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Sleep Apnea Syndromes: HELP
Articles by Thomas Penzel
Based on 89 articles published since 2010
(Why 89 articles?)
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Between 2010 and 2020, T. Penzel wrote the following 89 articles about Sleep Apnea Syndromes.
 
+ Citations + Abstracts
Pages: 1 · 2 · 3 · 4
1 Editorial Editorial: Anatomy of Upper Airway and Neuronal Control of Pharyngeal Muscles in Obstructive Sleep Apnea. 2019

Fenik, Victor B / Penzel, Thomas / Malhotra, Atul. ·Department of Medical Research, VA Greater Los Angeles Healthcare System (VHA), Los Angeles, CA, United States. · Websciences International, Los Angeles, CA, United States. · Center of Sleep Medicine, Charité University Hospital, Berlin, Germany. · Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego, San Diego, CA, United States. ·Front Neurol · Pubmed #31338060.

ABSTRACT: -- No abstract --

2 Editorial Use of large patient registries in sleep apnea patients - Results from the ESADA database. 2019

Penzel, Thomas. ·Charite Universitätsmedizin Berlin, Sleep Medicine Center, Chariteplatz 1, 10117, Berlin, Germany. Electronic address: thomas.penzel@charite.de. ·Sleep Med · Pubmed #30770205.

ABSTRACT: -- No abstract --

3 Review On the rise and fall of the apnea-hypopnea index: A historical review and critical appraisal. 2020

Pevernagie, Dirk A / Gnidovec-Strazisar, Barbara / Grote, Ludger / Heinzer, Raphael / McNicholas, Walter T / Penzel, Thomas / Randerath, Winfried / Schiza, Sophia / Verbraecken, Johan / Arnardottir, Erna S. ·Department of Lung Diseases, Ghent University Hospital, Gent, Belgium. · Department of Internal Medicine and Paediatrics, Ghent University, Ghent, Belgium. · Department of Paediatrics, General Hospital Celje and University of Ljubljana, Celje, Slovenia. · Department for Respiratory Disease, Sahlgrenska University Hospital, Centre for Sleep and Wake Disorders, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden. · Pulmonary Department, Center for Investigation and Research in Sleep (CIRS), Lausanne University Hopital, Lausanne, Switzerland. · School of Medicine, University College Dublin, Department of Respiratory and Sleep Medicine, St Vincent's Hospital Group, Dublin, Ireland. · Interdisciplinary Sleep Medicine Center, Charité University Hospital Berlin, Berlin, Germany. · Russian Federation, Saratov State University, Saratov, Russia. · Institute of Pneumology at the University of Cologne, Solingen, Germany. · Bethanien Hospital, Clinic for Pneumology and Allergology, Centre of Sleep Medicine and Respiratory Care, Solingen, Germany. · Sleep Disorders Unit, Department of Respiratory Medicine, Medical School, University of Crete, Rethimno, Greece. · Department of Pulmonary Medicine, Multidisciplinary Sleep Disorders Centre, Antwerp University Hospital and University of Antwerp, Antwerp, Belgium. · Department of Engineering, Reykjavik University, Reykjavik, Iceland. · Internal Medicine Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland. ·J Sleep Res · Pubmed #32406974.

ABSTRACT: The publication of "The Sleep Apnea Syndromes" by Guilleminault et al. in the 1970s hallmarked the discovery of a new disease entity involving serious health consequences. Obstructive sleep apnea was shown to be the most important disorder among the sleep apnea syndromes (SAS). In the course of time, it was found that the prevalence of obstructive sleep apnea reached the proportions of a global epidemic, with a major impact on public health, safety and the economy. Early on, a metric was introduced to gauge the seriousness of obstructive sleep apnea, based on the objective measurement of respiratory events during nocturnal sleep. The apnea index and later on the apnea-hypopnea index, being the total count of overnight respiratory events divided by the total sleep time in hours, were embraced as principle measures to establish the diagnosis of obstructive sleep apnea and to rate its severity. The current review summarises the historical evolution of the apnea-hypopnea index, which has been subject to many changes, and has been criticised for not capturing relevant clinical features of obstructive sleep apnea. In fact, the application of the apnea-hypopnea index as a continuous exposure variable is based on assumptions that it represents a disease state of obstructive sleep apnea and that evocative clinical manifestations are invariably caused by obstructive sleep apnea if the apnea-hypopnea index is above diagnostic threshold. A critical appraisal of the extensive literature shows that both assumptions are invalid. This conclusion prompts a reconsideration of the role of the apnea-hypopnea index as the prime diagnostic metric of clinically relevant obstructive sleep apnea.

4 Review A Review of Obstructive Sleep Apnea Detection Approaches. 2019

Mendonca, Fabio / Mostafa, Sheikh Shanawaz / Ravelo-Garcia, Antonio G / Morgado-Dias, Fernando / Penzel, Thomas. · ·IEEE J Biomed Health Inform · Pubmed #29993672.

ABSTRACT: Sleep disorders are a common health condition that can affect numerous aspects of life. Obstructive sleep apnea is one of the most common disorders and is characterized by a reduction or cessation of airflow during sleep. In many countries, this disorder is usually diagnosed in sleep laboratories, by polysomnography, which is an expensive procedure involving much effort for the patient. Multiple systems have been proposed to address this situation, including performing the examination and analysis in the patient's home, using sensors to detect physiological signals that are automatically analyzed by algorithms. However, the precision of these devices is usually not enough to provide clinical diagnosis. Therefore, the objective of this review is to analyze already existing algorithms that have not been implemented on hardware but have had their performance verified by at least one experiment that aims to detect obstructive sleep apnea to predict trends. The performance of different algorithms and methods for apnea detection through the use of different sensors (pulse oximetry, electrocardiogram, respiration, sound, and combined approaches) has been evaluated. 84 original research articles published from 2003 to 2017 with the potential to be promising diagnostic tools have been selected to cover multiple solutions. This paper could provide valuable information for those researchers who want to carry out a hardware implementation of potential signal processing algorithms.

5 Review Devices for home detection of obstructive sleep apnea: A review. 2018

Mendonça, Fábio / Mostafa, Sheikh Shanawaz / Ravelo-García, Antonio G / Morgado-Dias, Fernando / Penzel, Thomas. ·Madeira Interactive Technologies Institute, Portugal; Universidade de Lisboa, Instituto Superior Técnico, Portugal. · Universidad de Las Palmas de Gran Canaria, Institute for Technological Development and Innovation in Communications, Spain. Electronic address: antonio.ravelo@ulpgc.es. · Madeira Interactive Technologies Institute, Portugal; Universidade da Madeira, Portugal. · Charité Universitatsmedizin, Sleep Center, Germany; International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic. ·Sleep Med Rev · Pubmed #30149930.

