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Yan Wang,1 Thomas Penzel,1 Matthew Salanitro,1 Philipp Arens2 1Interdisciplinary Sleep Medicine Center Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universitätzu Berlin, Berlin, Germany; 2Department of Otorhinolaryngology, Campus Virchow Klinikum Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, GermanyCorrespondence: Philipp Arens, Department of Otorhinolaryngology, Campus Virchow Klinikum Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany, Email philipp.arens@charite.dePurpose: Since 2001, hypoglossal nerve stimulators (HNS) have been used worldwide to treat patients with obstructive sleep apnea (OSA). Recently, a few studies reported treatment-emergent central sleep apnea (TECSA) with spontaneous resolution following HNS. However, the evidence of persistent development of TECSA during long-term care visits was lacking. As a result, this study first report two patients with persistent TECSA and describe their development phenotype during more than two years of follow-up visits to help explore the influencing factors and underlying mechanisms.Patients and Methods: This retrospective study included twenty-seven patients who underwent HNS implantation from 2016 to 2021. Their demographic data, pre- and postoperative sleep study characteristics, and device use settings were collected. The possible factors associated with post-operative elevated CSA (central apnea index ≥ 5) were evaluated. Moreover, the development phenotype of the TECSA was observed and followed up with a titration trial study.Results: Among overall 27 patients with OSA, 3 patients with an increased preoperative Epworth Sleepiness Score (ESS) got an elevated CSA (CAI ≥ 5). Two of these 3 patients developed a persistent TECSA with a significant negative correlation between obstructive apnea index (OAI) and central and mixed sleep apnea index (CMAI) (R = − 0.745, P = 0.021). These development phenotypes might be associated with different stimulation amplitudes of the HNS device. Furthermore, the following titration trial study also suggested that different amplitudes would influence the development of TECSA following HNS.Conclusion: OSA patients with severe daytime sleepiness are more likely to have elevated CSA following HNS. An inappropriate stimulation amplitude might influence the development course of TECSA in such patients.Keywords: hypoglossal nerve stimulation, obstructive sleep apnea, treatment-emergent central sleep apnea, stimulation amplitude, daytime sleepiness

Rui Zhao,1 Jianbo Xue,1 Xueli Zhang,1 Maohuan Peng,1 Jing Li,1 Bing Zhou,1 Long Zhao,1 Thomas Penzel,2 Meir Kryger,3 Xiao Song Dong,1 Zhancheng Gao,1 Fang Han1 1Department of Pulmonary and Critical Care Medicine, Peking University People’s Hospital, Beijing, People’s Republic of China; 2Sleep Medicine Center, Charité-Universitätsmedizin, Berlin, Germany; 3Division of Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USACorrespondence: Xiao Song Dong; Zhancheng Gao, Department of Pulmonary and Critical Care Medicine, Peking University People’s Hospital, No. 11 Xizhimen Nandajie, Xicheng District, Beijing, 100044, People’s Republic of China, Email dongxiaosong@pkuph.edu.cn; zcgao@bjmu.edu.cnObjective: A novel ring-worn oximeter (Circul) uses reflective photoplethysmography and automated signal processing to calculate oxygen desaturations. We evaluated the ability of Circul to detect obstructive sleep apnea in Chinese adults.Methods: We recruited 207 Chinese Han subjects: 70% males, mean age 48.2± 14.7 years, mean BMI 27.6± 4.8 kg/m2 and mean AHI 28.6± 25.2 events/h. All participants underwent simultaneous polysomnography (PSG) and Circul testing in a sleep laboratory. Oxygen desaturation index (ODI), mean oxygen saturation (MSpO2), cumulative time at SpO2< 90% (CT90), cumulative percentage of sleep time spent with SpO2< 90% (CT90/TST) were derived and compared for the Circul and the PSG.Results: The ODI was 25.3± 24.5 events/h using PSG and 22.2± 24.5 events/h using Circul (P< 0.0001), with an intraclass correlation coefficient (ICC) of 0.884. CT90 and CT90/TST between the two methods were not different; the MSpO2 level calculated by PSG was slightly lower than Circul, 95.0% (93.0– 96.0%) vs 95.3% (93.9– 96.6%), P< 0.0001. Circul-ODI had a good correlation (r=0.91, p< 0.0001) and close agreement with PSG-AHI (Bland-Altman analysis: Mean Difference 6.4, 95% CI − 14.8 to 27.5 events/h). Using a threshold of AHI ≥ 5 events/h, the Circul had 87% sensitivity, 83% specificity, 5.09 positive likelihood ratio (LR+), 86% accuracy, and 0.929 area under the curve (AUC).Conclusion: Circul ring pulse oximetry can detect OSA with reasonable reliability. The Circul system is a reliable and comfortable choice for OSA assessment.Keywords: obstructive sleep apnea, reflective photoplethysmography, pulse oximetry, polysomnography

