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Mann DL, Staykov E, Georgeson T, Azarbarzin A, Kainulainen S, Redline S, Sands SA, Terrill PI. Flow Limitation Is Associated with Excessive Daytime Sleepiness in Individuals without Moderate or Severe Obstructive Sleep Apnea. Ann Am Thorac Soc 2024; 21:1186-1193. [PMID: 38530665 PMCID: PMC11298983 DOI: 10.1513/annalsats.202308-710oc] [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: 08/17/2023] [Accepted: 03/20/2024] [Indexed: 03/28/2024] Open
Abstract
Rationale: Moderate-severe obstructive sleep apnea (OSA) (apnea-hypopnea index [AHI], >15 events/h) disturbs sleep through frequent bouts of apnea and is associated with daytime sleepiness. However, many individuals without moderate-severe OSA (i.e., AHI <15 events/h) also report sleepiness. Objectives: To test the hypothesis that sleepiness in the AHI <15 events/h group is a consequence of substantial flow limitation in the absence of overt reductions in airflow (i.e., apnea/hypopnea). Methods: A total of 1,886 participants from the MESA sleep cohort were analyzed for frequency of flow limitation from polysomnogram-recorded nasal airflow signal. Excessive daytime sleepiness (EDS) was defined by an Epworth Sleepiness Scale score ⩾11. Covariate-adjusted logistic regression assessed the association between EDS (binary dependent variable) and frequency of flow limitation (continuous) in individuals with an AHI <15 events/h. Results: A total of 772 individuals with an AHI <15 events/h were included in the primary analysis. Flow limitation was associated with EDS (odds ratio, 2.04; 95% confidence interval, 1.17-3.54; per 2-standard deviation increase in flow limitation frequency) after adjusting for age, sex, body mass index, race/ethnicity, and sleep duration. This effect size did not appreciably change after also adjusting for AHI. Conclusions: In individuals with an AHI <15 events/h, increasing flow limitation frequency by 2 standard deviations is associated with a twofold increase in the risk of EDS. Future studies should investigate addressing flow limitation in low-AHI individuals as a potential mechanism for ameliorating sleepiness.
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Affiliation(s)
- Dwayne L. Mann
- School of Electrical Engineering and Computer Science
- Institute for Social Science Research, and
| | - Eric Staykov
- School of Electrical Engineering and Computer Science
| | - Thomas Georgeson
- Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Ali Azarbarzin
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham & Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Samu Kainulainen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; and
- Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham & Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Scott A. Sands
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham & Women’s Hospital, Harvard Medical School, Boston, Massachusetts
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Borsini E, Blanco M, Nigro CA. Formulas to predict continuous positive airway pressure level using a home auto-adjusting device for obstructive sleep apnea treatment. Sleep Breath 2024:10.1007/s11325-024-03104-2. [PMID: 39073667 DOI: 10.1007/s11325-024-03104-2] [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: 11/22/2023] [Revised: 06/12/2024] [Accepted: 07/01/2024] [Indexed: 07/30/2024]
Abstract
PURPOSE To develop equations to predict therapeutic continuous positive airway pressure (CPAPT) based on home-based CPAP titration, including the type of interface used. METHOD Retrospective study conducted in adult patients with obstructive sleep apnea (OSA) who used home-based autoCPAP titration (AutoSet S10, ResMed®). CPAPT was obtained manually through a visual analysis of autoCPAP data (CPAPV) and automatically using the 95th percentile pressure (CPAPP95). Multiple linear regression and K-fold cross-validation were applied. Independent variables were AHI, neck circumference (NC), BMI, and mask. Two formulas were generated based on mask and the Miljeteig and Hoffstein formula. RESULTS We included 702 patients (174 women), median age, BMI and AHI of 58 years, 32 kg/m2 and 32 ev/h, respectively. Predictors for CPAPv (M1) were BMI, NC, AHI and type of interface (R2: 0.19); and for CPAPP95 (M2), BMI, AHI and mask (R2: 0.09). Error and precision between the formulas and CPAPT were: 0 (CPAPV/CPAPP95), and - 3.2 to 3.2 (CPAPV) and - 4 to 4 cm H2O (CPAPP95). CPAPV was higher with oronasal mask (10 vs. 9 cm H2O, p < 0.01). Accuracy defined as; a difference ± 2 cm H2O between estimated CPAP and CPAPT was greater in M1 than in M2 (79% vs. 64%, p < 0.01). CONCLUSION In both models, calculated error was close to zero. CPAPV (± 3.2 cm H2O) showed more precision than CPAPP95 (± 4 cm H2O). With M1 (CPAPV), 79% of patients could start CPAP with reasonable accuracy (error of ± 2 cm H2O).
