treatment modalities, and the role of clinicians in curbing its risk.
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Affiliation(s)
- Rahim Hirani
- School of Medicine, New York Medical College, Valhalla, NY 10595, USA
- Department of Surgery, Westchester Medical Center, New York, NY 10595, USA
| | - Abbas Smiley
- School of Medicine, New York Medical College, Valhalla, NY 10595, USA
- Department of Surgery, Westchester Medical Center, New York, NY 10595, USA
- Correspondence:
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19
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Liu Y, Abdul Ghafoor A, Hajipour M, Ayas N. Role of precision medicine in obstructive sleep apnoea. BMJ MEDICINE 2023; 2:e000218. [PMID: 36936264 PMCID: PMC9951383 DOI: 10.1136/bmjmed-2022-000218] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 12/14/2022] [Indexed: 01/07/2023]
Abstract
Obstructive sleep apnoea is a substantial clinical and public health problem because it contributes to harmful effects on quality of life, daytime symptoms, road traffic incidents, and cardiometabolic disease. Increasingly, obstructive sleep apnoea is recognised as a heterogeneous disease, and patients have varied susceptibility to long term complications and different responses to treatment. This narrative review summarises the current knowledge of precision medicine in obstructive sleep apnoea, particularly the role of symptom clusters, polysomnogram phenotypes, physiological endotypes, and circulating biomarkers in defining subtypes. In the near future, the prognostic accuracy of these measures in predicting long term complications in obstructive sleep apnoea will likely be improved, together with better matching of treatments to disease subtypes.
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Affiliation(s)
- Yu Liu
- Department of Pharmacology, Shanxi Medical University, Taiyuan, Shanxi, China
- Department of Medicine, University of British Columbia Faculty of Medicine, Vancouver, BC, Canada
| | - Ali Abdul Ghafoor
- Department of Medicine, University of British Columbia Faculty of Medicine, Vancouver, BC, Canada
| | - Mohammadreza Hajipour
- Division of Experimental Medicine, Department of Medicine, University of British Columbia Faculty of Medicine, Vancouver, BC, Canada
| | - Najib Ayas
- Department of Medicine, University of British Columbia Faculty of Medicine, Vancouver, BC, Canada
- Leon Judah Blackmore Sleep Disorders Program, UBC Hospital, Vancouver, BC, Canada
- Canadian Sleep and Circadian Network, Montréal, QC, Canada
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20
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Doufas AG, Tian L, Kutscher S, Finnsson E, Ágústsson JS, Chung BI, Panousis P. The effect of hyperoxia on ventilation during recovery from general anesthesia: A randomized pilot study for a parallel randomized controlled trial. J Clin Anesth 2022; 83:110982. [PMID: 36265267 DOI: 10.1016/j.jclinane.2022.110982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/29/2022] [Accepted: 10/05/2022] [Indexed: 11/06/2022]
Abstract
STUDY OBJECTIVE While supplemental O2 inhalation corrects hypoxemia, its effect on post-anesthesia ventilation remains unknown. This pilot trial tested the hypothesis that hyperoxia increases the time spent with a transcutaneous PCO2 (TcPCO2) > 45 mmHg, compared with standard O2 supplementation. DESIGN Single-blinded, parallel two-arm randomized pilot trial. SETTING University hospital. PATIENTS 20 patients undergoing robotic-assisted laparoscopic nephrectomy. MEASUREMENTS After institutional approval and informed consent, patients were randomized to receive O2 titrated to arterial saturation (SpO2): 90-94% (Conservative O2, N =10), or to SpO2 > 96% (Liberal O2, N = 10) for up to 90 min after anesthesia. Continuous TcPCO2, respiratory inductance plethysmography (RIP), and SpO2, were recorded. We calculated the percentage of time at TcPCO2 > 45 mmHg for each patient and compared the two groups using analysis of covariance, adjusting for sex, age, and body mass index. We also estimated the sample size required to detect the between-group difference observed in this pilot trial. RIP signals were used to calculate apnea/hypopnea index (AHI), which was then compared between two groups. MAIN RESULTS The mean percentage of time with a TcPCO2 > 45 mmHg was 80.6% for the Conservative O2 (N=9) and 61.2% for the Liberal O2 (N=10) group [between-group difference of 19.4% (95% CI: -18.7% to 57.6%), P = 0.140]. With an observed effect size of 0.73, we estimated that 30 participants per group are required, to demonstrate this difference with a power of 80% at a two-sided alpha of 5%. Means SpO2 were 94.5% and 99.9% for the Conservative O2 and the Liberal O2 groups, respectively. AHI was significantly higher in the Conservative O2, compared with the Liberal O2 group (median AHI: 16 vs. 3; P = 0.0014). CONCLUSIONS Hyperoxia in the post-anesthesia period reduced the time spent at TcPCO2 > 45 mmHg and significantly decreased AHI, while mean SpO2 ranged inside the a priori defined limits. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT04723433.
