Obstructive sleep apnoea (OSA) in regional and remote Indigenous Australians

Background: Despite Aboriginal and Torres Strait Islander people having increased risk factors for OSA (diabetes, obesity) and high levels of comorbid associated conditions (chronic non-communicable diseases), there are currently no published data relating to the nature of sleep related breathing disorders affecting Indigenous adults. Aims/Objectives: The aim of this study was to compare the use of sleep diagnostic tests, the risks, and cofactors, and outcomes of the care of Indigenous and non-indigenous Australian adults in regional and remote Australia in whom sleep related breathing disorders have been diagnosed. Methods: A retrospective cohort study of 200 sequential subjects: 100 Aboriginal and/or Torres Strait Islander people and 100 non-Indigenous Australians in northern Queensland and Central Australia. Results: Results showed overall Indigenous Australians were 1.8 times more likely to have a positive diagnostic sleep study performed compared with non-indigenous patients, 1.6 times less likely in central Australia and 3.4 times more likely in far north Queensland. All regional and remote residents accessed diagnostic sleep studies at a rate less than Australia overall (31/100,000/y compared with 575/100,000/y). Discussion: Appropriate and more accessible diagnostic and treatment sleep services are required in regional and remote Australia. Further research is required to validate appropriate screening tools and pathways of care especially for Aboriginal and Torres Strait Islander peoples

Sleep Strategies: Sleep in Women A Changing Perspective

As with many other specialties, sleep medicine has been shifting toward helping clinicians obtain a better understanding of gender-specific issues in disorders and disturbances. It is easier today to appreciate the complex dynamics of biological, psychosocial, and cultural factors that define sleep patterns and problems in women. Sleep in women changes across their life spans, with three major shifts likely due to hormonal differences: at the onset of the menstrual cycle, during pregnancy, and during the perimenopausal period

Sleep medicine catalogue of knowledge and skills - Revision

The 'catalogue of knowledge and skills' for sleep medicine presents the blueprint for a curriculum, a textbook, and an examination on sleep medicine. The first catalogue of knowledge and skills was presented by the European Sleep Research Society in 2014. It was developed following a formal Delphi procedure. A revised version was needed in order to incorporate changes that have occurred in the meantime in the International Classification of Sleep Disorders, updates in the manual for scoring sleep and associated events, and, most important, new knowledge in sleep physiology and pathophysiology. In addition, another major change can be observed in sleep medicine: a paradigm shift in sleep medicine has taken place. Sleep medicine is no longer a small interdisciplinary field in medicine. Sleep medicine has increased in terms of recognition and importance in medical care. Consequently, major medical fields (e.g. pneumology, cardiology, neurology, psychiatry, otorhinolaryngology, paediatrics) recognise that sleep disorders become a necessity for education and for diagnostic assessment in their discipline. This paradigm change is considered in the catalogue of knowledge and skills revision by the addition of new chapters.Peer reviewe

Knowledge and Attitude Regarding Sleep Medicine among Medical Students at Qassim University, Saudi Arabia

BACKGROUNDS: Sleep disorders and sleep medicine are underrecognized by both the general public and health care workers. Lack of education and training in sleep medicine has resulted in a culture of physicians who have very limited knowledge about sleep disorders and, as a result, are likely to underdiagnose and under-treat patients. AIM: This study aimed to assess the knowledge of and attitude regarding sleep medicine among medical students at Qassim University. METHODS: This was a cross-sectional study of 4th and 5th-year medical students, conducted at Qassim University (Central and Unaizah branches), Saudi Arabia. We used a self-administered data collection tool to collect personal information (age, name, sex, medical school), and assessed general attitude toward sleep medicine and the students’ current knowledge about sleep medicine using the Assessment of Sleep Knowledge in Medical Education (ASKME) survey. RESULTS: The prevalence of medical students who had a special interest in sleep medicine was 23.3%. Poor knowledge about sleep medicine was detected in 94.8% of students, while good knowledge was observed in only 5.2%. The attitude of the students toward sleep medicine was negative among 40.5% and positive among 59.5%. University branches, gender, and preferred speciality were all significantly associated with attitude score, whereas interest in sleep medicine and knowledge of sleep disorders were associated with both knowledge and attitude scores. CONCLUSION: This study found that medical students’ knowledge of sleep medicine was very low, despite the majority of them having a positive attitude toward it