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Affiliation(s)
- Eduardo Borsini
- Sleep and Ventilation Unit, Hospital Británico, Buenos Aires, Argentina.
| | - Magalí Blanco
- Sleep and Ventilation Unit, Hospital Británico, Buenos Aires, Argentina
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Pamidi S, Ayappa I. Automating detection of inspiratory flow limitation: the next frontier in assessing sleep disordered breathing in pregnancy and risk for adverse pregnancy outcomes? Eur Respir J 2024; 64:2400768. [PMID: 39025517 DOI: 10.1183/13993003.00768-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 06/03/2024] [Indexed: 07/20/2024]
Affiliation(s)
- Sushmita Pamidi
- The Respiratory Epidemiology and Clinical Research Unit, Research Institute of the McGill University Health Centre, McGill University, Montreal, QC, Canada
| | - Indu Ayappa
- Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Staykov E, Mann DL, Leppänen T, Töyräs J, Kainulainen S, Azarbarzin A, Duce B, Sands SA, Terrill PI. Increased flow limitation during sleep is associated with decreased psychomotor vigilance task performance in individuals with suspected obstructive sleep apnea: a multi-cohort study. Sleep 2024; 47:zsae077. [PMID: 38513056 PMCID: PMC11168759 DOI: 10.1093/sleep/zsae077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Indexed: 03/23/2024] Open
Affiliation(s)
- Eric Staykov
- School of Electrical Engineering and Computer Science, University of Queensland, Brisbane, QLD, Australia
| | - Dwayne L Mann
- School of Electrical Engineering and Computer Science, University of Queensland, Brisbane, QLD, Australia
| | - Timo Leppänen
- School of Electrical Engineering and Computer Science, University of Queensland, Brisbane, QLD, Australia
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Juha Töyräs
- School of Electrical Engineering and Computer Science, University of Queensland, Brisbane, QLD, Australia
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- Science Service 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
| | - Ali Azarbarzin
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham & Women’s Hospital & Harvard Medical School, Boston, MA, USA
| | - Brett Duce
- Department of Respiratory and Sleep Medicine, Princess Alexandra Hospital, Brisbane, QLD, Australia
- Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Scott A Sands
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham & Women’s Hospital & Harvard Medical School, Boston, MA, USA
| | - Philip I Terrill
- School of Electrical Engineering and Computer Science, University of Queensland, Brisbane, QLD, Australia
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5
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Staykov E, Mann DL, Duce B, Kainulainen S, Leppänen T, Töyräs J, Azarbarzin A, Georgeson T, Sands SA, Terrill PI. Increased Flow Limitation During Sleep Is Associated With Increased Psychomotor Vigilance Task Lapses in Individuals With Suspected OSA. Chest 2024; 165:990-1003. [PMID: 38048938 DOI: 10.1016/j.chest.2023.11.031] [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: 04/18/2023] [Revised: 09/03/2023] [Accepted: 11/16/2023] [Indexed: 12/06/2023] Open
Abstract
BACKGROUND Impaired daytime vigilance is an important consequence of OSA, but several studies have reported no association between objective measurements of vigilance and the apnea-hypopnea index (AHI). Notably, the AHI does not quantify the degree of flow limitation, that is, the extent to which ventilation fails to meet intended ventilation (ventilatory drive). RESEARCH QUESTION Is flow limitation during sleep associated with daytime vigilance in OSA? STUDY DESIGN AND METHODS Nine hundred ninety-eight participants with suspected OSA completed a 10-min psychomotor vigilance task (PVT) before same-night in-laboratory polysomnography. Flow limitation frequency (percent of flow-limited breaths) during sleep was quantified using airflow shapes (eg, fluttering and scooping) from nasal pressure airflow. Multivariable regression assessed the association between flow limitation frequency and the number of lapses (response times > 500 ms, primary outcome), adjusting for age, sex, BMI, total sleep time, depression, and smoking