Brigitte Holzinger,1,2 Franziska Nierwetberg,1 Frances Chung,3 Courtney J Bolstad,4 Bjørn Bjorvatn,5 Ngan Yin Chan,6 Yves Dauvilliers,7 Colin A Espie,8 Fang Han,9 Yuichi Inoue,10 Damien Leger,11 Tainá Macêdo,12 Kentaro Matsui,13,14 Ilona Merikanto,15,16 Charles M Morin,17 Sérgio A Mota-Rolim,18 Markku Partinen,19 Giuseppe Plazzi,20,21 Thomas Penzel,22 Mariusz Sieminski,23 Yun Kwok Wing,6 Serena Scarpelli,24 Michael R Nadorff,4,25 Luigi De Gennaro24,26 1Institute for Consciousness and Dream Research, Vienna, Austria; 2Medical University Vienna, Postgraduate Master ULG Sleep Coaching, Vienna, Austria; 3Department of Anesthesiology and Pain Medicine, University Health Network, University of Toronto, Toronto, ON, Canada; 4Mississippi State University, Mississippi State, MS, USA; 5Department of Global Public Health and Primary Care, University of Bergen and Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Bergen, Norway; 6Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, Special Administrative Region, People’s Republic of China; 7Sleep-Wake Disorders Unit, Department of Neurology, Gui-de-Chauliac Hospital, CHU Montpellier, INM, Univ Montpellier, INSERM, Montpellier, France; 8Sir Jules Thorn Sleep & Circadian Neuroscience Institute (SCNi), University of Oxford, Oxford, UK; 9Department of Pulmonary and Critical Care Medicine, Peking University People’s Hospital, Beijing, People’s Republic of China; 10Tokyo Medical University, Tokyo, Japan; 11Université de Paris, APHP, Hôtel-Dieu, Centre du Sommeil et de la Vigilance, Paris, France; 12Department of Psychology, Federal University of Rio Grande do Norte, Natal, Brazil; 13Department of Laboratory Medicine, National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Japan; 14Department of Psychiatry, Tokyo Women’s Medical University, Tokyo, Japan; 15SleepWell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; 16Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland; 17École de Psychologie, Centre d’étude des troubles du sommeil, Centre de recherche CERVO/Brain Research Center, Université Laval, Québec, QC, Canada; 18Brain Institute, Physiology and Behavior Department, and Onofre Lopes University Hospital - Federal University of Rio Grande do Norte, Natal, Brazil; 19Helsinki Sleep Clinic, Terveystalo Healthcare, and Department of Neurosciences, Clinicum, University of Helsinki, Helsinki, Finland; 20IRCCS, Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; 21Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; 22Sleep Medicine Center, Charité Universitätsmedizin Berlin, Berlin, Germany; 23Department of Emergency Medicine, Medical University of Gdansk, Gdansk, Poland; 24Department of Psychology, Sapienza University of Rome, Rome, Italy; 25Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA; 26IRCCS Fondazione Santa Lucia, Rome, ItalyCorrespondence: Brigitte Holzinger, Tel +43 699 101 99 042, Email brigitte.holzinger@meduniwien.ac.atPurpose: The COVID-19 pandemic affects mental health and sleep, resulting in frequent nightmares. Therefore, identifying factors associated with nightmare frequency is important, as it can indicate mental health issues. The study aimed to investigate increases in nightmare frequency comparing the pre-pandemic and pandemic period, and identify its risk factors. Further, the mediating role of post-traumatic stress disorder symptoms between the pandemic and nightmares is explored.Patients and Methods: For this cross-sectional survey data were obtained via self-rating online survey (ICOSS: details in Partinen et al, 2021), which was open to anyone older than 18 years. The final volunteer sample consisted of 15,292 participants, divided according to their nightmare frequency (high: ≥ 1– 2 nights/week; low: < 1– 2 nights/week). A total of 9100 participants were excluded if answers on variables of interest were missing or receiving rewards for participation. Chi-square tests identified changes of nightmare frequency. Predictors of high nightmare frequency were assessed using logistic regression and presented as Odds Ratios. Post-hoc mediation models were used to investigate the role of post-traumatic stress symptoms (PTSS).Results: The mean age was 41.63 (SD=16.55) with 64.05% females. High nightmare frequency increased significantly from 13.24% to 22.35% during the pandemic. Factors associated with it included self-reported PTSS (OR=2.11), other mental disorders and various sleep disorders or problems. Financial burden due to the pandemic, confinement, having had COVID-19, and work situation during the pandemic were associated with nightmare frequency, those relations were partly mediated through PTSS.Conclusion: Our results display the pandemic influence on nightmare frequency, which in turn connects to multiple mental health and sleep factors. These relations were partly mediated through PTSS. The COVID-19 pandemic appears to have caused traumatization of a substantial proportion of society. Health care workers should consider nightmares in their screening routines, as it might indicate PTSS and/or other mental and sleep disorders.Keywords: COVID-19, nightmares, mental health, sleep, post-traumatic stress disorder, collective trauma