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Affiliation(s)
- Anthony G Doufas
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, United States of America; Center for Sleep and Circadian Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States of America.
| | - Lu Tian
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, United States of America
| | - Scott Kutscher
- Department of Psychiatry and Behavioral Sciences, and Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, CA, United States of America
| | | | | | - Benjamin I Chung
- Department of Urology, Stanford University School of Medicine, Stanford, CA, United States of America
| | - Periklis Panousis
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, United States of America
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Osman AM, Mukherjee S, Altree TJ, Delbeck M, Gehring D, Hahn M, Lang T, Xing C, Muller T, Weimann G, Eckert DJ. Topical Potassium Channel Blockage Improves Pharyngeal Collapsibility: A Translational, Placebo-Controlled Trial. Chest 2022; 163:953-965. [PMID: 36435266 DOI: 10.1016/j.chest.2022.11.024] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 10/06/2022] [Accepted: 11/02/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Potassium channel inhibition has been identified in animal models as a potential target to increase pharyngeal dilator muscle activity and to treat OSA. However, these findings have not yet been translated to humans. RESEARCH QUESTION Does a novel, potent, TWIK-related acid-sensitive K+ (TASK) 1/3 channel antagonist, BAY2586116, improve pharyngeal collapsibility in pigs and humans, and secondarily, what is the optimal dose and method of topical application? STUDY DESIGN AND METHODS In the preclinical study, pharyngeal muscle activity and upper-airway collapsibility via transient negative pressure application was quantified in 13 anesthetized pigs during administration of placebo, 0.3 μg, 3 μg, and 30 μg nasal drops of BAY2586116. In the clinical study, 12 people with OSA instrumented with polysomnography equipment, an epiglottic pressure catheter, pneumotachograph, and nasal mask to monitor sleep and breathing performed up to four detailed upper airway sleep physiology studies. Participants received BAY2586116 or placebo nasal spray (160 μg) before sleep via a double-masked, randomized, crossover design. Most participants also returned for three additional overnight visits: (1) nasal drops (160 μg), (2) half-dose nasal spray (80 μg), and (3) direct endoscopic application (160 μg). The upper-airway critical closing pressure during sleep was quantified at each visit. RESULTS Consistent and sustained improvements in pharyngeal collapsibility to negative pressure were found with 3 and 30 μg of BAY2586116 vs placebo in pigs. Similarly, BAY2586116 improved pharyngeal collapsibility by an average of approximately 2 cm H2O vs placebo, regardless of topical application method and dose (P < .008, mixed model) in participants with OSA. INTERPRETATION Acute topical application of BAY2586116 improves upper-airway collapsibility in anesthetized pigs and sleeping humans with OSA. These novel physiologic findings highlight the therapeutic potential to target POTASSIUM channel mechanisms to treat OSA. TRIAL REGISTRY ClinicalTrials.gov; No.: NCT04236440; URL: www. CLINICALTRIALS gov.
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Affiliation(s)
- Amal M Osman
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide.
| | - Sutapa Mukherjee
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide; Respiratory and Sleep Service, Southern Adelaide Local Health Network, SA Health, SA, Australia
| | - Thomas J Altree
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide; Respiratory and Sleep Service, Southern Adelaide Local Health Network, SA Health, SA, Australia
| | - Martina Delbeck
- Research & Development, Pharmaceuticals, Bayer AG, Wuppertal
| | | | - Michael Hahn
- Research & Development, Pharmaceuticals, Bayer AG, Wuppertal
| | - Tina Lang
- Research & Development, Pharmaceuticals, Bayer AG, Wuppertal
| | - Charles Xing
- Research & Development, Pharmaceuticals, Bayer AG, Wuppertal
| | - Thomas Muller
- Research & Development, Pharmaceuticals, Bayer AG, Wuppertal
| | - Gerrit Weimann
- Research & Development, Pharmaceuticals, Bayer AG, Wuppertal
| | - Danny J Eckert
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide
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22
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Schmickl CN, Orr JE, Kim P, Nokes B, Sands S, Manoharan S, McGinnis L, Parra G, DeYoung P, Owens RL, Malhotra A. Point-of-care prediction model of loop gain in patients with obstructive sleep apnea: development and validation. BMC Pulm Med 2022; 22:158. [PMID: 35468829 PMCID: PMC9036750 DOI: 10.1186/s12890-022-01950-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 04/13/2022] [Indexed: 11/10/2022] Open
Abstract