status. RESULTS Increased flow limitation frequency was associated with decreased vigilance: a 1-SD (35.3%) increase was associated with 2.1 additional PVT lapses (95% CI, 0.7-3.7; P = .003). This magnitude was similar to that for age, where a 1-SD increase (13.5 years) was associated with 1.9 additional lapses. Results were similar after adjusting for AHI, hypoxemia severity, and arousal severity. The AHI was not associated with PVT lapses (P = .20). In secondary exploratory analysis, flow limitation frequency was associated with mean response speed (P = .012), median response time (P = .029), fastest 10% response time (P = .041), slowest 10% response time (P = .018), and slowest 10% response speed (P = .005). INTERPRETATION Increased flow limitation during sleep was associated with decreased daytime vigilance in individuals with suspected OSA, independent of the AHI. Flow limitation may complement standard clinical metrics in identifying individuals whose vigilance impairment most likely is explained by OSA.
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Affiliation(s)
- Eric Staykov
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, QLD, Australia.
| | - Dwayne L Mann
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, QLD, Australia; Institute for Social Science Research, The University of Queensland, Brisbane, QLD, Australia
| | - Brett Duce
- Department of Respiratory & Sleep Medicine, Princess Alexandra Hospital, Brisbane, QLD, Australia; Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Samu Kainulainen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Timo Leppänen
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, QLD, Australia; Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Juha Töyräs
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, QLD, Australia; Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Science Service Center, Kuopio University Hospital, Kuopio, Finland
| | - Ali Azarbarzin
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA
| | - Thomas Georgeson
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, QLD, Australia; Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Scott A Sands
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA
| | - Philip I Terrill
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, QLD, Australia
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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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7
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Gu Y, Gagnon JF, Kaminska M. Sleep electroencephalography biomarkers of cognition in obstructive sleep apnea. J Sleep Res 2023; 32:e13831. [PMID: 36941194 DOI: 10.1111/jsr.13831] [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: 09/26/2022] [Revised: 12/20/2022] [Accepted: 01/04/2023] [Indexed: 03/23/2023]
Abstract
Obstructive sleep apnea has been associated with cognitive impairment and may be linked to disorders of cognitive function. These associations may be a result of intermittent hypoxaemia, sleep fragmentation and changes in sleep microstructure in obstructive sleep apnea. Current clinical metrics of obstructive sleep apnea, such as the apnea-hypopnea index, are poor predictors of cognitive outcomes in obstructive sleep apnea. Sleep microstructure features, which can be identified on sleep electroencephalography of traditional overnight polysomnography, are increasingly being characterized in obstructive sleep apnea and may better predict cognitive outcomes. Here, we summarize the literature on several major sleep electroencephalography features (slow-wave activity, sleep spindles, K-complexes, cyclic alternating patterns, rapid eye movement sleep quantitative electroencephalography, odds ratio product) identified in obstructive sleep apnea. We will review the associations between these sleep electroencephalography features and cognition in obstructive sleep apnea, and examine how treatment of obstructive sleep apnea affects these associations. Lastly, evolving technologies in sleep electroencephalography analyses will also be discussed (e.g. high-density electroencephalography, machine learning) as potential predictors of cognitive function in obstructive sleep apnea.