Giora Pillar,1 Murray Berall,2 Richard B Berry,3 Tamar Etzioni,1 Yaakov Henkin,4 Dennis Hwang,5 Ibrahim Marai,6,7 Faheem Shehadeh,6 Prasanth Manthena,8 Anil Rama,9 Rebecca Spiegel,10 Thomas Penzel,11 Riva Tauman12 1Sleep Laboratory, Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel; 2Center of Sleep and Chronobiology, University of Toronto, Toronto, ON, Canada; 3UF Health Sleep Center, University of Florida, Gainesville, FL, USA; 4Cardiology Department, Soroka Medical Center, Be’er Sheva, Israel; 5Kaiser Permanente San Bernardino County Medical Center, Fontana, CA, USA; 6Cardiology Department, Rambam Medical Center, Haifa, Israel; 7Baruch Padeh Medical Center and the Azrieli Faculty of Medicine in the Galilee, Poriya, Israel; 8Sleep clinic, Kaiser Permanente Los Angeles Medical Center, Los Angeles, CA, USA; 9Sleep Clinic, Kaiser Permanente San Jose Medical Center, San Jose, CA, USA; 10Department of Neurology and Sleep Center, Stony Brook University Hospital, Stony Brook, NY, USA; 11Charite Universitätsmedizin Berlin, Sleep Medicine Center, Berlin, Germany; 12Sleep Disorders Center, Tel Aviv Sourasky Medical Center and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, IsraelCorrespondence: Giora Pillar, Sleep Laboratory, Carmel Medical Center and Technion Faculty of Medicine, Haifa, 31096, Israel, Tel +972 4 8250258, Fax +972 48250699, Email gpillar@technion.ac.ilBackground: The WatchPAT (WP) device was shown to be accurate for the diagnosis of sleep apnea and is widely used worldwide as an ambulatory diagnostic tool. While it records peripheral arterial tone (PAT) and not electrocardiogram (ECG), the ability of it to detect arrhythmias is unknown and was not studied previously. Common arrhythmias such as atrial fibrillation (AF) or premature beats may be uniquely presented while recording PAT/pulse wave.Purpose: To examine the potential detection of common arrhythmias by analyzing the PAT amplitude and pulse rate/volume changes.Patients and Methods: Patients with suspected sleep disordered breathing (SDB) were recruited with preference for patients with previously diagnosed AF or congestive heart failure (CHF). They underwent simultaneous WP and PSG studies in 11 sleep centers. A novel algorithm was developed to detect arrhythmias while measuring PAT and was tested on these patients. Manual scoring of ECG channel (recorded as part of the PSG) was blinded to the automatically analyzed WP data.Results: A total of 84 patients aged 57± 16 (54 males) participated in this study. Their BMI was 30± 5.7Kg/m2. Of them, 41 had heart failure (49%) and 17 (20%) had AF. The sensitivity and specificity of the WP to detect AF segments (of at least 60 seconds) were 0.77 and 0.99, respectively. The correlation between the WP derived detection of premature beats (events/min) to that of the PSG one was 0.98 (p< 0.001).Conclusion: The novel automatic algorithm of the WP can reasonably detect AF and premature beats. We suggest that when the algorithm raises a flag for arrhythmia, the patients should shortly undergo ECG and/or Holter ECG study.Keywords: home sleep apnea test, WatchPAT, obstructive sleep apnea, arrhythmia, atrial fibrillation

Serena Scarpelli,1 Michael R Nadorff,2,3 Bjørn Bjorvatn,4 Frances Chung,5 Yves Dauvilliers,6 Colin A Espie,7 Yuichi Inoue,8 Kentaro Matsui,9,10 Ilona Merikanto,11,12 Charles M Morin,13 Thomas Penzel,14 Mariusz Sieminski,15 Han Fang,16 Tainá Macêdo,17 Sérgio A Mota-Rolim,18 Damien Leger,19 Giuseppe Plazzi,20,21 Ngan Yin Chan,22 Markku Partinen,23 Courtney J Bolstad,2 Brigitte Holzinger,24,25 Luigi De Gennaro1,26 1Department of Psychology, Sapienza University of Rome, Rome, Italy; 2Mississippi State University, Mississippi State, MS, USA; 3Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA; 4Department of Public Health and Primary Care, University of Bergen and Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Bergen, Norway; 5Department of Anesthesiology and Pain Medicine, University Health Network, University