ABSTRACT: One of the most common sleep-related disorders is obstructive sleep apnea, characterized by a reduction of airflow while breathing during sleep and cause significant health problems. This disorder is mainly diagnosed in sleep labs with polysomnography, involving high costs and stress for the patient. To address this situation multiple systems have been proposed to conduct the examination and analysis in the patient's home, using sensors to detect physiological signals that are examined by algorithms. The objective of this research is to review publications that show the performance of different devices for ambulatory diagnosis of sleep apnea. Commercial systems that were examined by an independent research group and validated research projects were selected. In total 117 articles were analysed, including a total of 50 commercial devices. Each article was evaluated according to diagnostic elements, level of automatisation implemented and the deducted level of evidence and quality rating. Each device was categorized using the SCOPER categorization system, including an additional proposed category, and a final comparison was performed to determine the sensors that provided the best results.

6 Review Opportunities for utilizing polysomnography signals to characterize obstructive sleep apnea subtypes and severity. 2018

Mazzotti, Diego R / Lim, Diane C / Sutherland, Kate / Bittencourt, Lia / Mindel, Jesse W / Magalang, Ulysses / Pack, Allan I / de Chazal, Philip / Penzel, Thomas. ·Center for Sleep and Circadian Neurobiology, University of Pennsylvania, Philadelphia, United States of America. ·Physiol Meas · Pubmed #30047487.

ABSTRACT: BACKGROUND: Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder with many pathophysiological pathways to disease. Currently, the diagnosis and classification of OSA is based on the apnea-hypopnea index, which poorly correlates to underlying pathology and clinical consequences. A large number of in-laboratory sleep studies are performed around the world every year, already collecting an enormous amount of physiological data within an individual. Clinically, we have not yet fully taken advantage of this data, but combined with existing analytical approaches, we have the potential to transform the way OSA is managed within an individual patient. Currently, respiratory signals are used to count apneas and hypopneas, but patterns such as inspiratory flow signals can be used to predict optimal OSA treatment. Electrocardiographic data can reveal arrhythmias, but patterns such as heart rate variability can also be used to detect and classify OSA. Electroencephalography is used to score sleep stages and arousals, but specific patterns such as the odds-ratio product can be used to classify how OSA patients responds differently to arousals. OBJECTIVE: In this review, we examine these and many other existing computer-aided polysomnography signal processing algorithms and how they can reflect an individual's manifestation of OSA. SIGNIFICANCE: Together with current technological advance, it is only a matter of time before advanced automatic signal processing and analysis is widely applied to precision medicine of OSA in the clinical setting.

7 Review New technology to assess sleep apnea: wearables, smartphones, and accessories. 2018

Penzel, Thomas / Schöbel, Christoph / Fietze, Ingo. ·Interdisciplinary Sleep medicine Center, Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany. · International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic. ·F1000Res · Pubmed #29707207.

ABSTRACT: Sleep medicine has been an expanding discipline during the last few decades. The prevalence of sleep disorders is increasing, and sleep centers are expanding in hospitals and in the private care environment to meet the demands. Sleep medicine has evidence-based guidelines for the diagnosis and treatment of sleep disorders. However, the number of sleep centers and caregivers in this area is not sufficient. Many new methods for recording sleep and diagnosing sleep disorders have been developed. Many sleep disorders are chronic conditions and require continuous treatment and monitoring of therapy success. Cost-efficient technologies for the initial diagnosis and for follow-up monitoring of treatment are important. It is precisely here that telemedicine technologies can meet the demands of diagnosis and therapy follow-up studies. Wireless recording of sleep and related biosignals allows diagnostic tools and therapy follow-up to be widely and remotely available. Moreover, sleep research requires new technologies to investigate underlying mechanisms in the regulation of sleep in order to better understand the pathophysiology of sleep disorders. Home recording and non-obtrusive recording over extended periods of time with telemedicine methods support this research. Telemedicine allows recording with little subject interference under normal and experimental life conditions.

8 Review Pre-operative screening for obstructive sleep apnoea. 2017

Verbraecken, Johan / Hedner, Jan / Penzel, Thomas. ·Dept of Pulmonary Medicine and Multidisciplinary Sleep Disorders Centre, Antwerp University Hospital and University of Antwerp, Antwerp, Belgium johan.verbraecken@uza.be. · Dept of Sleep Medicine, Pulmonary Medicine and Allergology, Sahlgrenska University Hospital, Gothenburg, Sweden. · Sleep Medicine Center, Dept of Cardiology CC11, Charité - Universitätsmedizin Berlin, Berlin, Germany. ·Eur Respir Rev · Pubmed #28049125.

ABSTRACT: Sleep disordered breathing, especially obstructive sleep apnoea (OSA), has a high and increasing prevalence. Depending on the apnoea and hypopnoea scoring criteria used, and depending on the sex and age of the subjects investigated, prevalence varies between 3% and 49% of the general population. These varying prevalences need to be reflected when considering screening for OSA. OSA is a cardiovascular risk factor and patients are at risk when undergoing medical interventions such as surgery. Screening for OSA before anaesthesia and surgical interventions is increasingly considered. Therefore, methods for screening and the rationale for screening for OSA are reviewed in this study.

9 Review Definition and Importance of Autonomic Arousal in Patients with Sleep Disordered Breathing. 2016

Bartels, Wibke / Buck, Dana / Glos, Martin / Fietze, Ingo / Penzel, Thomas. ·Interdisciplinary Center of Sleep Medicine, Department of Cardiology, Charité Universitätsmedizin Berlin, Charité Campus Mitte, Charitéplatz 1, Berlin 10117, Germany. · Interdisciplinary Center of Sleep Medicine, Department of Cardiology, Charité Universitätsmedizin Berlin, Charité Campus Mitte, Charitéplatz 1, Berlin 10117, Germany; Department of Oto-Rhino-Laryngology, Charité Universitätsmedizin Berlin, Charité Campus Mitte, Charitéplatz 1, Berlin 10117, Germany. · Interdisciplinary Center of Sleep Medicine, Department of Cardiology, Charité Universitätsmedizin Berlin, Charité Campus Mitte, Charitéplatz 1, Berlin 10117, Germany. Electronic address: thomas.penzel@charite.de. ·Sleep Med Clin · Pubmed #28118868.

ABSTRACT: Autonomic arousal at the end of sleep apnea events are not well-explored. We prospectively studied 20 patients with obstructive sleep apnea (OSA) and 24 healthy volunteers for 2 nights with cardiorespiratory polysomnography and continuous noninvasive blood pressure (Portapres). Recordings were scored visually for cortical and autonomic arousal. In the OSA group, 2151 cortical arousals and in the controls 1089 cortical arousals were scored. Respiratory arousal caused most frequently an increase of highest mean arterial blood pressure in patients and controls. A useful definition for autonomic arousal for OSA and controls based on blood pressure and heart rate analysis was developed.