Background High loop gain (unstable ventilatory control) is an important—but difficult to measure—contributor to obstructive sleep apnea (OSA) pathogenesis, predicting OSA sequelae and/or treatment response. Our objective was to develop and validate a clinical prediction tool of loop gain. Methods A retrospective cohort of consecutive adults with OSA (apnea–hypopnea index, AHI > 5/hour) based on in-laboratory polysomnography 01/2017–12/2018 was randomly split into a training and test-set (3:1-ratio). Using a customized algorithm (“reference standard”) loop gain was quantified from raw polysomnography signals on a continuous scale and additionally dichotomized (high > 0.7). Candidate predictors included general patient characteristics and routine polysomnography data. The model was developed (training-set) using linear regression with backward selection (tenfold cross-validated mean square errors); the predicted loop gain of the final linear regression model was used to predict loop gain class. More complex, alternative models including lasso regression or random forests were considered but did not meet pre-specified superiority-criteria. Final model performance was validated on the test-set. Results The total cohort included 1055 patients (33% high loop gain). Based on the final model, higher AHI (beta = 0.0016; P < .001) and lower hypopnea-percentage (beta = −0.0019; P < .001) predicted higher loop gain values. The predicted loop gain showed moderate-to-high correlation with the reference loop gain (r = 0.48; 95% CI 0.38–0.57) and moderate discrimination of patients with high versus low loop gain (area under the curve = 0.73; 95% CI 0.67–0.80). Conclusion To our knowledge this is the first prediction model of loop gain based on readily-available clinical data, which may facilitate retrospective analyses of existing datasets, better patient selection for clinical trials and eventually clinical practice.
Supplementary Information The online version contains supplementary material available at 10.1186/s12890-022-01950-y.
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Affiliation(s)
- Christopher N Schmickl
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego (UCSD), San Diego, CA, 92037, USA.
| | - Jeremy E Orr
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego (UCSD), San Diego, CA, 92037, USA
| | - Paul Kim
- Division of Cardiology, University of California, San Diego (UCSD), San Diego, CA, 92037, USA
| | - Brandon Nokes
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego (UCSD), San Diego, CA, 92037, USA
| | - Scott Sands
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sreeganesh Manoharan
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego (UCSD), San Diego, CA, 92037, USA
| | - Lana McGinnis
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego (UCSD), San Diego, CA, 92037, USA
| | - Gabriela Parra
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego (UCSD), San Diego, CA, 92037, USA
| | - Pamela DeYoung
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego (UCSD), San Diego, CA, 92037, USA
| | - Robert L Owens
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego (UCSD), San Diego, CA, 92037, USA
| | - Atul Malhotra
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego (UCSD), San Diego, CA, 92037, USA
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23
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Abstract
STUDY OBJECTIVES To assess early adherence to therapy with hypoglossal nerve stimulation therapy. METHODS This is a prospective study of consecutive patients with moderate to severe obstructive sleep apnea who underwent implantation of hypoglossal nerve stimulation therapy within a single academic practice and attended a follow-up appointment after greater than 30 days of therapy use. Objective adherence data were extracted from an objective monitoring database and compared to patient characteristics. RESULTS The study population was 79 participants who were 29.1% female with a mean age of 58.7 ± 12.8 years old, body mass index of 28.9 ± 3.4 kg/m2, and baseline apnea-hypopnea index of 33.8 ± 17.6 events/h. In the first 7 days after device activation, average use was 7.8 h/night, with 91.9% of nights with greater than 4 hours of therapy use and an average of 0.2 pauses in therapy per night. These figures remained stable after 30 days of use: 7.7 h/night, 91.0% of nights longer than 4 hours, and 0.3 pauses per night. Objective evidence of difficulty with acclimatization was associated with age less than 60 years (odds ratio 2.8, 95% confidence interval 1.1-7.1, P = .03) and a history of prior upper airway surgery (3.9, 1.2-11.9, P = .015). Insomnia was present in 31 patients and was not associated with objective evidence of difficulty tolerating therapy. CONCLUSIONS Early adherence to hypoglossal nerve stimulation is excellent (92.4% >4 hours on >70% of nights), suggesting that the acclimatization period is straightforward in most. Younger age and a history of prior upper airway surgery appear to be associated with an increased risk of difficulty with acclimatization. CITATION Huyett P. Early objective adherence to hypoglossal nerve stimulation therapy. J Clin Sleep Med. 2022;18(2):631-636.