of Toronto, Toronto, Canada; 6Sleep-Wake Disorders Unit, Department of Neurology, Gui-de-Chauliac Hospital, CHU Montpellier, INM, Univ Montpellier, INSERM, Montpellier, France; 7Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; 8Tokyo Medical University, Tokyo, Japan; 9Department of Laboratory Medicine, National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Japan; 10Department of Psychiatry, Tokyo Women’s Medical University, Tokyo, Japan; 11SleepWell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; 12Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland; 13École de Psychologie, Centre d’étude des troubles du sommeil, Centre de recherche CERVO/Brain Research Center, Université Laval, Québec, Canada; 14Sleep Medicine Center, Charité Universitätsmedizin Berlin, Berlin, Germany; 15Department of Emergency Medicine, Medical University of Gdansk, Gdansk, Poland; 16Department of Pulmonary and Critical Care Medicine, Peking University People’s Hospital, Beijing, People’s Republic of China; 17Department of Psychology, Federal University of Rio Grande do Norte, Natal, Brazil; 18Brain Institute, Physiology and Behavior Department, and Onofre Lopes University Hospital - Federal University of Rio Grande do Norte, Natal, Brazil; 19Université de Paris, APHP, Hôtel-Dieu, Centre du Sommeil et de la Vigilance, Paris, France; 20IRCCS, Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; 21Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; 22Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, Special Administrative Regions, People’s Republic of China; 23Helsinki Sleep Clinic, Terveystalo Healthcare, and Department of Neurosciences, Clinicum, University of Helsinki, Helsinki, Finland; 24Institute for Consciousness and Dream Research, Vienna, Austria; 25Medical University Vienna, Postgraduate Master Program Medical Sleep Coaching, ZK-Schlafcoaching, Vienna, Austria; 26IRCCS Fondazione Santa Lucia, Rome, ItalyCorrespondence: Luigi De Gennaro, Tel +39-06-49917647, Fax +39-06-49917711, Email luigi.degennaro@uniroma1.itIntroduction: A growing number of studies have demonstrated that the coronavirus disease-19 (COVID-19) pandemic has severely affected sleep and dream activity in healthy people. To date, no investigation has examined dream activity specifically in COVID-19 patients.Methods: As part of the International COVID-19 Sleep Study (ICOSS), we compared 544 COVID-19 participants with 544 matched-controls. A within-subjects comparison between pre-pandemic and pandemic periods computed separately for controls and COVID-19 participants were performed on dream recall and nightmare frequency (DRF; NF). Also, non-parametric comparisons between controls and COVID-19 participants were carried out. Further, we compared psychological measures between the groups collected during pandemic. Ordinal logistic regression to detect the best predictors of NF was performed.Results: We found that people reported greater dream activity during the pandemic. Comparisons between controls and COVID-19 participants revealed a) no difference between groups concerning DRF in the pre-pandemic period and during the pandemic; b) no difference between groups concerning nightmare frequency in the pre-pandemic period; and c) COVID-19 participants reported significantly higher NF than controls during pandemic (p = 0.003). Additionally, we showed that a) anxiety, depression, post-traumatic stress-disorder (PTSD) symptom scores were higher in COVID-19 participants than controls; and b) quality of life and health as well as wellbeing (WHO-5) scores were significantly higher in controls than COVID-19 participants. Finally, ordinal logistic regression indicates that DRF (p < 0.001), PTSD (p < 0.001), anxiety (p = 0.018), insomnia (p = 0.039), COVID-19 severity (p = 0.014), sleep duration (p = 0.003) and age (p = 0.001) predicted NF.Discussion: Our work shows strong associations between increased nightmares in those reporting having had COVID-19. This suggests that the more that people were affected by COVID-19, the greater the impact upon dream activity and quality of life.Keywords: dreaming, pandemic, sleep, PTSD, anxiety, COVID-19 severity