10 Review Modulations of Heart Rate, ECG, and Cardio-Respiratory Coupling Observed in Polysomnography. 2016

Penzel, Thomas / Kantelhardt, Jan W / Bartsch, Ronny P / Riedl, Maik / Kraemer, Jan F / Wessel, Niels / Garcia, Carmen / Glos, Martin / Fietze, Ingo / Schöbel, Christoph. ·Interdisziplinäres Schlafmedizinisches Zentrum, Charité - Universitätsmedizin BerlinBerlin, Germany; International Clinical Research Center, St. Anne's University Hospital BrnoBrno, Czech Republic. · Naturwissenschaftliche Fakultät II - Chemie, Physik und Mathematik, Institut für Physik, Martin-Luther Universität Halle-WittenbergHalle, Germany; Kardiovaskuläre Physik, Arbeitsgruppe Nichtlineare Dynamik, Fachbereich Physik, Humboldt-Universität BerlinBerlin, Germany. · Physics Department, Bar-Ilan-University Ramat Gan, Israel. · Kardiovaskuläre Physik, Arbeitsgruppe Nichtlineare Dynamik, Fachbereich Physik, Humboldt-Universität Berlin Berlin, Germany. · Interdisziplinäres Schlafmedizinisches Zentrum, Charité - Universitätsmedizin Berlin Berlin, Germany. ·Front Physiol · Pubmed #27826247.

ABSTRACT: The cardiac component of cardio-respiratory polysomnography is covered by ECG and heart rate recordings. However, their evaluation is often underrepresented in summarizing reports. As complements to EEG, EOG, and EMG, these signals provide diagnostic information for autonomic nervous activity during sleep. This review presents major methodological developments in sleep research regarding heart rate, ECG, and cardio-respiratory couplings in a chronological (historical) sequence. It presents physiological and pathophysiological insights related to sleep medicine obtained by new technical developments. Recorded nocturnal ECG facilitates conventional heart rate variability (HRV) analysis, studies of cyclical variations of heart rate, and analysis of ECG waveform. In healthy adults, the autonomous nervous system is regulated in totally different ways during wakefulness, slow-wave sleep, and REM sleep. Analysis of beat-to-beat heart-rate variations with statistical methods enables us to estimate sleep stages based on the differences in autonomic nervous system regulation. Furthermore, up to some degree, it is possible to track transitions from wakefulness to sleep by analysis of heart-rate variations. ECG and heart rate analysis allow assessment of selected sleep disorders as well. Sleep disordered breathing can be detected reliably by studying cyclical variation of heart rate combined with respiration-modulated changes in ECG morphology (amplitude of R wave and T wave).

11 Review [Sleep apnoea syndrome in the rehabilitation setting]. 2012

Penzel, T / Fietze, I / Schöbel, C / Baumann, G. ·Interdisziplinäres Schlafmedizinisches Zentrum, CharitéCentrum für Herz- Kreislauf- und Gefässmedizin, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Deutschland. thomas.penzel@charite.de ·Herz · Pubmed #22048328.

ABSTRACT: Sleep-related breathing disorders are a common finding in patients undergoing cardiological rehabilitation. Sleep apnoea is recognized as a major risk factor for cardiovascular disorders. The diagnosis of sleep-related breathing disorders begins with taking a thorough sleep medicine-related patient history and answering dedicated questionnaires. The second step involves portable monitoring to assess oxygen saturation, heart rate, respiratory flow and effort. Portable monitoring is able to detect the severity of the breathing disorder and forms the basis on which to refer the patient for further sleep laboratory diagnosis or, in the case of positive results, to initiate appropriate treatment. In order to exclude a sleep-related breathing disorder, to distinguish between obstructive and central sleep apnoea, or to diagnose other sleep disorders a cardiorespiratory polysomnography in a sleep laboratory is required. Polysomnography is also needed if comorbidities are present. Appropriate and prompt treatment of sleep-related breathing disorders can shorten cardiological rehabilitation and improve outcomes in this patient group.

12 Clinical Trial Investigating relative respiratory effort signals during mixed sleep apnea using photoplethysmogram. 2013

Khandoker, A H / Karmakar, C K / Penzel, T / Glos, M / Palaniswami, M. ·Department of Electrical & Electronic Engineering, The University of Melbourne, Parkville, VIC 3010, Australia. ahsank@unimelb.edu.au ·Ann Biomed Eng · Pubmed #23695488.

ABSTRACT: Sleep disordered breathing does show different types of events. These are obstructive apnea events, central apnea events and mixed sleep apnea (MSA) which have a central component with a pause in airflow without respiratory effort followed by an obstructive component with respiratory effort. The esophageal pressure (Pes) is the accurate method to assess respiratory effort. The aim of the present study is to investigate whether the features extracted from photo-plethysmogram (PPG) could relate with the changes in Pes during MSA. Therefore, Pes and PPG signals during 65 pre-scored MSA events and 10 s preceding the events were collected from 8 patients. Pulse intervals (PPI), Pulse wave amplitudes (PWA) and wavelet decomposition (Wv) of PPG signals at level 8 (0.15-0.32 Hz) were derived from PPG signals. Results show that significant correlations (r = 0.63, p < 0.01; r = 0.42, p < 0.05; r = 0.8, p < 0.01 for OSA part) were found between reductions in Pes and that in PPG based surrogate respiratory signals PPI, PWA and Wv. Results suggest that PPG based relative respiratory effort signal can be considered as an alternative to Pes as a means of measuring changes in inspiratory effort when scoring OSA and CSA parts of MSA events.

