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Cho JS, Park JH. Application of artificial intelligence in hypertension. Clin Hypertens 2024; 30:11. [PMID: 38689376 PMCID: PMC11061896 DOI: 10.1186/s40885-024-00266-9] [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: 10/02/2023] [Accepted: 02/13/2024] [Indexed: 05/02/2024] Open
Abstract
Hypertension is an important modifiable risk factor for morbidity and mortality associated with cardiovascular disease. The incidence of hypertension is increasing not only in Korea but also in many Western countries due to the aging of the population and the increase in unhealthy lifestyles. However, hypertension control rates remain low due to poor adherence to antihypertensive medications, low awareness of hypertension, and numerous factors that contribute to hypertension, including diet, environment, lifestyle, obesity, and genetics. Because artificial intelligence (AI) involves data-driven algorithms, AI is an asset to understanding chronic diseases that are influenced by multiple factors, such as hypertension. Although several hypertension studies using AI have been published recently, most are exploratory descriptive studies that are often difficult for clinicians to understand and have little clinical relevance. This review aims to provide a clinician-centered perspective on AI by showing recent studies on the relevance of AI for patients with hypertension. The review is organized into sections on blood pressure measurement and hypertension diagnosis, prognosis, and management.
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Affiliation(s)
- Jung Sun Cho
- Division of Cardiology, Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Catholic Research Institute for Intractable Cardiovascular Disease, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Jae-Hyeong Park
- Department of Cardiology in Internal Medicine, Chungnam National University, Chungnam National University Hospital, 282 Munhwa-ro, Jung-gu, 35015, Daejeon, Republic of Korea.
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Volpes G, Valenti S, Genova G, Barà C, Parisi A, Faes L, Busacca A, Pernice R. Wearable Ring-Shaped Biomedical Device for Physiological Monitoring through Finger-Based Acquisition of Electrocardiographic, Photoplethysmographic, and Galvanic Skin Response Signals: Design and Preliminary Measurements. BIOSENSORS 2024; 14:205. [PMID: 38667198 PMCID: PMC11048376 DOI: 10.3390/bios14040205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Revised: 04/12/2024] [Accepted: 04/18/2024] [Indexed: 04/28/2024]
Abstract
Wearable health devices (WHDs) are rapidly gaining ground in the biomedical field due to their ability to monitor the individual physiological state in everyday life scenarios, while providing a comfortable wear experience. This study introduces a novel wearable biomedical device capable of synchronously acquiring electrocardiographic (ECG), photoplethysmographic (PPG), galvanic skin response (GSR) and motion signals. The device has been specifically designed to be worn on a finger, enabling the acquisition of all biosignals directly on the fingertips, offering the significant advantage of being very comfortable and easy to be employed by the users. The simultaneous acquisition of different biosignals allows the extraction of important physiological indices, such as heart rate (HR) and its variability (HRV), pulse arrival time (PAT), GSR level, blood oxygenation level (SpO2), and respiratory rate, as well as motion detection, enabling the assessment of physiological states, together with the detection of potential physical and mental stress conditions. Preliminary measurements have been conducted on healthy subjects using a measurement protocol consisting of resting states (i.e., SUPINE and SIT) alternated with physiological stress conditions (i.e., STAND and WALK). Statistical analyses have been carried out among the distributions of the physiological indices extracted in time, frequency, and information domains, evaluated under different physiological conditions. The results of our analyses demonstrate the capability of the device to detect changes between rest and stress conditions, thereby encouraging its use for assessing individuals' physiological state. Furthermore, the possibility of performing synchronous acquisitions of PPG and ECG signals has allowed us to compare HRV and pulse rate variability (PRV) indices, so as to corroborate the reliability of PRV analysis under stationary physical conditions. Finally, the study confirms the already known limitations of wearable devices during physical activities, suggesting the use of algorithms for motion artifact correction.
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Affiliation(s)
| | | | | | | | | | | | | | - Riccardo Pernice
- Department of Engineering, University of Palermo, Viale delle Scienze, Building 9, 90128 Palermo, Italy; (G.V.); (S.V.); (G.G.); (C.B.); (A.P.); (L.F.); (A.B.)