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Affiliation(s)
- Yusing Gu
- Department of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Jean-François Gagnon
- Department of Psychology, Université du Québec à Montréal, Montréal, Québec, Canada
- Center for Advanced Research in Sleep Medicine, CIUSSS-NÎM - Hôpital du Sacré-Coeur de Montréal, Montreal, Quebec, Canada
| | - Marta Kaminska
- Respiratory Epidemiology and Clinical Research Unit, Research Institute of the McGill University Health Centre, Montreal, Québec, Canada
- Respiratory Division & Sleep Laboratory, McGill University Health Centre, Montreal, Québec, Canada
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8
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Mutti C, Pollara I, Abramo A, Soglia M, Rapina C, Mastrillo C, Alessandrini F, Rosenzweig I, Rausa F, Pizzarotti S, Salvatelli ML, Balella G, Parrino L. The Contribution of Sleep Texture in the Characterization of Sleep Apnea. Diagnostics (Basel) 2023; 13:2217. [PMID: 37443611 PMCID: PMC10340273 DOI: 10.3390/diagnostics13132217] [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: 05/29/2023] [Revised: 06/20/2023] [Accepted: 06/27/2023] [Indexed: 07/15/2023] Open
Abstract
Obstructive sleep apnea (OSA) is multi-faceted world-wide-distributed disorder exerting deep effects on the sleeping brain. In the latest years, strong efforts have been dedicated to finding novel measures assessing the real impact and severity of the pathology, traditionally trivialized by the simplistic apnea/hypopnea index. Due to the unavoidable connection between OSA and sleep, we reviewed the key aspects linking the breathing disorder with sleep pathophysiology, focusing on the role of cyclic alternating pattern (CAP). Sleep structure, reflecting the degree of apnea-induced sleep instability, may provide topical information to stratify OSA severity and foresee some of its dangerous consequences such as excessive daytime sleepiness and cognitive deterioration. Machine learning approaches may reinforce our understanding of this complex multi-level pathology, supporting patients' phenotypization and easing in a more tailored approach for sleep apnea.
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Affiliation(s)
- Carlotta Mutti
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
| | - Irene Pollara
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
| | - Anna Abramo
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
| | - Margherita Soglia
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
| | - Clara Rapina
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
| | - Carmela Mastrillo
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
| | - Francesca Alessandrini
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
| | - Ivana Rosenzweig
- Sleep Disorders Centre, Guy’s and St Thomas’ NHS Foundation Trust, London SE1 7EH, UK;
| | - Francesco Rausa
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
| | - Silvia Pizzarotti
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
| | - Marcello luigi Salvatelli
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
- Neurology Unit, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy
| | - Giulia Balella
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
- Sleep Disorders Centre, Guy’s and St Thomas’ NHS Foundation Trust, London SE1 7EH, UK;
| | - Liborio Parrino
- Sleep Disorders Center, Department of Medicine and Surgery, University Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy; (C.M.); (I.P.); (A.A.); (M.S.); (C.R.); (C.M.); (F.A.); (F.R.); (S.P.); (M.l.S.); (G.B.)