13 Article Defining Extreme Phenotypes of Obstructive Sleep Apnea across International Sleep Centers. 2020

Rizzatti, Fabiola G / Mazzotti, Diego R / Mindel, Jesse / Maislin, Greg / Keenan, Brendan T / Bittencourt, Lia / Chen, Ning-Hung / Cistulli, Peter A / McArdle, Nigel / Pack, Frances M / Singh, Bhajan / Sutherland, Kate / Benediktsdottir, Bryndis / Fietze, Ingo / Gislason, Thorarinn / Lim, Diane C / Penzel, Thomas / Sanner, Bernd / Han, Fang / Li, Qing Yun / Schwab, Richard / Tufik, Sergio / Pack, Allan I / Magalang, Ulysses J. ·Departamento de Psicobiologia, Universidade Federal de São Paulo; Departamento de Medicina, Universidade Federal de São Carlos, São Paulo, Brazil. · Center for Sleep and Circadian Neurobiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States. · Division of Pulmonary, Critical Care, and Sleep Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, United States. · Departamento de Psicobiologia, Universidade Federal de São Paulo. · Division of Pulmonary, Critical Care Medicine and Sleep Medicine, Chang Gung Memorial Hospital, Taoyuan City, Taiwan. · Charles Perkins Centre, Faculty of Medicine and Health, University of Sydney; Department of Respiratory and Sleep Medicine, Royal North Shore Hospital Sydney, Australia. · West Australian Sleep Disorders Research Institute, Sir Charles Gairdner Hospital, Nedlands, Australia. · Department of Sleep Medicine, Landspitali University Hospital; Medical Faculty, University of Iceland, Reykjavik, Iceland. · Interdisciplinary Center of Sleep Medicine, Charité University Hospital, Berlin, Germany. · Department of Pulmonary Medicine, Agaplesion Bethesda Krankenhaus Wuppertal, Wuppertal, Germany. · Department of Respiratory Medicine, Peking University, Beijing, China. · Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. · Division of Pulmonary, Critical Care, and Sleep Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, United States; Neuroscience Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, United States. Electronic address: ulysses.magalang@osumc.edu. ·Chest · Pubmed #32304773.

ABSTRACT: BACKGROUND: We developed objective definitions of extreme phenotypes of obstructive sleep apnea (OSA) using a multivariate approach, and demonstrate their utility for identifying characteristics that confer predisposition towards or protection against OSA in a new prospective sample. METHODS: In a large international sample, we calculated race-specific liability scores from a weighted logistic regression including age, gender and body mass index (BMI). Extreme Cases were defined as individuals with an apnea-hypopnea index (AHI) ≥30 events/hour, but low likelihood of OSA based on age, gender and BMI (liability scores >90th percentile). Similarly, Extreme Controls were individuals with AHI<5, but high likelihood of OSA (liability scores <10th percentile). Definitions were applied to a prospective sample from the Sleep Apnea Global Interdisciplinary Consortium (SAGIC) and differences in photography-based craniofacial and intraoral phenotypes evaluated. RESULTS: Retrospective data included 81,338 individuals. We identified 4,168 Extreme Cases and 1,432 Extreme Controls using liability scores. Extreme Cases were younger (43.1±14.7 years), overweight (28.6±6.8 kg/m CONCLUSIONS: This objective definition can be applied in sleep centers throughout the world to consistently define OSA extreme phenotypes for future studies on genetic, anatomic and physiological pathways to OSA.

14 Article Detecting central sleep apnea in adult patients using WatchPAT-a multicenter validation study. 2020

Pillar, Giora / Berall, Murray / Berry, Richard / Etzioni, Tamar / Shrater, Noam / Hwang, Dennis / Ibrahim, Marai / Litman, Efrat / Manthena, Prasanth / Koren-Morag, Nira / Rama, Anil / Schnall, Robert P / Sheffy, Koby / Spiegel, Rebecca / Tauman, Riva / Penzel, Thomas. ·Technion Faculty of Medicine, Sleep Laboratory, Carmel Medical Center, Haifa, Israel. gpillar@technion.ac.il. · Center of Sleep and Chronobiology, Toronto, ON, Canada. · Health Sleep center, University of Florida, Gainesville, FL, USA. · Technion Faculty of Medicine, Sleep Laboratory, Carmel Medical Center, Haifa, Israel. · Cardiology Department, Soroka Medical Center, Be'er Sheva, Israel. · Kaiser Permanente Fontana Medical Center, Fontana, CA, USA. · Cardiology Department, Rambam Medical Center, Haifa, Israel. · Itamar Medical, Caesarea, Israel. · Sleep clinic, Kaiser Permanente Los Angeles Medical Center, Los Angeles, CA, USA. · Sackler School of Medicine, Tel Aviv University, Tel Aviv-Yafo, Israel. · Kaiser Permanente San Jose Medical Center, San Jose, CA, USA. · Stony Brook University Hospital, Stony Brook, NY, USA. · Sleep Disorders Center, Tel Aviv Souraski Medical Center, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel. · Charite Universitätsmedizin Berlin, Berlin, Germany. ·Sleep Breath · Pubmed #31402439.

ABSTRACT: STUDY OBJECTIVES: To assess the accuracy of WatchPAT (WP-Itamar-Medical, Caesarea, Israel) enhanced with a novel systolic upstroke analysis coupled with respiratory movement analysis derived from a dedicated snoring and body position (SBP) sensor, to enable automated algorithmic differentiation between central sleep apnea (CSA) and obstructive sleep apnea (OSA) compared with simultaneous in-lab sleep studies with polysomnography (PSG). METHODS: Eighty-four patients with suspected sleep-disordered breathing (SDB) underwent simultaneous WP and PSG studies in 11 sleep centers. PSG scoring was blinded to the automatically analyzed WP data. RESULTS: Overall WP apnea-hypopnea index (AHI; mean ± SD) was 25.2 ± 21.3 (range 0.2-101) versus PSG AHI 24.4 ± 21.2 (range 0-110) (p = 0.514), and correlation was 0.87 (p < 0.001). Using a threshold of AHI ≥ 15, the sensitivity and specificity of WP versus PSG for diagnosing sleep apnea were 85% and 70% respectively and agreement was 79% (kappa = 0.867). WP central AHI (AHIc) was 4.2 ± 7.7 (range 0-38) versus PSG AHIc 5.9 ± 11.8 (range 0-63) (p = 0.034), while correlation was 0.90 (p < 0.001). Using a threshold of AHI ≥ 15, the sensitivity and specificity of WP versus PSG for diagnosing CSA were 67% and 100% respectively with agreement of 95% (kappa = 0.774), and receiver operator characteristic (ROC) area under the curve of 0.866, (p < 0.01). Using a threshold of AHI ≥ 10 showed comparable overall sleep apnea and CSA diagnostic accuracies. CONCLUSIONS: These findings show that WP can accurately detect overall AHI and effectively differentiate between CSA and OSA.