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Yilmaz G, Ong JL, Ling LH, Chee MWL. Insights into vascular physiology from sleep photoplethysmography. Sleep 2023; 46:zsad172. [PMID: 37379483 PMCID: PMC10566244 DOI: 10.1093/sleep/zsad172] [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: 02/24/2023] [Revised: 05/19/2023] [Indexed: 06/30/2023] Open
Abstract
STUDY OBJECTIVES Photoplethysmography (PPG) in consumer sleep trackers is now widely available and used to assess heart rate variability (HRV) for sleep staging. However, PPG waveform changes during sleep can also inform about vascular elasticity in healthy persons who constitute a majority of users. To assess its potential value, we traced the evolution of PPG pulse waveform during sleep alongside measurements of HRV and blood pressure (BP). METHODS Seventy-eight healthy adults (50% male, median [IQR range] age: 29.5 [23.0, 43.8]) underwent overnight polysomnography (PSG) with fingertip PPG, ambulatory blood pressure monitoring, and electrocardiography (ECG). Selected PPG features that reflect arterial stiffness: systolic to diastolic distance (∆T_norm), normalized rising slope (Rslope) and normalized reflection index (RI) were derived using a custom-built algorithm. Pulse arrival time (PAT) was calculated using ECG and PPG signals. The effect of sleep stage on these measures of arterial elasticity and how this pattern of sleep stage evolution differed with participant age were investigated. RESULTS BP, heart rate (HR) and PAT were reduced with deeper non-REM sleep but these changes were unaffected by the age range tested. After adjusting for lowered HR, ∆T_norm, Rslope, and RI showed significant effects of sleep stage, whereby deeper sleep was associated with lower arterial stiffness. Age was significantly correlated with the amount of sleep-related change in ∆T_norm, Rslope, and RI, and remained a significant predictor of RI after adjustment for sex, body mass index, office BP, and sleep efficiency. CONCLUSIONS The current findings indicate that the magnitude of sleep-related change in PPG waveform can provide useful information about vascular elasticity and age effects on this in healthy adults.
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Affiliation(s)
- Gizem Yilmaz
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ju Lynn Ong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Lieng-Hsi Ling
- Department of Cardiology, National University Heart Centre, National University Health System, Singapore and
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Michael W L Chee
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
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Verbraecken J. Respiratory event duration in obstructive sleep apnea: don't forget the chemical drive ! Sleep Med Rev 2023; 68:101765. [PMID: 36924700 DOI: 10.1016/j.smrv.2023.101765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 02/14/2023] [Indexed: 03/16/2023]
Affiliation(s)
- Johan Verbraecken
- Department of Pulmonary Medicine and Multidisciplinary Sleep Disorders Centre, Antwerp University Hospital and University of Antwerp, Drie Eikenstraat 655, 2650, Edegem, Antwerp, Belgium.
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Rinkevičius M, Charlton PH, Bailón R, Marozas V. Influence of Photoplethysmogram Signal Quality on Pulse Arrival Time during Polysomnography. SENSORS (BASEL, SWITZERLAND) 2023; 23:2220. [PMID: 36850820 PMCID: PMC9967654 DOI: 10.3390/s23042220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/05/2023] [Accepted: 02/15/2023] [Indexed: 06/18/2023]
Abstract
Intervals of low-quality photoplethysmogram (PPG) signals might lead to significant inaccuracies in estimation of pulse arrival time (PAT) during polysomnography (PSG) studies. While PSG is considered to be a "gold standard" test for diagnosing obstructive sleep apnea (OSA), it also enables tracking apnea-related nocturnal blood pressure fluctuations correlated with PAT. Since the electrocardiogram (ECG) is recorded synchronously with the PPG during PSG, it makes sense to use the ECG signal for PPG signal-quality assessment. (1) Objective: to develop a PPG signal-quality assessment algorithm for robust PAT estimation, and investigate the influence of signal quality on PAT during various sleep stages and events such as OSA. (2) Approach: the proposed algorithm uses R and T waves from the ECG to determine approximate locations of PPG pulse onsets. The MESA database of 2055 PSG recordings was used for this study. (3) Results: the proportions of high-quality PPG were significantly lower in apnea-related oxygen desaturation (matched-pairs rc = 0.88 and rc = 0.97, compared to OSA and hypopnea, respectively, when p < 0.001) and arousal (rc = 0.93 and rc = 0.98, when p < 0.001) than in apnea events. The significantly large effect size of interquartile ranges of PAT distributions was between low- and high-quality PPG (p < 0.001, rc = 0.98), and regular and irregular pulse waves (p < 0.001, rc = 0.74), whereas a lower quality of the PPG signal was found to be associated with a higher interquartile range of PAT across all subjects. Suggested PPG signal quality-based PAT evaluation reduced deviations (e.g., rc = 0.97, rc = 0.97, rc = 0.99 in hypopnea, oxygen desaturation, and arousal stages, respectively, when p < 0.001) and allowed obtaining statistically larger differences between different sleep stages and events. (4) Significance: the implemented algorithm has the potential to increase the robustness of PAT estimation in PSG studies related to nocturnal blood pressure monitoring.