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9
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Drakatos P, O'Regan D, Liao Y, Panayiotou C, Higgins S, Kabiljo R, Benson J, Pool N, Tahmasian M, Romigi A, Nesbitt A, Stokes PRA, Kumari V, Young AH, Rosenzweig I. Profile of sleep disturbances in patients with recurrent depressive disorder or bipolar affective disorder in a tertiary sleep disorders service. Sci Rep 2023; 13:8785. [PMID: 37258713 PMCID: PMC10232417 DOI: 10.1038/s41598-023-36083-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 05/29/2023] [Indexed: 06/02/2023] Open
Abstract
Bidirectional relationship between sleep disturbances and affective disorders is increasingly recognised, but its underlying mechanisms are far from clear, and there is a scarcity of studies that report on sleep disturbances in recurrent depressive disorder (RDD) and bipolar affective disorder (BPAD). To address this, we conducted a retrospective study of polysomnographic and clinical records of patients presenting to a tertiary sleep disorders clinic with affective disorders. Sixty-three BPAD patients (32 female; mean age ± S.D.: 41.8 ± 12.4 years) and 126 age- and gender-matched RDD patients (62 female; 41.5 ± 12.8) were studied. Whilst no significant differences were observed in sleep macrostructure parameters between BPAD and RDD patients, major differences were observed in comorbid sleep and physical disorders, both of which were higher in BPAD patients. Two most prevalent sleep disorders, namely obstructive sleep apnoea (OSA) (BPAD 50.8.0% vs RDD 29.3%, P = 0.006) and insomnia (BPAD 34.9% vs RDD 15.0%, P = 0.005) were found to be strongly linked with BPAD. In summary, in our tertiary sleep clinic cohort, no overt differences in the sleep macrostructure between BPAD and RDD patients were demonstrated. However, OSA and insomnia, two most prevalent sleep disorders, were found significantly more prevalent in patients with BPAD, by comparison to RDD patients. Also, BPAD patients presented with significantly more severe OSA, and with higher overall physical co-morbidity. Thus, our findings suggest an unmet/hidden need for earlier diagnosis of those with BPAD.
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Affiliation(s)
- Panagis Drakatos
- Sleep Disorders Centre, Guy's and St Thomas' NHS Foundation Trust, London, UK
- Faculty of Life Sciences and Medicine, King's College London, London, UK
- Department of Neuroimaging, Sleep and Brain Plasticity Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, De Crespigny Park, Box 089, London, SE5 8AF, UK
| | - David O'Regan
- Sleep Disorders Centre, Guy's and St Thomas' NHS Foundation Trust, London, UK
- Faculty of Life Sciences and Medicine, King's College London, London, UK
- Department of Neuroimaging, Sleep and Brain Plasticity Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, De Crespigny Park, Box 089, London, SE5 8AF, UK
| | - Yingqi Liao
- Department of Neuroimaging, Sleep and Brain Plasticity Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, De Crespigny Park, Box 089, London, SE5 8AF, UK
| | - Constantinos Panayiotou
- Department of Neuroimaging, Sleep and Brain Plasticity Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, De Crespigny Park, Box 089, London, SE5 8AF, UK
| | - Sean Higgins
- Sleep Disorders Centre, Guy's and St Thomas' NHS Foundation Trust, London, UK
- Department of Neuroimaging, Sleep and Brain Plasticity Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, De Crespigny Park, Box 089, London, SE5 8AF, UK
| | - Renata Kabiljo
- Department of Neuroimaging, Sleep and Brain Plasticity Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, De Crespigny Park, Box 089, London, SE5 8AF, UK
- Department of Biostatistics and Health Informatics, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Denmark Hill, London, SE5 8AF, UK
| | - Joshua Benson
- Sleep Disorders Centre, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Norman Pool
- Department of Neuropsychiatry, St George's Hospital, South West London and St George's Mental Health NHS Trust, London, UK
| | - Masoud Tahmasian
- Institute of Neuroscience and Medicine Research, Brain and Behaviour (INM-7), Jülich Research Center, Jülich, Germany & Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Andrea Romigi
- IRCCS Neuromed Istituto Neurologico Mediterraneo Pozzilli (IS), Pozzilli, Italy
| | - Alexander Nesbitt
- Sleep Disorders Centre, Guy's and St Thomas' NHS Foundation Trust, London, UK
- Department of Neuroimaging, Sleep and Brain Plasticity Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, De Crespigny Park, Box 089, London, SE5 8AF, UK
- Department of Neurology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Paul R A Stokes
- Department of Psychological Medicine, Centre for Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Veena Kumari
- Division of Psychology, Department of Life Sciences, & Centre for Cognitive Neuroscience, College of Health, Medicine and Life Sciences, Brunel University London, London, UK
| | - Allan H Young
- Department of Psychological Medicine, King's College London & South London and Maudsley NHS Foundation Trust, Institute of Psychiatry, Psychology and Neuroscience, Bethlem Royal Hospital, Beckenham, UK
| | - Ivana Rosenzweig
- Sleep Disorders Centre, Guy's and St Thomas' NHS Foundation Trust, London, UK.