15 Article Unique sleep-stage transitions determined by obstructive sleep apnea severity, age and gender. 2020

Wächter, Marcel / Kantelhardt, Jan W / Bonsignore, Maria R / Bouloukaki, Izolde / Escourrou, Pierre / Fietze, Ingo / Grote, Ludger / Korzybski, Damian / Lombardi, Carolina / Marrone, Oreste / Paranicova, Ivana / Pataka, Athanasia / Ryan, Silke / Schiza, Sophia E / Sliwinski, Pawel / Steiropoulos, Paschalis / Verbraecken, Johan / Penzel, Thomas / Anonymous1871127. ·Schlafmedizinisches Zentrum, Charité-Universitätsmedizin Berlin, Berlin, Germany. · Institut für Physik, Martin-Luther-Universität Halle-Wittenberg, Halle, Germany. · PROMISE Department, University of Palermo, and National Research Council, IBIM, Palermo, Palermo, Italy. · Medical School, University of Crete, Heraklion, Greece. · Hopital Antoine Beclere, Paris, France. · Sleep Medicine Center, Sahlgrenska University Hospital, Gothenborg, Sweden. · 2nd Department of Respiratory Medicine, Institute of Tuberculosis and Lung Diseases, Warsaw, Poland. · Istituto Auxologico Italiano, IRCCS-Milano Bicocca University, Milano, Italy. · University Hospital Kosice, Kosice, Slovakia. · Aristotle University of Thessaloniki, Thessaloniki, Greece. · University College Dublin, Dublin, Ireland. · Medical School, Democritus University of Thrace, University Hospital of Alexandroupolis, Alexandroupolis, Greece. · Antwerp University Hospital and University of Antwerp, Antwerp, Belgium. ·J Sleep Res · Pubmed #31347213.

ABSTRACT: In obstructive sleep apnea, patients' sleep is fragmented leading to excessive daytime sleepiness and co-morbidities like arterial hypertension. However, traditional metrics are not always directly correlated with daytime sleepiness, and the association between traditional sleep quality metrics like sleep duration and arterial hypertension is still ambiguous. In a development cohort, we analysed hypnograms from mild (n = 209), moderate (n = 222) and severe (n = 272) obstructive sleep apnea patients as well as healthy controls (n = 105) from the European Sleep Apnea Database. We assessed sleep by the analysis of two-step transitions depending on obstructive sleep apnea severity and anthropometric factors. Two-step transition patterns were examined for an association to arterial hypertension or daytime sleepiness. We also tested cumulative distributions of wake as well as sleep-states for power-laws (exponent α) and exponential distributions (decay time τ) in dependency on obstructive sleep apnea severity and potential confounders. Independent of obstructive sleep apnea severity and potential confounders, wake-state durations followed a power-law distribution, while sleep-state durations were characterized by an exponential distribution. Sleep-stage transitions are influenced by obstructive sleep apnea severity, age and gender. N2 → N3 → wake transitions were associated with high diastolic blood pressure. We observed higher frequencies of alternating (symmetric) patterns (e.g. N2 → N1 → N2, N2 → wake → N2) in sleepy patients both in the development cohort and in a validation cohort (n = 425). In conclusion, effects of obstructive sleep apnea severity and potential confounders on sleep architecture are small, but transition patterns still link sleep fragmentation directly to obstructive sleep apnea-related clinical outcomes like arterial hypertension and daytime sleepiness.

16 Article The prediction of obstructive sleep apnea severity based on anthropometric and Mallampati indices. 2019

Amra, Babak / Pirpiran, Mohsen / Soltaninejad, Forogh / Penzel, Thomas / Fietze, Ingo / Schoebel, Christoph. ·Bamdad Respiratory and Sleep Research Center, Isfahan University of Medical Sciences, Isfahan, Iran. · Department of Internal Medicine, Isfahan University of Medical Sciences, Isfahan, Iran. · Center of Sleep Medicine, Charité - Berlin University of Medicine, Berlin, Germany. · Department of Cardiology and Pulmonology, Center of Sleep Medicine, Charité - Berlin University of Medicine, Berlin, Germany. · Department of Cardiology and Angiology, Center of Sleep Medicine, Charité - Berlin University of Medicine, Berlin, Germany. ·J Res Med Sci · Pubmed #31523252.

ABSTRACT: Background: Obstructive sleep apnea (OSA) is a common health issue with serious complications. Regarding the high cost of the polysomnography (PSG), sensitive and inexpensive screening tools are necessary. The objective of this study was to evaluate the predictive value of anthropometric and Mallampati indices for OSA severity in both genders. Materials and Methods: In a cross-sectional study, we evaluated anthropometric data and the Mallampati classification for the patients ( Results: About 54.1% of the patients were male. Mallampati, age, and NCs are important factors in predicting moderate OSA. The likelihood of moderate OSA severity based on Model 1 was 94.16%. In severe OSA, Mallampati, BMI, age, AC, and gender are more predictive. In Model 2, gender had a significant role. The likelihood of severe OSA based on Model 2 in female patients was 89.98% and in male patients was 90.32%. Comparison of the sensitivity and specificity of both models showed a higher sensitivity of Model 1 (93.5%) and a higher specificity of Model 2 (89.66%). Conclusion: For the prediction of moderate and severe OSA, anthropometric and Mallampati indices are important factors.

17 Article A comparison between auto-scored apnea-hypopnea index and oxygen desaturation index in the characterization of positional obstructive sleep apnea. 2019

Levendowski, Daniel J / Hamilton, Garun S / St Louis, Erik K / Penzel, Thomas / Dawson, David / Westbrook, Philip R. ·Advanced Brain Monitoring, Inc. , Carlsbad, CA, USA. · Monash Health & School of Clinical Sciences, Monash University, Clayton, VIC, Australia. · Center for Sleep Medicine, Departments of Neurology and Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA. · Sleep Medicine Center, Charité Universitätsmedizin Berlin, GmbH, Berlin, Germany. · Department of Anesthesiology, Bradford Teaching Hospitals NHS Foundation Trust, West Yorkshire, UK. ·Nat Sci Sleep · Pubmed #31372075.

ABSTRACT: Objective: Evaluate the concordance between overall and positional oxygen desaturation indices (ODI) and apnea-hypopnea indices (AHI) according to two different definitions for positional obstructive sleep apnea (POSA). Methods: A total of 184 in-home polysomnograms were edited to simulate Level III home sleep apnea tests (HSAT) with the auto-scored AHI and ODI based on recording time. POSA was determined using 132 records with an AHI≥5 and at least 20 mins of recording time in both supine and non-supine positions. POSA was defined independently for the AHI and ODI based on ratios of overall/non-supine event/h ≥1.4 (O/NS) and supine/non-supine event/h≥2.0 (S/NS). Results: Correlation between the AHI and ODI was 0.97 overall, 0.94 for supine, and 0.96 for non-supine recording times (all Conclusions: Auto-scored positional oximetry is a clinically viable alternative to an auto-scored Level III HSAT AHI in the characterization of POSA based on a 3% desaturation.