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Affiliation(s)
- Mantas Rinkevičius
- Biomedical Engineering Institute, Kaunas University of Technology, K. Baršausko Str. 59, LT-51423 Kaunas, Lithuania
| | - Peter H. Charlton
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 1TN, UK
- Research Centre for Biomedical Engineering, University of London, London WC1E 7HU, UK
| | - Raquel Bailón
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon, University of Zaragoza, 50009 Zaragoza, Spain
- Biomedical Research Networking Center (CIBER), 50018 Zaragoza, Spain
| | - Vaidotas Marozas
- Biomedical Engineering Institute, Kaunas University of Technology, K. Baršausko Str. 59, LT-51423 Kaunas, Lithuania
- Faculty of Electrical and Electronics Engineering, Kaunas University of Technology, Studentų Str. 50, LT-51368 Kaunas, Lithuania
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Hajipour M, Baumann B, Azarbarzin A, Allen AH, Liu Y, Fels S, Goodfellow S, Singh A, Jen R, Ayas NT. Association of alternative polysomnographic features with patient outcomes in obstructive sleep apnea: a systematic review. J Clin Sleep Med 2023; 19:225-242. [PMID: 36106591 PMCID: PMC9892740 DOI: 10.5664/jcsm.10298] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 09/09/2022] [Accepted: 09/12/2022] [Indexed: 02/04/2023]
Abstract
STUDY OBJECTIVES Polysomnograms (PSGs) collect a plethora of physiologic signals across the night. However, few of these PSG data are incorporated into standard reports, and hence, ultimately, under-utilized in clinical decision making. Recently, there has been substantial interest regarding novel alternative PSG metrics that may help to predict obstructive sleep apnea (OSA)-related outcomes better than standard PSG metrics such as the apnea-hypopnea index. We systematically review the recent literature for studies that examined the use of alternative PSG metrics in the context of OSA and their association with health outcomes. METHODS We systematically searched EMBASE, MEDLINE, and the Cochrane Database of Systematic Reviews for studies published between 2000 and 2022 for those that reported alternative metrics derived from PSG in adults and related them to OSA-related outcomes. RESULTS Of the 186 initial studies identified by the original search, data from 31 studies were ultimately included in the final analysis. Numerous metrics were identified that were significantly related to a broad range of outcomes. We categorized the outcomes into 2 main subgroups: (1) cardiovascular/metabolic outcomes and mortality and (2) cognitive function- and vigilance-related outcomes. Four general categories of alternative metrics were identified based on signals analyzed: autonomic/hemodynamic metrics, electroencephalographic metrics, oximetric metrics, and respiratory event-related metrics. CONCLUSIONS We have summarized the current landscape of literature for alternative PSG metrics relating to risk prediction in OSA. Although promising, further prospective observational studies are needed to verify findings from other cohorts, and to assess the clinical utility of these metrics. CITATION Hajipour M, Baumann B, Azarbarzin A, et al. Association of alternative polysomnographic features with patient outcomes in obstructive sleep apnea: a systematic review. J Clin Sleep Med. 2023;19(2):225-242.