- Department of Neuroimaging, Sleep and Brain Plasticity Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, De Crespigny Park, Box 089, London, SE5 8AF, UK.
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10
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Bonsignore MR, Lombardi C, Lombardo S, Fanfulla F. Epidemiology, Physiology and Clinical Approach to Sleepiness at the Wheel in OSA Patients: A Narrative Review. J Clin Med 2022; 11:jcm11133691. [PMID: 35806976 PMCID: PMC9267880 DOI: 10.3390/jcm11133691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 06/22/2022] [Accepted: 06/24/2022] [Indexed: 11/16/2022] Open
Abstract
Sleepiness at the wheel (SW) is recognized as an important factor contributing to road traffic accidents, since up to 30 percent of fatal accidents have been attributed to SW. Sleepiness-related motor vehicle accidents may occur both from falling asleep while driving and from behavior impairment attributable to sleepiness. SW can be caused by various sleep disorders but also by behavioral factors such as sleep deprivation, shift work and non-restorative sleep, as well as chronic disease or the treatment with drugs that negatively affect the level of vigilance. An association between obstructive sleep apnea (OSA) and motor vehicle accidents has been found, with an increasing risk in OSA patients up to sevenfold in comparison to the general population. Regular treatment with continuous positive airway pressure (CPAP) relieves excessive daytime sleepiness and reduces the crash risk. Open questions still remain about the physiological and clinical determinants of SW in OSA patients: the severity of OSA in terms of the frequency of respiratory events (apnea hypopnea index, AHI) or hypoxic load, the severity of daytime sleepiness, concomitant chronic sleep deprivation, comorbidities, the presence of depressive symptoms or chronic fatigue. Herein, we provide a review addressing the epidemiological, physiological and clinical aspects of SW, with a particular focus on the methods to recognize those patients at risk of SW.
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Affiliation(s)
- Maria R. Bonsignore
- PROMISE Department, University of Palermo, 90127 Palermo, Italy
- Sleep Clinic, Division of Respiratory Medicine, Ospedali Riuniti Villa Sofia-Cervello, 90146 Palermo, Italy;
- Institute for Biomedical Research and Innovation (IRIB), National Research Council (CNR), 90146 Palermo, Italy
- Correspondence:
| | - Carolina Lombardi
- Sleep Disorders Center, Department of Cardiology, San Luca Hospital, Istituto Auxologico Italiano, IRCCS, 20145 Milan, Italy;
- Department of Medicine and Surgery, University of Milano-Bicocca, 20126 Milan, Italy
| | - Simone Lombardo
- Sleep Clinic, Division of Respiratory Medicine, Ospedali Riuniti Villa Sofia-Cervello, 90146 Palermo, Italy;
| | - Francesco Fanfulla
- Respiratory Function and Sleep Unit, Maugeri Clinical and Scientific Institute of Pavia and Montescano, 27100 Pavia, Italy;
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11
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Lechat B, Scott H, Decup F, Hansen KL, Micic G, Dunbar C, Liebich T, Catcheside P, Zajamsek B. Environmental noise-induced cardiovascular responses during sleep. Sleep 2021; 45:6489046. [PMID: 34965303 DOI: 10.1093/sleep/zsab302] [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: 09/22/2021] [Revised: 11/21/2021] [Indexed: 11/15/2022] Open
Abstract
STUDY OBJECTIVES This study was designed to test the utility of cardiovascular responses as markers of potentially different environmental noise disruption effects of wind farm compared to traffic noise exposure during sleep. METHODS Twenty participants underwent polysomnography. In random order, and at six sound pressure levels from 33 dBA to 48 dBA in 3 dB increments, three types of wind farm and two types of road traffic noise recordings of 20-sec duration were played during established N2 or deeper sleep, each separated by 20 seconds without noise. Each noise sequence also included a no-noise control. Electrocardiogram and finger pulse oximeter recorded pulse wave amplitude changes from the pre-noise onset baseline following each noise exposure and were assessed algorithmically to quantify the magnitude of heart rate and finger vasoconstriction responses to noise exposure. RESULTS Higher sound pressure levels were more likely to induce drops in pulse wave amplitude. Sound pressure levels as low as 39 dBA evoked a pulse wave amplitude response (Odds ratio [95% confidence interval]; 1.52 [1.15, 2.02]). Wind farm noise with amplitude modulation was less likely to evoke a pulse wave amplitude response than the other noise types, but warrants cautious interpretation given low numbers of replications within each noise type. CONCLUSION These preliminary data support that drops in pulse wave amplitude are a particularly sensitive marker of noise-induced cardiovascular responses during. Larger trials are clearly warranted to further assess relationships between recurrent cardiovascular activation responses to environmental noise and potential long-term health effects.