18 Article A Global Comparison of Anatomic Risk Factors and Their Relationship to Obstructive Sleep Apnea Severity in Clinical Samples. 2019

Sutherland, Kate / Keenan, Brendan T / Bittencourt, Lia / Chen, Ning-Hung / Gislason, Thorarinn / Leinwand, Sarah / Magalang, Ulysses J / Maislin, Greg / Mazzotti, Diego R / McArdle, Nigel / Mindel, Jesse / Pack, Allan I / Penzel, Thomas / Singh, Bhajan / Tufik, Sergio / Schwab, Richard J / Cistulli, Peter A / Anonymous1801168. ·Department of Respiratory and Sleep Medicine, Royal North Shore Hospital, Sydney, New South Wales, Australia. · Charles Perkins Centre, Sydney Medical School, University of Sydney, Sydney, Australia. · Center for Sleep and Circadian Neurobiology, University of Pennsylvania, Philadelphia, Pennsylvania. · Disciplilna de Medicina e Biologia do Sono, Departamento de Psicobiologia, Universidade Federal de Sao Paulo, Sao Paulo, Brazil. · Sleep Center, Department of Pulmonary and Critical Care Medicine; Chang Gung Memorial Hospital, Taoyuan, Taiwan. · Department of Respiratory Medicine and Sleep, Landspitali -The National University Hospital of Iceland and Faculty of Medicine, University of Iceland, Reykjavik, Iceland. · Division of Pulmonary, Critical Care, and Sleep Medicine, The Ohio State Wexner Medical Center, Columbus, Ohio. · Division of Sleep Medicine, Perelman School of Medicine at the University of Pennsylvania. · West Australian Sleep Disorders Research Institute; Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital; University of Western Australia, Perth, Western Australia, Australia. · Center of Sleep Medicine, Charité University Hospital, Berlin, Germany. ·J Clin Sleep Med · Pubmed #30952214.

ABSTRACT: STUDY OBJECTIVES: Obstructive sleep apnea (OSA) is a global health issue and is associated with obesity and oropharyngeal crowding. Global data are limited on the effect of ethnicity and sex on these relationships. We compare associations between the apnea-hypopnea index (AHI) and these risk factors across ethnicities and sexes within sleep clinics. METHODS: This is a cross-sectional, multicenter study of patients with OSA from eight sleep centers representing the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Four distinct ethnic groups were analyzed, using a structured questionnaire: Caucasians (Australia, Iceland, Germany, United States), African Americans (United States), Asians (Taiwan), and South Americans (Brazil). Regression analyses and interaction tests were used to assess ethnic and sex differences in relationships between AHI and anthropometric measures (body mass index [BMI], neck circumference, waist circumference) or Mallampati score. RESULTS: Analyses included 1,585 individuals from four ethnic groups: Caucasian (60.6%), African American (17.5%), Asian (13.1%), and South American (8.9%). BMI was most strongly associated with AHI in South Americans (7.8% increase in AHI per 1 kg/m CONCLUSIONS: We demonstrate ethnic and sex variations in associations between obesity and OSA. For similar BMI increases, South American patients show greatest AHI increases compared to African Americans. Findings highlight the importance of considering ethnicity and sex in clinical assessments of OSA risk.

19 Article Comparison of Apnea Detection Using Oronasal Thermal Airflow Sensor, Nasal Pressure Transducer, Respiratory Inductance Plethysmography and Tracheal Sound Sensor. 2019

Sabil, AbdelKebir / Glos, Martin / Günther, Alexandra / Schöbel, Christoph / Veauthier, Christian / Fietze, Ingo / Penzel, Thomas. ·Research and Development at CIDELEC, Sainte Gemmes, France. · Interdisciplinary Sleep Medicine Center, Charité - Universitätsmedizin Berlin, Berlin, Germany. · International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic. ·J Clin Sleep Med · Pubmed #30736876.

ABSTRACT: STUDY OBJECTIVES: Evaluation of apnea detection using a tracheal sound (TS) sensor during sleep in patients with obstructive sleep apnea. METHODS: Polysomnographic recordings of 32 patients (25 male, mean age 66.7 ± 15.3 years, and mean body mass index 30.1 ± 4.5 kg/m RESULTS: The number of apneas detected by the thermistor was 4,167. The number of apneas detected using the NP was 5,416 (+29.97%), using the RIPsum was 2,959 (-29.71%) and using the TS was 5,019 (+20.45%). The kappa statistics (95% confidence interval) were 0.72 (0.71 to 0.74) for TS, 0.69 (0.67 to 0.70) for NP, and 0.57 (0.55 to 0.59) for RIPsum. The sensitivity/specificity (%) with respect to the thermistor were 99.23/69.27, 64.07/93.06 and 96.06/76.07 for the NP, RIPsum and TS respectively. CONCLUSIONS: With the sensor placed properly on the suprasternal notch, tracheal sounds could help detecting apneas that are underscored by the RIPsum and identify apneas that may be overscored by the NP sensor due to mouth breathing. In the absence of thermistor, TS sensors can be used for apnea detection. CLINICAL TRIAL REGISTRATION: Registry: German Clinical Trials Register (DRKS), Title: Using the tracheal sound probe of the polygraph CID102 to detect and differentiate obstructive, central, and mixed sleep apneas in patients with sleep disordered breathing, Identifier: DRKS00012795, URL: https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00012795.

20 Article Apnea and hypopnea characterization using esophageal pressure, respiratory inductance plethysmography, and suprasternal pressure: a comparative study. 2019

Sabil, AbdelKebir / Schöbel, Christoph / Glos, Martin / Gunther, Alexandra / Veauthier, Christian / Arens, Philipp / Fietze, Ingo / Penzel, Thomas. ·Research and Development at CIDELEC, Sainte Gemmes, France. Kebir.sabil@cloudsleeplab.com. · Interdisciplinary Sleep Medicine Center, Charité - Universitätsmedizin Berlin, Berlin, Germany. · International Clinical Research Center, Saint Anne's University Hospital Brno, Brno, Czech Republic. ·Sleep Breath · Pubmed #30729405.

ABSTRACT: OBJECTIVES: To determine if recording of suprasternal pressure (SSP) can classify apneas and hypopneas as reliably as respiratory inductance plethysmography (RIP) belts and to compare the two methods to classification with esophageal pressure (Pes), the reference method for assessing respiratory effort. METHODS: In addition to polysomnographic recordings that included Pes, SSP was recorded. Recordings from 32 patients (25 males, mean age 66.7 ± 15.3 years, and mean BMI 30.1 ± 4.5 kg/m RESULTS: Using Pes as a reference for apnea characterization, the Cohen kappa (κ) was 0.93 for SSP and 0.87 for the RIP. The sensitivity/specificity of SSP was 97.0%/96.9% for obstructive, 93.9%/98.3% for central, and 94.9%/97.9% for mixed apneas. The sensitivity/specificity of the RIP was 97.4%/91.9% for obstructive, 87.5%/97.9% for central, and 85.6%/96.6% for mixed apneas. For hypopnea characterization using the Pes as a reference, κ was 0.92 for SSP and 0.86 for the RIP. The sensitivity/specificity of SSP was 99.7%/97.6% for obstructive and 97.6%/99.7% for central. The sensitivity/specificity of the RIP was 99.8%/81.1% for obstructive and 81.1%/99.8% for central. CONCLUSIONS: These results confirm the excellent agreement in the detection of respiratory effort between SSP, RIP belts, and Pes signals. Thus, we conclude that apnea and hypopnea characterization in adults with SSP is a reliable method.