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Affiliation(s)
- Mohammadreza Hajipour
- Department of Experimental Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Brett Baumann
- Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Ali Azarbarzin
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital and Harvard Medical School, Harvard University, Boston, Massachusetts
| | - A.J. Hirsch Allen
- Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Yu Liu
- Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
- Department of Pharmacology, Shanxi Medical University, Taiyuan, China
| | - Sidney Fels
- Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Sebastian Goodfellow
- Department of Critical Care Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Amrit Singh
- Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Rachel Jen
- Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Najib T. Ayas
- Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
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Lechat B, Nguyen DP, Reynolds A, Loffler K, Escourrou P, McEvoy RD, Adams R, Catcheside PG, Eckert DJ. Single-Night Diagnosis of Sleep Apnea Contributes to Inconsistent Cardiovascular Outcome Findings. Chest 2023:S0012-3692(23)00157-5. [PMID: 36716954 DOI: 10.1016/j.chest.2023.01.027] [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: 09/20/2022] [Revised: 12/05/2022] [Accepted: 01/18/2023] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Single-night disease misclassification of OSA due to night-to-night variability may contribute to inconsistent findings in OSA trials. RESEARCH QUESTION Does multinight quantification of OSA severity provide more precise estimates of associations with incident hypertension? STUDY DESIGN AND METHODS A total of 3,831 participants without hypertension at baseline were included in simulation analyses. Included participants had ≥ 28 days of nightly apnea-hypopnea index (AHI) recordings via an under-mattress sensor and ≥ 3 separate BP measurements over a 3-month baseline period followed by ≥ 3 separate BP measurements 6 to 9 months postbaseline. Incident hypertension was defined as a mean systolic BP ≥ 140 mm Hg or a mean diastolic BP ≥ 90 mm Hg. Simulated trials (1,000) were performed, using bootstrap methods to investigate the effect of variable numbers of nights (x = 1-56 per participant) to quantify AHI and the ability to detect associations between OSA and incident hypertension via logistic regression adjusted for age, sex, and BMI. RESULTS Participants were middle-aged (mean ± SD, 52 ± 12 y), mostly men (91%), and overweight (BMI, 28 ± 5 kg/m2). Single-night quantification of OSA failed to detect an association with hypertension risk in 42% of simulated trials (α = 0.05). Conversely, 100% of trials detected an association when AHI was quantified over ≥ 28 nights. Point estimates of hypertension risk were also 50% higher and uncertainty was 5 times lower during multinight vs single-night simulation trials. INTERPRETATION Multinight monitoring of OSA allows for better estimates of hypertension risk and potentially other adverse health outcomes associated with OSA. These findings have important implications for clinical care and OSA trial design.
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Affiliation(s)
- Bastien Lechat
- Flinders Health and Medical Research Institute, Sleep Health, Flinders University, Adelaide, SA, Australia.
| | - Duc Phuc Nguyen
- Flinders Health and Medical Research Institute, Sleep Health, Flinders University, Adelaide, SA, Australia; College of Science and Engineering, Flinders University, Adelaide, SA, Australia
| | - Amy Reynolds
- Flinders Health and Medical Research Institute, Sleep Health, Flinders University, Adelaide, SA, Australia
| | - Kelly Loffler
- Flinders Health and Medical Research Institute, Sleep Health, Flinders University, Adelaide, SA, Australia
| | | | - R Doug McEvoy
- Flinders Health and Medical Research Institute, Sleep Health, Flinders University, Adelaide, SA, Australia
| | - Robert Adams
- Flinders Health and Medical Research Institute, Sleep Health, Flinders University, Adelaide, SA, Australia