Naima Laharnar,1,&ast; Sebastian Herberger,1,&ast; Lisa-Kristin Prochnow,1 Ning-Hung Chen,2 Peter A Cistulli,3,4 Allan I Pack,5 Richard Schwab,5 Brendan T Keenan,5 Diego R Mazzotti,5,6 Ingo Fietze,1,7 Thomas Penzel1,8 1Department of Internal Medicine and Dermatology, Interdisciplinary Center of Sleep Medicine, Charité – Universitätsmedizin Berlin, Berlin, Germany; 2Department of Pulmonary and Critical Care Medicine, Sleep Center, Chang Gung Memorial Hospital, Taipei, Taiwan; 3Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia; 4Department of Respiratory Medicine, Royal North Shore Hospital, Sydney, NSW, Australia; 5Department of Medicine/Division of Sleep Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; 6Department of Internal Medicine, Division of Medical Informatics, University of Kansas Medical Center, Kansas City, KS, USA; 7The Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov, First Moscow State Medical University of the Ministry of Health of the Russian Federation, Moscow, Russia; 8Department of Biology, Saratov State University, Saratov, Russia&ast;These authors contributed equally to this workCorrespondence: Naima LaharnarDepartment of Internal Medicine and Dermatology, Interdisciplinary Center of Sleep Medicine, Charité – Universitätsmedizin Berlin, Campus Charité Mitte, Chariteplatz 1, Berlin, 10117, GermanyTel +49-30 450 513 120Email naima.laharnar@charite.dePurpose: An early prescreening in suspected obstructive sleep apnea (OSA) patients is desirable to expedite diagnosis and treatment. However, the accuracy and applicability of current prescreening tools is insufficient. We developed and tested an unbiased scoring system based solely on objective variables, which focuses on the diagnosis of severe OSA and exclusion of OSA.Patients and Methods: The OSA prediction score was developed (n = 150) and validated (n = 50) within German sleep center patients that were recruited as part of the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Six objective variables that were easy to assess and highly correlated with the apnea–hypopnea index were chosen for the score, including some known OSA risk factors: body-mass index, neck circumference, waist circumference, tongue position, male gender, and age (for women only). To test the predictive ability of the score and identify score thresholds, the receiver-operating characteristics (ROC) and curve were calculated.Results: A score ≥ 8 for predicting severe OSA resulted in an area under the ROC curve (ROC-AUC) of 90% (95% confidence interval: 84%, 95%), test accuracy of 82% (75%, 88%), sensitivity of 82% (65%, 93%), specificity of 82% (74%, 88%), and positive likelihood ratio of 4.55 (3.00, 6.90). A score ≤ 5 for predicting the absence of OSA resulted in a ROC-AUC of 89% (83%, 94%), test accuracy of 80% (73%, 86%), sensitivity of 72% (55%, 85%), specificity of 83% (75%, 89%), and positive likelihood ratio of 4.20 (2.66, 6.61). Performance characteristics were comparable in the small validation sample.Conclusion: We introduced a novel prescreening tool combining easily obtainable objective measures with predictive power and high general applicability. The proposed tool successfully predicted severe OSA (important due to its high risk of cardiovascular disease) and the exclusion of OSA (rarely a feature of previous screening instruments, but important for better differential diagnosis and treatment).Keywords: obstructive sleep apnea, diagnostic, sensitivity, specificity, screening

Eirin Fränkl,1 Serena Scarpelli,2 Michael R Nadorff,3,4 Bjørn Bjorvatn,5 Courtney J Bolstad,3 Ngan Yin Chan,6 Frances Chung,7 Yves Dauvilliers,8 Colin A Espie,9 Yuichi Inoue,10,11 Damien Leger,12,13 Tainá Macêdo,14 Kentaro Matsui,15,16 Ilona Merikanto,17– 19 Charles M Morin,20 Sérgio Mota-Rolim,21 Markku Partinen,22,23 Thomas Penzel,24 Giuseppe Plazzi,25,26 Mariusz Sieminski,27 Yun Kwok Wing,6 Luigi De Gennaro,2,28 Brigitte Holzinger1,29 1Institute for Consciousness and Dream Research, Vienna, Austria; 2Department of Psychology, Sapienza University of Rome, Rome, Italy; 3Mississippi State University, Mississippi State, MS, USA; 4Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA; 5Department of Global Public Health and Primary Care, University of Bergen, and Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Bergen, Norway; 6Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China; 7Department of Anesthesiology and Pain Medicine, University Health Network, University of Toronto, Toronto, Canada; 8Sleep-Wake Disorders Center, Department of Neurology, Gui-de-Chauliac Hospital, Institute for Neurosciences of Montpellier INM, INSERM, University of Montpellier, Montpellier, France; 9Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; 10Department of Somnology, Tokyo Medical University, Tokyo, Japan; 11Japan Somnology Center, Neuropsychiatric Research Institute, Tokyo, Japan; 12Université de Paris, VIFASOM (EA 7331 Vigilance Fatigue, Sommeil et Santé Publique), Paris, France; 13APHP, Hotel-Dieu de Paris, Centre du Sommeil et de la Vigilance, Paris, France; 14Department of Psychology, Federal University of Rio Grande do Norte, Natal, Brazil; 15Department of Clinical Laboratory and Department