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Affiliation(s)
- Bastien Lechat
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Bedford Park, Adelaide, SA 5042, Australia
| | - Hannah Scott
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Bedford Park, Adelaide, SA 5042, Australia
| | - Felix Decup
- College of Science and Engineering, Flinders University, Bedford Park, Adelaide, SA 5042, Australia
| | - Kristy L Hansen
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Bedford Park, Adelaide, SA 5042, Australia.,College of Science and Engineering, Flinders University, Bedford Park, Adelaide, SA 5042, Australia
| | - Gorica Micic
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Bedford Park, Adelaide, SA 5042, Australia
| | - Claire Dunbar
- College of Education, Psychology and Social Work, Flinders University, Bedford Park, Adelaide, SA 5042, Australia
| | - Tessa Liebich
- College of Education, Psychology and Social Work, Flinders University, Bedford Park, Adelaide, SA 5042, Australia
| | - Peter Catcheside
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Bedford Park, Adelaide, SA 5042, Australia
| | - Branko Zajamsek
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Bedford Park, Adelaide, SA 5042, Australia
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12
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Lechat B, Scott H, Naik G, Hansen K, Nguyen DP, Vakulin A, Catcheside P, Eckert DJ. New and Emerging Approaches to Better Define Sleep Disruption and Its Consequences. Front Neurosci 2021; 15:751730. [PMID: 34690688 PMCID: PMC8530106 DOI: 10.3389/fnins.2021.751730] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Accepted: 09/16/2021] [Indexed: 01/07/2023] Open
Abstract
Current approaches to quantify and diagnose sleep disorders and circadian rhythm disruption are imprecise, laborious, and often do not relate well to key clinical and health outcomes. Newer emerging approaches that aim to overcome the practical and technical constraints of current sleep metrics have considerable potential to better explain sleep disorder pathophysiology and thus to more precisely align diagnostic, treatment and management approaches to underlying pathology. These include more fine-grained and continuous EEG signal feature detection and novel oxygenation metrics to better encapsulate hypoxia duration, frequency, and magnitude readily possible via more advanced data acquisition and scoring algorithm approaches. Recent technological advances may also soon facilitate simple assessment of circadian rhythm physiology at home to enable sleep disorder diagnostics even for “non-circadian rhythm” sleep disorders, such as chronic insomnia and sleep apnea, which in many cases also include a circadian disruption component. Bringing these novel approaches into the clinic and the home settings should be a priority for the field. Modern sleep tracking technology can also further facilitate the transition of sleep diagnostics from the laboratory to the home, where environmental factors such as noise and light could usefully inform clinical decision-making. The “endpoint” of these new and emerging assessments will be better targeted therapies that directly address underlying sleep disorder pathophysiology via an individualized, precision medicine approach. This review outlines the current state-of-the-art in sleep and circadian monitoring and diagnostics and covers several new and emerging approaches to better define sleep disruption and its consequences.
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Affiliation(s)
- Bastien Lechat
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Hannah Scott
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Ganesh Naik
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Kristy Hansen
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Duc Phuc Nguyen
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Andrew Vakulin
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Peter Catcheside
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Danny J Eckert
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
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