| | - Peter G Catcheside
- Flinders Health and Medical Research Institute, Sleep Health, Flinders University, Adelaide, SA, Australia
| | - Danny J Eckert
- Flinders Health and Medical Research Institute, Sleep Health, Flinders University, Adelaide, SA, Australia
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8
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Herranz Olazabal J, Wieringa F, Hermeling E, Van Hoof C. Comparing Remote Speckle Plethysmography and Finger-Clip Photoplethysmography with Non-Invasive Finger Arterial Pressure Pulse Waves, Regarding Morphology and Arrival Time. BIOENGINEERING (BASEL, SWITZERLAND) 2023; 10:bioengineering10010101. [PMID: 36671673 PMCID: PMC9854800 DOI: 10.3390/bioengineering10010101] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 01/04/2023] [Accepted: 01/08/2023] [Indexed: 01/14/2023]
Abstract
OBJECTIVE The goal was to compare Speckle plethysmography (SPG) and Photoplethysmography (PPG) with non-invasive finger Arterial Pressure (fiAP) regarding Pulse Wave Morphology (PWM) and Pulse Arrival Time (PAT). METHODS Healthy volunteers (n = 8) were connected to a Non-Invasive Blood Pressure (NIBP) monitor providing fiAP pulse wave and PPG from a clinical transmission-mode SpO2 finger clip. Biopac recorded 3-lead ECG. A camera placed at a 25 cm distance recorded a video stream (100 fps) of a finger illuminated by a laser diode at 639 nm. A chest belt (Polar) monitored respiration. All signals were recorded simultaneously during episodes of spontaneous breathing and paced breathing. ANALYSIS Post-processing was performed in Matlab to obtain SPG and analyze the SPG, PPG and fiAP mean absolute deviations (MADs) on PWM, plus PAT modulation. RESULTS Across 2599 beats, the average fiAP MAD with PPG was 0.17 (0-1) and with SPG 0.09 (0-1). PAT derived from ECG-fiAP correlated as follows: 0.65 for ECG-SPG and 0.67 for ECG-PPG. CONCLUSION Compared to the clinical NIBP monitor fiAP reference, PWM from an experimental camera-derived non-contact reflective-mode SPG setup resembled fiAP significantly better than PPG from a simultaneously recorded clinical transmission-mode finger clip. For PAT values, no significant difference was found between ECG-SPG and ECG-PPG compared to ECG-fiAP.
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Affiliation(s)
- Jorge Herranz Olazabal
- IMEC, 3000 Leuven, Belgium
- Faculty of Engineering Science, Katholieke Universiteit Leuven (KUL), 3000 Leuven, Belgium
- IMEC NL, 5656 AE Eindhoven, The Netherlands
| | - Fokko Wieringa
- IMEC NL, 5656 AE Eindhoven, The Netherlands
- Division of Internal Medicine, Department of Nephrology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | | | - Chris Van Hoof
- IMEC, 3000 Leuven, Belgium
- Faculty of Engineering Science, Katholieke Universiteit Leuven (KUL), 3000 Leuven, Belgium
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Guo J, Xiao Y. New Metrics from Polysomnography: Precision Medicine for OSA Interventions. Nat Sci Sleep 2023; 15:69-77. [PMID: 36923968 PMCID: PMC10010122 DOI: 10.2147/nss.s400048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 02/20/2023] [Indexed: 03/18/2023] Open
Abstract
Obstructive sleep apnea (OSA) is a highly preventable disease accompanied by multiple comorbid conditions. Despite the well-established cardiovascular and neurocognitive sequelae with OSA, the optimal metric for assessing the OSA severity and response to therapy remains controversial. Although overnight polysomnography (PSG) is the golden standard for OSA diagnosis, the abundant information is not fully exploited. With the development of deep learning and the era of big data, new metrics derived from PSG have been validated in some OSA consequences and personalized treatment. In this review, these metrics are introduced based on the pathophysiological mechanisms of OSA and new technologies. Emphasis is laid on the advantages and the prognostic value against apnea-hypopnea index. New classification criteria should be established based on these metrics and other clinical characters for precision medicine.