21 Article Screening for Obstructive Sleep Apnea in Commercial Drivers Using EKG-Derived Respiratory Power Index. 2019

Lyons, M Melani / Kraemer, Jan F / Dhingra, Radha / Keenan, Brendan T / Wessel, Niels / Glos, Martin / Penzel, Thomas / Gurubhagavatula, Indira. ·Center for Sleep and Circadian Neurobiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania. · Department of Physics, Humboldt-Universitat zu Berlin, Berlin, Germany. · Mahatma Gandhi Medical College and Hospital, Jaipur, India. · The Centre of Sleep Medicine, Department of Cardiology, Charité Universitätsmedizin, Berlin, Berlin, Germany. · Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania. · Sleep Disorders Clinic at the Philadelphia CMC VA Medical Center, Philadelphia, Pennsylvania. ·J Clin Sleep Med · Pubmed #30621825.

ABSTRACT: STUDY OBJECTIVES: Obstructive sleep apnea (OSA) is common in commercial motor vehicle operators (CMVOs); however, polysomnography (PSG), the gold-standard diagnostic test, is expensive and inconvenient for screening. OSA is associated with changes in heart rate and voltage on electrocardiography (EKG). We evaluated the utility of EKG parameters in identifying CMVOs at greater risk for sleepiness-related crashes (apnea-hypopnea index [AHI] ≥ 30 events/h). METHODS: In this prospective study of CMVOs, we performed EKGs with concurrent PSG, and calculated the respiratory power index (RPI) on EKG, a surrogate for AHI calculated from PSG. We evaluated the utility of two-stage predictive models using simple clinical measures (age, body mass index [BMI], neck circumference, Epworth Sleepiness Scale score, and the Multi-Variable Apnea Prediction [MVAP] score) in the first stage, followed by RPI in a subset as the second-stage. We assessed area under the receiver operating characteristic curve (AUC), sensitivity, and negative posttest probability (NPTP) for this two-stage approach and for RPI alone. RESULTS: The best-performing model used the MVAP, which combines BMI, age, and sex with three OSA symptoms, in the first stage, followed by RPI in the second. The model yielded an estimated (95% confidence interval) AUC of 0.883 (0.767-0.924), sensitivity of 0.917 (0.706-0.962), and NPTP of 0.034 (0.015-0.133). Predictive characteristics were similar using a model with only BMI as the first-stage screen. CONCLUSIONS: A two-stage model that combines BMI or the MVAP score in the first stage, with EKG in the second, had robust discriminatory power to identify severe OSA in CMVOs.

22 Article Nocturnal ventricular repolarization lability predicts cardiovascular mortality in the Sleep Heart Health Study. 2019

Schmidt, Martin / Baumert, Mathias / Penzel, Thomas / Malberg, Hagen / Zaunseder, Sebastian. ·Institute of Biomedical Engineering, TU Dresden, Dresden , Germany. · Centre For Heart Rhythm Disorders, University of Adelaide and Royal Adelaide Hospital , Adelaide, South Australia , Australia. · Center for Sleep Medicine, Charité-Universitätsmedizin Berlin, Berlin , Germany. ·Am J Physiol Heart Circ Physiol · Pubmed #30550351.

ABSTRACT: The objective of the present study was to quantify repolarization lability and its association with sex, sleep stage, and cardiovascular mortality. We analyzed polysomnographic recordings of 2,263 participants enrolled in the Sleep Heart Health Study (SHHS-2). Beat-to-beat QT interval variability (QTV) was quantified for consecutive epochs of 5 min according to the dominant sleep stage [wakefulness, nonrapid eye movement stage 2 (NREM2), nonrapid eye movement stage 3 (NREM3), and rapid eye movement (REM)]. To explore the effect of sleep stage and apnea-hypopnea index (AHI) on QT interval parameters, we used a general linear mixed model and mixed ANOVA. The Cox proportional hazards model was used for cardiovascular disease (CVD) death prediction. Sex-related differences in T wave amplitude ( P < 0.001) resulted in artificial QTV differences. Hence, we corrected QTV parameters by T wave amplitude for further analysis. Sleep stages showed a significant effect ( P < 0.001) on QTV. QTV was decreased in deep sleep compared with wakefulness, was higher in REM than in NREM, and showed a distinct relation to AHI in all sleep stages. The T wave amplitude-corrected QTV index (cQTVi) in REM sleep was predictive of CVD death (hazard ratio: 2.067, 95% confidence interval: 1.105-3.867, P < 0.05) in a proportional hazards model. We demonstrated a significant impact of sleep stages on ventricular repolarization variability. Sex differences in QTV are due to differences in T wave amplitude, which should be corrected for. Independent characteristics of QTV measures to sleep stages and AHI showed different behaviors of heart rate variability and QTV expressed as cQTVi. cQTVi during REM sleep predicts CVD death. NEW & NOTEWORTHY We demonstrate here, for the first time, a significant impact of sleep stages on ventricular repolarization variability, quantified as QT interval variability (QTV). We showed that QTV is increased in rapid eye movement sleep, reflective of high sympathetic drive, and predicts death from cardiovascular disease. Sex-related differences in QTV are shown to be owing to differences in T wave amplitude, which should be corrected for.

23 Article Time domain characterization for sleep apnea in oronasal airflow signal: a dynamic threshold classification approach. 2019

Kim, Jungyoon / ElMoaqet, Hisham / Tilbury, Dawn M / Ramachandran, Satya Krishna / Penzel, Thomas. ·Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48105, United States of America. Department of Computer Science, Kent State University, Kent, OH 44242, United States of America. ·Physiol Meas · Pubmed #30524019.