of Sleep-Wake Disorders, National Center of Neurology and Psychiatry National Institute of Mental Health, Kodaira, Japan; 16Department of Psychiatry, Tokyo Women’s Medical University, Tokyo, Japan; 17Sleep Well Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; 18Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland; 19Orton Orthopaedics Hospital, Helsinki, Finland; 20École de Psychologie, Centre d’étude des troubles du sommeil, Centre de recherche CERVO/Brain Research Center, Université Laval, Québec, Canada; 21Brain Institute, Physiology and Behavior Department, and Onofre Lopes University Hospital, Federal University of Rio Grande do Norte, Natal, Brazil; 22Helsinki Sleep Clinic, Terveystalo Healthcare, Helsinki, Finland; 23Department of Neurosciences, Clinicum, University of Helsinki, Helsinki, Finland; 24Sleep Medicine Center, Charité Universitätsmedizin Berlin, Berlin, Germany; 25IRCCS, Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; 26Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; 27Department of Emergency Medicine, Medical University of Gdansk, Gdansk, Poland; 28IRCCS Fondazione Santa Lucia, Rome, Italy; 29Medical University Vienna, ZK-Schlafcoaching, Vienna, AustriaCorrespondence: Brigitte HolzingerInstitute for Consciousness and Dream Research, Canongasse 13/1, Vienna, 1180, AustriaTel +43699-101 99 042Fax +4301-25330334600Email brigitte.holzinger@meduniwien.ac.atObjective: Many have reported odd dreams during the pandemic. Given that dreams are associated with mental health, understanding these changes could provide crucial information about wellbeing during the pandemic. This study explored associations between COVID-19 and dream recall frequency (DRF), and related social, health, and mental health factors.Methods: We conducted a cross-sectional web survey of 19,355 individuals in 14 countries from May to July 2020. We collected data on COVID-19, mental health, sleep and DRF during the pandemic. We performed McNemar Tests to compare low (< 3 nights per week) and high DRF (≥ 3 nights per week) before and during COVID-19 and to evaluate changes in sleep variables segmented by DRF. Chi-square tests were conducted to compare characteristics between low and high DRF. Logistic regression analyses were conducted to examine associations between various independent variables and DRF.Results: Reports of high DRF during the pandemic were higher than before the pandemic (P< 0.001). Female gender (aOR=1.25, 95% CI 1.10– 1.41), nightmares (aOR=4.22, 95% CI 3.45– 5.17), sleep talking (aOR= 2.36, 1.73– 3.23), sleep maintenance problems (aOR=1.34, 95% CI 1.15– 1.56), symptoms of REM sleep behavior disorder (RBD; aOR=1.24, 95% CI 1.09– 1.41) and repeated disturbing thoughts (posttraumatic stress disorder (PTSD) symptoms) were associated with high DRF. Age group 55– 64 years (aOR=0.69, 95% CI 0.58– 0.83) reported less high DRF than younger participants. Unadjusted OR showed associations between depression, anxiety, and DRF; however, in adjusted regression depression (aOR= 0.71, 0.59– 0.86) and anxiety (aOR=0.79, 95% CI 0.66– 0.94) were negatively associated with high DRF.Conclusion and Relevance: DRF was higher than pre-pandemic levels across four continents. DRF was associated with gender and parasomnias like nightmares and RBD symptoms, sleep maintenance problems, PTSD symptoms and negatively associated with depression and anxiety. The results implicate that COVID-19 is reflected in our dreams as an expression of the emotional intensity of the pandemic.Keywords: sleep, sleep disorder, mental health, parasomnia, collective threat

Riva Tauman,1 Murray Berall,2 Richard Berry,3 Tamar Etzioni,4 Noam Shrater,5 Dennis Hwang,6 Ibrahim Marai,7 Prasanth Manthena,8 Anil Rama,9 Rebecca Spiegel,10 Thomas Penzel,11 Nira Koren Morag,12 Giora Pillar4 1Sleep Disorders Center, Tel Aviv Souraski Medical Center, Tel Aviv, Israel; 2Center of Sleep and Chronobiology, Toronto, ON, Canada; 3UF Health Sleep Center, University of Florida, Gainesville, FL, USA; 4Technion Faculty of Medicine, Sleep Laboratory, Carmel Medical Center, Haifa, Israel; 5Cardiology Department, Soroka Medical Center, Be’er Sheva, Israel; 6Kaiser Permanente Fontana Medical Center, Fontana, CA, USA; 7Cardiology Department, Rambam Medical Center, Haifa, Israel; 8Sleep Clinic, Kaiser Permanente Los Angeles Medical Center, Los Angeles, CA, USA; 9Kaiser Permanente San Jose Medical Center, San Jose, CA, USA; 10Stony Brook University Hospital, Stony Brook, NY, USA; 11Charite Universitätsmedizin Berlin, Sleep Medicine Center, Berlin, Germany; 12Sackler School of Medicine, Tel Aviv University, Tel Aviv, IsraelCorrespondence: Riva TaumanSleep Disorders Center, Tel