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Affiliation(s)
- Junwei Guo
- Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China
| | - Yi Xiao
- Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China
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10
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Lechat B, Loffler KA, Wallace DM, Reynolds A, Appleton SL, Scott H, Vakulin A, Lovato N, Adams R, Eckert DJ, Catcheside PG, Sweetman A. All-Cause Mortality in People with Co-Occurring Insomnia Symptoms and Sleep Apnea: Analysis of the Wisconsin Sleep Cohort. Nat Sci Sleep 2022; 14:1817-1828. [PMID: 36263373 PMCID: PMC9576322 DOI: 10.2147/nss.s379252] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 09/30/2022] [Indexed: 11/30/2022] Open
Abstract
PURPOSE Insomnia symptoms and sleep apnea frequently co-occur and are associated with worse sleep, daytime function, mental health and quality of life, compared to either insomnia or obstructive sleep apnea (OSA) alone. This study aimed to investigate the association of symptoms of co-morbid insomnia and sleep apnea (COMISA) with all-cause mortality. PATIENTS AND METHODS Wisconsin Sleep Cohort data were analysed to assess potential associations between COMISA symptoms and all-cause mortality. Nocturnal insomnia symptoms were defined as difficulties initiating sleep, maintaining sleep, and/or early morning awakenings "often" or "almost always", and/or regular sedative-hypnotic medicine use. OSA was defined as an apnea-hypopnea index ≥5/hr sleep. Participants were classified as having neither insomnia symptoms nor OSA, insomnia symptoms alone, OSA alone, or COMISA symptoms. Associations between the four groups and all-cause mortality over 20 years of follow-up were examined via multivariable adjusted Cox regression models. RESULTS Among 1115 adult participants (mean ± SD age 55 ± 8 years, 53% males), 19.1% had COMISA symptoms. After controlling for sociodemographic and behavioral factors, COMISA symptoms were associated with an increased risk of all-cause mortality compared to no insomnia symptoms or OSA (HR [95% CI]; 1.71 [1.00-2.93]). OSA alone (0.91 [0.53, 1.57]) and insomnia symptoms alone (1.04 [0.55, 1.97]) were not associated with increased mortality risk. CONCLUSION Co-morbid insomnia symptoms and sleep apnea is associated with increased all-cause mortality risk. Future research should investigate mechanisms underpinning COMISA and the effectiveness of different treatment approaches to reduce mortality risk for this common condition.
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Affiliation(s)
- Bastien Lechat
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Adelaide, South Australia, Australia
| | - Kelly A Loffler
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Adelaide, South Australia, Australia
| | - Douglas M Wallace
- Department of Neurology, Sleep Medicine Division, University of Miami Miller School of Medicine, Miami, FL, USA.,Neurology Service, Bruce W. Carter Department of Veterans Affairs Medical Centre, Miami, FL, USA
| | - Amy Reynolds
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Adelaide, South Australia, Australia
| | - Sarah L Appleton
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Adelaide, South Australia, Australia
| | - Hannah Scott
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Adelaide, South Australia, Australia
| | - Andrew Vakulin
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Adelaide, South Australia, Australia.,National Centre for Sleep Health Services Research: A NHMRC Centre of Research Excellence, Flinders University, Adelaide, South Australia, Australia
| | - Nicole Lovato
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Adelaide, South Australia, Australia.,National Centre for Sleep Health Services Research: A NHMRC Centre of Research Excellence, Flinders University, Adelaide, South Australia, Australia
| | - Robert Adams
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Adelaide, South Australia, Australia.,National Centre for Sleep Health Services Research: A NHMRC Centre of Research Excellence, Flinders University, Adelaide, South Australia, Australia
| | - Danny J Eckert
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Adelaide, South Australia, Australia
| | - Peter G Catcheside
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Adelaide, South Australia, Australia
| | - Alexander Sweetman
- Adelaide Institute for Sleep Health and FHMRI Sleep Health, Flinders University, Adelaide, South Australia, Australia.,National Centre for Sleep Health Services Research: A NHMRC Centre of Research Excellence, Flinders University, Adelaide, South Australia, Australia
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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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Lechat B, Naik G, Reynolds A, Aishah A, Scott H, Loffler KA, Vakulin A, Escourrou P, McEvoy RD, Adams RJ, Catcheside PG, Eckert DJ. Multi-night Prevalence, Variability, and Diagnostic Misclassification of Obstructive Sleep Apnea. Am J Respir Crit Care Med 2021; 205:563-569. [PMID: 34904935 PMCID: PMC8906484 DOI: 10.1164/rccm.202107-1761oc] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Rationale Recent studies suggest that obstructive sleep apnea (OSA) severity can vary markedly from night to night which may have important implications for diagnosis and management. Objectives This study aimed to assess OSA prevalence from multi-night in-home recordings and the impact of