ABSTRACT: OBJECTIVE: Apneas are the most common type of sleep-related breathing disorders; they cause patients to move from restorative sleep into inefficient sleep. The American Academy of Sleep Medicine (AASM) considers sleep apnea as a hidden health crisis that affects 29.4 million adults, costing the USA billions of dollars. Traditional detection methods of sleep apnea are achieved by human observation of the respiration signals. This introduces limitations in terms of access and efficiency of diagnostic sleep studies. However, alternative device technologies have limited diagnostic accuracy for detecting apnea events although many of the previous investigational algorithms are based on multiple physiological channel inputs. Guided by the AASM recommendations for sleep apnea diagnostics, this paper investigates time domain metrics to characterize changes in oronasal airflow respiration signals during the occurrence of apneic events. APPROACH: A new algorithm is developed to derive a respiratory baseline from the oronasal airflow signal in order to detect sleep apnea events using a dynamically adjusted threshold classification approach. To demonstrate our results, we use polysomnography data of [Formula: see text] patients with different apnea severity levels as reflected by their overnight apnea hypopnea index (AHI), including patients with mild apnea (5 [Formula: see text] AHI [Formula: see text]), moderate apnea ([Formula: see text] AHI [Formula: see text]), and severe apnea (AHI [Formula: see text]). MAIN RESULTS: Our results indicate the ability to characterize sleep apnea events in oronasal airflow signals using the proposed dynamic threshold classification approach. Overall, the new algorithm achieved a sensitivity of 80.0%, specificity of 88.7%, and an area under receiver operating characteristics curve of 0.844. SIGNIFICANCE: The present results contribute a new approach for progressive detection of sleep apnea using an adaptive threshold that is dynamically adjusted with respect to the patient's respiration baseline, making it potentially able to effectively generalize over patients with different apnea severity levels and longer monitoring periods.

24 Article Prevalence and association analysis of obstructive sleep apnea with gender and age differences - Results of SHIP-Trend. 2019

Fietze, Ingo / Laharnar, Naima / Obst, Anne / Ewert, Ralf / Felix, Stephan B / Garcia, Carmen / Gläser, Sven / Glos, Martin / Schmidt, Carsten Oliver / Stubbe, Beate / Völzke, Henry / Zimmermann, Sandra / Penzel, Thomas. ·Department of Cardiology and Angiology, Interdisciplinary Center of Sleep Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany. · Department of Internal Medicine B, Cardiology, Pneumology, Weaning, Infectious Diseases, Intensive Care Medicine, University Hospital Greifswald, Greifswald, Germany. · Department of Internal Medicine, Pneumology, Vivantes Hospital Berlin Spandau, Berlin, Germany. · Institute for Community Medicine, SHIP/Clinical Epidemiology Research, University Hospital Greifswald, Greifswald, Germany. ·J Sleep Res · Pubmed #30272383.

ABSTRACT: Identification of obstructive sleep apnea and risk factors is important for reduction in symptoms and cardiovascular risk, and for improvement of quality of life. The population-based Study of Health in Pomerania investigated risk factors and clinical diseases in a general population of northeast Germany. Additional polysomnography was applied to measure sleep and respiration with the objective of assessing prevalence and risk factors of obstructive sleep apnea in a German cohort. One-thousand, two-hundred and eight people between 20 and 81 years old (54% men, median age 54 years) underwent overnight polysomnography. The estimated obstructive sleep apnea prevalence was 46% (59% men, 33% women) for an apnea-hypopnea index ≥5%, and 21% (30% men, 13% women) for an apnea-hypopnea index ≥ 15. The estimated obstructive sleep apnea syndrome prevalence (apnea-hypopnea index ≥5; Epworth Sleepiness Scale >10) was 6%. The prevalence of obstructive sleep apnea continuously increased with age for men and women with, however, later onset for women. Gender, age, body mass index, waist-to-hip ratio, snoring, alcohol consumption (for women only) and self-reported cardiovascular diseases were significantly positively associated with obstructive sleep apnea, whereas daytime sleepiness was not. Diabetes, hypertension and metabolic syndrome were positively associated with severe obstructive sleep apnea. The associations became non-significant after adjustment for body mass. Women exhibited stronger associations than men. The prevalence of obstructive sleep apnea was high, with almost half the population presenting some kind of obstructive sleep apnea. The continuous increase of obstructive sleep apnea with age challenges the current theory that mortality due to obstructive sleep apnea and cardiovascular co-morbidities affect obstructive sleep apnea prevalence at an advanced age. Also, gender differences regarding obstructive sleep apnea and associations are significant for recognizing obstructive sleep apnea mechanisms and therapy responsiveness.

25 Article Home sleep apnea testing: comparison of manual and automated scoring across international sleep centers. 2019

Magalang, Ulysses J / Johns, Jennica N / Wood, Katherine A / Mindel, Jesse W / Lim, Diane C / Bittencourt, Lia R / Chen, Ning-Hung / Cistulli, Peter A / Gíslason, Thorarinn / Arnardottir, Erna S / Penzel, Thomas / Tufik, Sergio / Pack, Allan I. ·Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, The Ohio State University Wexner Medical Center, 201 Davis Heart and Lung Research Institute, 473 West 12th Avenue, Columbus, OH, 43210, USA. ulysses.magalang@osumc.edu. · Neuroscience Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA. ulysses.magalang@osumc.edu. · Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, The Ohio State University Wexner Medical Center, 201 Davis Heart and Lung Research Institute, 473 West 12th Avenue, Columbus, OH, 43210, USA. · Center for Sleep and Circadian Neurobiology, Division of Sleep Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. · Departamento de Psicobiologia, Universidade Federal de São Paulo, São Paulo, Brazil. · Division of Pulmonary, Critical Care, and Sleep Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan. · Charles Perkins Centre, University of Sydney, Camperdown, Australia. · Department of Respiratory and Sleep Medicine, Royal North Shore Hospital, Sydney, Australia. · Department of Sleep Medicine, Landspitali University Hospital, Reykjavik, Iceland. · Medical Faculty, University of Iceland, Reykjavik, Iceland. · Interdisciplinary Center of Sleep Medicine, Charité University Hospital, Berlin, Germany. ·Sleep Breath · Pubmed #30203176.

ABSTRACT: PURPOSE: To determine the agreement between the manual scoring of home sleep apnea tests (HSATs) by international sleep technologists and automated scoring systems. METHODS: Fifteen HSATs, previously recorded using a type 3 monitor, were saved in European Data Format. The studies were scored by nine experienced technologists from the sleep centers of the Sleep Apnea Global Interdisciplinary Consortium (SAGIC) using the locally available software. Each study was scored separately by human scorers using the nasal pressure (NP), flow derived from the NP signal (transformed NP), or respiratory inductive plethysmography (RIP) flow. The same procedure was followed using two automated scoring systems: Remlogic (RLG) and Noxturnal (NOX). RESULTS: The intra-class correlation coefficients (ICCs) of the apnea-hypopnea index (AHI) scoring using the NP, transformed NP, and RIP flow were 0.96 [95% CI 0.93-0.99], 0.98 [0.96-0.99], and 0.97 [0.95-0.99], respectively. Using the NP signal, the mean differences in AHI between the average of the manual scoring and the automated systems were - 0.9 ± 3.1/h (AHI CONCLUSIONS: There is very strong agreement in the scoring of the AHI for HSATs between the automated systems and experienced international technologists. Automated scoring of HSATs using commercially available software may be useful to standardize scoring in future endeavors involving international sleep centers.

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