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Affiliation(s)
- Phillip Huyett
- Address correspondence to: Phillip Huyett, Division of Sleep Medicine and Surgery, Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, MA; Tel: (617) 573-3793;
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24
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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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25
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Lim R, Messineo L, Grunstein RR, Carberry JC, Eckert DJ. The noradrenergic agent reboxetine plus the antimuscarinic hyoscine butylbromide reduces sleep apnoea severity: a double-blind, placebo-controlled, randomised crossover trial. J Physiol 2021; 599:4183-4195. [PMID: 34174090 DOI: 10.1113/jp281912] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Accepted: 06/23/2021] [Indexed: 11/08/2022] Open
Abstract
KEY POINTS Recent animal and human physiology studies indicate that noradrenergic and muscarinic processes are key mechanisms that mediate pharyngeal muscle control during sleep. The noradrenergic agent reboxetine combined with the anti-muscarinic hyoscine butylbromide has recently been shown to improve upper airway function during sleep in healthy individuals. However, whether these findings translate to the clinically relevant patient population of people with obstructive sleep apnoea (OSA), and the effects of the agents on OSA severity, are unknown. We found that reboxetine plus hyoscine butylbromide reduced OSA severity, including overnight hypoxaemia, via increases in pharyngeal muscle responsiveness, improvements in respiratory control and airway collapsibility without changing the respiratory arousal threshold. These findings provide mechanistic insight into the role of noradrenergic and anti-muscarinic agents on upper airway stability and breathing during sleep and are important for pharmacotherapy development for OSA. ABSTRACT The noradrenergic agent reboxetine combined with the anti-muscarinic hyoscine butylbromide has recently been shown to improve upper airway function during sleep in healthy individuals. However, the effects of this drug combination on obstructive sleep apnoea (OSA) severity are unknown. Accordingly, this study aimed to determine if reboxetine plus hyoscine butylbromide reduces OSA severity. Secondary aims were to investigate the effects on key upper airway physiology and endotypic traits. Twelve people with OSA aged 52 ± 13 years, BMI = 30 ± 5 kg/m2 , completed a double-blind, randomised, placebo-controlled, crossover trial (ACTRN12617001326381). Two in-laboratory sleep studies with nasal mask, pneumotachograph, epiglottic pressure sensor and bipolar fine-wire electrodes into genioglossus and tensor palatini muscles were performed separated by approximately 1 week. Each participant received either reboxetine (4 mg) plus hyoscine butylbromide (20 mg), or placebo immediately prior to sleep. Polysomnography, upper airway physiology and endotypic estimates of OSA were compared between conditions. Reboxetine plus hyoscine butylbromide reduced the apnoea/hypopnoea index by (mean ± SD) 17 ± 17 events/h from 51 ± 30 to 33 ± 22 events/h (P = 0.005) and nadir oxygen saturation increased by 6 ± 5% from 82 ± 5 to 88 ± 2% (P = 0.002). The drug combination increased tonic genioglossus muscle responsiveness during non-REM sleep (median [25th, 75th centiles]: -0.007 [-0.0004, -0.07] vs. -0.12 [-0.02, -0.40] %maxEMG/cmH2 O, P = 0.02), lowered loop gain (0.43 ± 0.06 vs. 0.39 ± 0.07, P = 0.01), and improved airway collapsibility (90 [69, 95] vs. 93 [88, 96] %eupnoea, P = 0.02), without changing the arousal threshold (P = 0.39). These findings highlight the important role that noradrenergic and muscarinic processes have on upper airway function during sleep and the potential for pharmacotherapy to target these mechanisms to treat OSA.
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Affiliation(s)
- Richard Lim
- Neuroscience Research Australia (NeuRA), New South Wales, Sydney, Australia.,School of Medical Sciences, University of New South Wales, New South Wales, Sydney, Australia
| | - Ludovico Messineo
- Flinders Health and Medical Research Institute and Adelaide Institute for Sleep Health, Flinders University, Bedford Park, South Australia, Australia
| | - Ronald R Grunstein
- Woolcock Institute of Medical Research, Sydney Medical School, the University of Sydney, New South Wales, Glebe, Australia.,Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, New South Wales, Camperdown, Australia
| | - Jayne C Carberry
- Neuroscience Research Australia (NeuRA), New South Wales, Sydney, Australia.,Flinders Health and Medical Research Institute and Adelaide Institute for Sleep Health, Flinders University, Bedford Park, South Australia, Australia.,UCD School of Medicine, University College Dublin, Belfield, Dublin, Ireland
| | - Danny J Eckert
- Neuroscience Research Australia (NeuRA), New South Wales, Sydney, Australia.,School of Medical Sciences, University of New South Wales, New South Wales, Sydney, Australia.,Flinders Health and Medical Research Institute and Adelaide Institute for Sleep Health, Flinders University, Bedford Park, South Australia, Australia
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26
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Redline S, Purcell SM. Sleep and Big Data: harnessing data, technology, and analytics for monitoring sleep and improving diagnostics, prediction, and interventions-an era for Sleep-Omics? Sleep 2021; 44:6248627. [PMID: 33893509 DOI: 10.1093/sleep/zsab107] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Affiliation(s)
- Susan Redline
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Shaun M Purcell
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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