night-to-night variability in OSA severity on diagnostic classification in a large, global, non-randomly selected community sample from a consumer database of people that purchased a novel, validated, under-mattress sleep analyzer. Methods 67,278 individuals aged between 18 and 90 years underwent in-home nightly monitoring over an average of ~170 nights per participant between July 2020 to March 2021. OSA was defined as a nightly mean apnea-hypopnea index (AHI) >15 events/h. Outcomes were multi-night global prevalence and likelihood of OSA misclassification from a single night AHI value. Measurements and Main Results Over 11.6 million nights of data were collected and analyzed. OSA global prevalence was 22.6% (95% CI: 20.9-24.3%). The likelihood of misdiagnosis in people with OSA based on a single night ranged between ~20% and 50%. Misdiagnosis error rates decreased with increased monitoring nights (e.g. 1-night F1-score=0.77 vs. 0.94 for 14-nights); and remained stable after 14-nights of monitoring. Conclusions Multi-night in-home monitoring using novel non-invasive under mattress sensor technology indicates a global prevalence of moderate to severe OSA of ~20%, and that ~20% of people diagnosed with a single night study may be misclassified. These findings highlight the need to consider night-to-night variation on OSA diagnosis and management. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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Affiliation(s)
- Bastien Lechat
- Flinders University, 1065, Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Adelaide, South Australia, Australia;
| | - Ganesh Naik
- Flinders University, 1065, Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Adelaide, South Australia, Australia
| | - Amy Reynolds
- Flinders University, 1065, Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Adelaide, South Australia, Australia
| | - Atqiya Aishah
- Flinders University, 1065, Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Adelaide, South Australia, Australia.,University of New South Wales, 7800, School of Medical Science, Neuroscience Research Australia (NeuRA), Sydney, New South Wales, Australia
| | - Hannah Scott
- Flinders University, 1065, Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Adelaide, South Australia, Australia
| | - Kelly A Loffler
- Flinders University, 1065, Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Adelaide, South Australia, Australia
| | - Andrew Vakulin
- Flinders University, 1065, Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Adelaide, South Australia, Australia
| | | | - R Doug McEvoy
- Flinders University, 1065, Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Adelaide, South Australia, Australia
| | - Robert J Adams
- Flinders University, 1065, Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Adelaide, South Australia, Australia
| | - Peter G Catcheside
- Flinders University, 1065, Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Adelaide, South Australia, Australia
| | - Danny J Eckert
- Flinders University, 1065, Adelaide Institute for Sleep Health and FHMRI Sleep Health, College of Medicine and Public Health, Adelaide, South Australia, Australia
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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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A Novel EEG Derived Measure of Disrupted Delta Wave Activity during Sleep Predicts All-Cause Mortality Risk. Ann Am Thorac Soc 2021; 19:649-658. [PMID: 34672877 DOI: 10.1513/annalsats.202103-315oc] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
RATIONALE Conventional markers of sleep disturbance, based on manual electroencephalography scoring, may not adequately capture important features of more fundamental electroencephalography-related sleep disturbance. OBJECTIVES This study aimed to determine if more comprehensive power-spectral measures of delta wave activity during sleep are stronger independent predictors of mortality than conventional sleep quality and disturbance metrics. METHODS Power spectral analysis of the delta frequency band and spectral entropy-based markers to quantify disruption of electroencephalography delta power during sleep were performed to examine potential associations with mortality risk in the Sleep Heart Health Study cohort (N = 5804). Adjusted Cox proportional hazard models were used to determine the association between disrupted delta wave activity at baseline and all-cause mortality over an ~11y follow-up period. RESULTS Disrupted delta electroencephalography power during sleep was associated with a 32% increased risk of all-cause mortality compared with no fragmentation (hazard ratios 1.32 [95% confidence interval 1.14, 1.50], after adjusting for total sleep time and other clinical and life-style related covariates including sleep apnea. The association was of similar magnitude to a reduction in total sleep time from 6.5h to 4.25h. Conventional measures of sleep quality, including wake after sleep onset and arousal index were not predictive of all-cause mortality. CONCLUSIONS Delta wave activity disruption during sleep is strongly associated with all-cause mortality risk, independent of traditional potential confounders. Future investigation into the potential role of delta sleep disruption on other specific adverse health consequences such as cardiometabolic, mental health and safety outcomes has considerable potential to provide unique neurophysiological insight.
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