Aviv Souraski Medical Center, 6 Weitzman Street, Tel Aviv 6423906, IsraelTel +972 36974614Fax +1 972 36974634Email tauman@tlvmc.gov.ilBackground: Early diagnosis and treatment of sleep apnea in patients with atrial fibrillation (AF) is critical. The WatchPAT (WP) device was shown to be accurate for the diagnosis of sleep apnea; however, studies using the WatchPAT device have thus far excluded patients with arrhythmias due to the potential effect of arrhythmias on the peripheral arterial tonometry (PAT) amplitude and pulse rate changes.Purpose: To examine the accuracy of the WP in detecting sleep apnea in patients with AF.Patients and Methods: Patients with AF underwent simultaneous WP and PSG studies in 11 sleep centers. PSG scoring was blinded to the automatically analyzed WP data.Results: A total of 101 patients with AF (70 males) were recruited. Forty-six had AF episodes during the overnight sleep study. A significant correlation was found between the PSG-derived AHI and the WP- derived AHI (r=0.80, p< 0.0001). There was a good agreement between PSG-derived AHI and WP-derived AHI (mean difference of AHI: -0.02± 13.2). Using a threshold of AHI ≥ 15 per hour of sleep, the sensitivity and specificity of the WP were 0.88 and 0.63, respectively. The overall accuracy in sleep staging between WP and PSG was 62% with Kappa agreement of 0.42.Conclusion: WP can detect sleep apnea events in patients with AF. AF should not be an exclusion criterion for using the device. This finding may be of even greater importance in the era of the COVID19 epidemic, when sleep labs were closed and most studies were home based.Keywords: home sleep apnea test, WatchPAT, obstructive sleep apnea, atrial fibrillation

Ying Huang,1 Steve Hennig,1 Ingo Fietze,1 Thomas Penzel,1,2 Christian Veauthier1 1Interdisciplinary Center of Sleep Medicine, Charité University Medicine Berlin, Berlin 10117, Germany; 2Department of Biology, Saratov State University, Saratow, RussiaCorrespondence: Christian VeauthierInterdisziplinäres Schlafmedizinisches Zentrum, Charité Universitätsmedizin Berlin, Luisenstraße 13, Berlin 10117 Tel +49 30 513 232Fax +49 30 513 959Email christian.veauthier@charite.deBackground: Sleepiness at the wheel affects 10% to 15% of drivers and is one major cause of death on highways with one-third of fatal accidents. Obstructive sleep apnea (OSA) is one of the most common sleep disorders leading to sleepiness at the wheel. The aim of this study was to compare the psychomotor vigilance test reaction time (PVT RT) in OSA patients and controls (morning and afternoon) with the results of a divided attention steering simulator (DASS). A second purpose was to compare these results with the mean sleep latencies in the multiple sleep latency test (MSLT), the Epworth Sleepiness Scale (ESS) values and a neurocognitive test (test of attentional performance, TAP).Patients and Methods: Thirty eight OSA patients and 16 age and sex matched healthy controls were investigated by ESS, PVT, TAP, MSLT, and DASS (response time, failed responses, lane deviation, and off-road-events).Results: With increasing age, the performance in the DASS decreased. There was no correlation between the DASS and the results of the MSLT and ESS. The controls showed a significantly faster DASS response time in the morning compared to OSA patients (median 2.1 versus 3.0; p=0.044) and fewer off-road events (9 versus 37; p=0.042). We found a moderate correlation between the PVT RT and all parameters of the DASS, as well as the TAP “alertness” subtest.Conclusion: The increase of PVT RT as well as the decreased tonic alertness in the TAP in untreated OSA patients correlated with an impairment of simulated driving performance. The PVT and the TAP are both suitable diagnostic tools for measuring impaired driving ability in OSA patients. The MSLT did not correlate with the simulated driving performance. We recommend investigation of a longer version of the PVT in order to increase its sensitivity.Keywords: polysomnography, sustained attention, tonic alertness, vigilance, MSLT, simulated driving performance

This article presents a review of signals used for measuring physiology and activity during sleep and techniques for extracting information from these signals. We examine both clinical needs and biomedical signal processing approaches across a range of sensor types. Issues with recording and analysing the signals are discussed, together with their applicability to various clinical disorders. Both univariate and data fusion (exploiting the diverse characteristics of the primary recorded signals) approaches are discussed, together with a comparison of automated methods for analysing sleep.

Summary: Periodic limb movements during sleep and obstructive sleep apnea are both associated with increased sympathetic tone, and have been proposed as risk factors for heart diseases and, in particular, cardiovascular disease. As sympathetic system activation may lead to dyslipidaemia, periodic limb movements during sleep could be an additional risk factor for cardiovascular disease in patients with obstructive sleep apnea. The aim of the study was to determine whether the presence of periodic limb movements during sleep affects serum lipid levels in obstructive sleep apnea. Total cholesterol, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, non‐ high‐density lipoprotein cholesterol and triglyceride levels were investigated in 4138 patients with obstructive sleep apnea in the European Sleep Apnea Database (ESADA) cohort, divided into those with periodic limb movements during sleep index ≥ 15 per hr (n = 628) and controls (n = 3510). ANCOVA adjusted for age, sex, body mass index, apnea–hypopnea index, alcohol intake, smoking status, diabetes, insomnia and study site was used to assess differences in lipids between periodic limb movements during sleep and controls. Patients with periodic limb movements during sleep (24% female, 54.4 ± 12.1 years, body mass index 31.9 ± 5.8 kg m−2, apnea–hypopnea index 36.7 ± 25.4 per hr) had higher triglyceride (1.81 ± 1.04 versus 1.69 ± 0.90 mmol L−1, p = 0.002) and lower high‐density lipoprotein cholesterol (1.19 ± 0.34 versus 1.24 ± 0.37 mmol L−1, p = 0.002) levels, whilst there was no difference in either total cholesterol (4.98 ± 1.10 versus 4.94 ± 1.07 mmol L−1), low‐density lipoprotein cholesterol (3.04 ± 0.96 versus 2.98 ± 0.98 mmol L−1) or non‐ high‐density lipoprotein cholesterol (3.78 ± 1.10 versus 3.70 ± 1.05 mmol L−1) concentrations (all p > 0.05). The results remained unchanged after most sensitivity analyses. Patients with obstructive sleep apnea with periodic limb movements during sleep had more prevalent cardiovascular disease (11% versus 6%, p < 0.01). Periodic limb movements during sleep in obstructive sleep apnea is associated with dyslipidaemia independently of important confounders. Our results highlight periodic limb movements during sleep as an additional risk factor for cardiovascular disease in obstructive sleep apnea. [ABSTRACT FROM AUTHOR]

Daniel J Levendowski,1 Garun S Hamilton,2 Erik K St. Louis,3 Thomas Penzel,4 David Dawson,5 Philip R Westbrook11Advanced Brain Monitoring, Inc., Carlsbad, CA, USA; 2Monash Health & School of Clinical Sciences, Monash University, Clayton, VIC, Australia; 3Center for Sleep Medicine, Departments of Neurology and Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA; 4Sleep Medicine Center, Charité Universitätsmedizin Berlin, GmbH, Berlin, Germany; 5Department of Anesthesiology, Bradford Teaching Hospitals NHS Foundation Trust, West Yorkshire, UKObjective: 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 p5/hr, and 6% exceeding >10 events/hr. The positive and negative percent agreements were uniformly good to excellent across varying clinical POSA cutoffs; percent agreements (positive, negative) were: AHI≥5=0.99, 0.78; AHI≥10=0.96, 0.89; and AHI≥15=0.96, 0.89. Cohen’s Kappa scores also showed substantial agreement for overall as well as supine and non-supine positions across varying clinical cutoffs of the AHI. Frequency of POSA was reproducibly uniform between 59% and 61% for both POSA criteria. When the O/NS and S/NS definitions conflicted in POSA characterization, O/NS was superior for identifying patients who might exhibit a greater response to supine restriction positional therapy.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.Keywords: obstructive sleep apnea, positional, supine, apnea-hypopnea index, oxygen desaturation index

Christian Veauthier,1 Sophie K Piper,2,3 Gunnar Gaede,4 Thomas Penzel,1,5 Friedemann Paul6,7 1Interdisciplinary Center of Sleep Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany; 2Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Biometry and Clinical Epidemiology, Berlin, Germany; 3Berlin Institute of Health (BIH), Berlin, Germany; 4Department of Neurology, St. Joseph Krankenhaus Berlin-Weissensee, Berlin, Germany; 5International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic; 6NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany; 7Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany Background: The first night effect (FNE) is a polysomnography (PSG) habituation effect in the first of several consecutive in-laboratory PSGs (I-PSGs). The FNE is caused by the discomfort provoked by electrodes and cables and the exposure to an unfamiliar environment. A reverse FNE (RFNE) with an improved sleep in the first night is characteristic of insomnia, presumably because the video PSG in the sleep laboratory leads to a decrease in the negatively toned cognitive activity. Therefore, two or more I-PSGs are required for an accurate diagnosis. Although the FNE is well documented in I-PSG, little is known about the FNE and the RFNE in home-based PSGs (H-PSGs).Methods: This is a retrospective analysis of a recently published cross-sectional study using H-PSG. Sixty-three consecutive patients suffering from multiple sclerosis (MS) were investigated by two consecutive H-PSGs without video. The differences between the first and second H-PSGs were analyzed. The patients were classified into four subgroups: no sleep disorder, insomnia, sleep-related breathing disorders (SRBDs), and periodic limb movement disorder or restless legs syndrome (PLMD/RLS).Results: MS patients suffering from insomnia showed no RFNE. MS patients with SRBD or PLMD/RLS showed no reduced sleep efficiency but significantly less slow wave sleep. Furthermore, SRBD patients showed significantly less non-rapid eye movement (NREM) sleep, and PLMD/RLS patients were significantly awake longer in the first night after sleep onset (increased wake-after-sleep-onset time) and showed a higher rapid eye movement (REM) latency.Conclusion: SRBD and PLMD/RLS patients showed a significant FNE. Two consecutive H-PSGs are required in these patients to obtain a precise hypnogram even in the ambulatory field. In MS patients suffering from insomnia, no RFNE was found, and in insomnia patients one H-PSG seems to be sufficient. Keywords: insomnia, multiple sclerosis, outpatient sleep studies, polysomnography, sleep latency, wake after sleep onset