Sleep medicine catalogue of knowledge and skills – Revision

The 'catalogue of knowledge and skills' for sleep medicine presents the blueprint for a curriculum, a textbook, and an examination on sleep medicine. The first catalogue of knowledge and skills was presented by the European Sleep Research Society in 2014. It was developed following a formal Delphi procedure. A revised version was needed in order to incorporate changes that have occurred in the meantime in the International Classification of Sleep Disorders, updates in the manual for scoring sleep and associated events, and, most important, new knowledge in sleep physiology and pathophysiology. In addition, another major change can be observed in sleep medicine: a paradigm shift in sleep medicine has taken place. Sleep medicine is no longer a small interdisciplinary field in medicine. Sleep medicine has increased in terms of recognition and importance in medical care. Consequently, major medical fields (e.g. pneumology, cardiology, neurology, psychiatry, otorhinolaryngology, paediatrics) recognise that sleep disorders become a necessity for education and for diagnostic assessment in their discipline. This paradigm change is considered in the catalogue of knowledge and skills revision by the addition of new chapters

Towards a Flexible Deep Learning Method for Automatic Detection of Clinically Relevant Multi-Modal Events in the Polysomnogram

Much attention has been given to automatic sleep staging algorithms in past years, but the detection of discrete events in sleep studies is also crucial for precise characterization of sleep patterns and possible diagnosis of sleep disorders. We propose here a deep learning model for automatic detection and annotation of arousals and leg movements. Both of these are commonly seen during normal sleep, while an excessive amount of either is linked to disrupted sleep patterns, excessive daytime sleepiness impacting quality of life, and various sleep disorders. Our model was trained on 1,485 subjects and tested on 1,000 separate recordings of sleep. We tested two different experimental setups and found optimal arousal detection was attained by including a recurrent neural network module in our default model with a dynamic default event window (F1 = 0.75), while optimal leg movement detection was attained using a static event window (F1 = 0.65). Our work show promise while still allowing for improvements. Specifically, future research will explore the proposed model as a general-purpose sleep analysis model.Comment: Accepted for publication in 41st International Engineering in Medicine and Biology Conference (EMBC), July 23-27, 201

Protocol of the SOMNIA project : an observational study to create a neurophysiological database for advanced clinical sleep monitoring

Introduction Polysomnography (PSG) is the primary tool for sleep monitoring and the diagnosis of sleep disorders. Recent advances in signal analysis make it possible to reveal more information from this rich data source. Furthermore, many innovative sleep monitoring techniques are being developed that are less obtrusive, easier to use over long time periods and in the home situation. Here, we describe the methods of the Sleep and Obstructive Sleep Apnoea Monitoring with Non-Invasive Applications (SOMNIA) project, yielding a database combining clinical PSG with advanced unobtrusive sleep monitoring modalities in a large cohort of patients with various sleep disorders. The SOMNIA database will facilitate the validation and assessment of the diagnostic value of the new techniques, as well as the development of additional indices and biomarkers derived from new and/or traditional sleep monitoring methods. Methods and analysis We aim to include at least 2100 subjects (both adults and children) with a variety of sleep disorders who undergo a PSG as part of standard clinical care in a dedicated sleep centre. Full-video PSG will be performed according to the standards of the American Academy of Sleep Medicine. Each recording will be supplemented with one or more new monitoring systems, including wrist-worn photoplethysmography and actigraphy, pressure sensing mattresses, multimicrophone recording of respiratory sounds including snoring, suprasternal pressure monitoring and multielectrode electromyography of the diaphragm

Artificial intelligence in the diagnosis and treatment of sleep apnea. First applications

During the past several years the application of digital health and artificial intelligence in sleep medicine has been developing at an extremely rapid pace. The diagnosis and treatment of patients with obstructive sleep apnea can be improved by artificial intelligence, facilitating the clinical work of sleep medicine specialists. Technologies based on artificial intelligence are becoming an integral part of the clinical practice of specialists in sleep medicine and ENT specialists. Artificial intelligence in medicine serves to make the right diagnosis, which is the key to proper treatment. From the literature review of scientific articles on artificial intelligence, the authors conclude that its application in sleep medicine can bring many benefits for rapid diagnosis and treatment. Artificial intelligence supports the treatment of obstructive sleep apnea and, even though it demands the right amount of data, which is a hurdle, it will prevent the development of a variety of problems, including severe morning headaches, daytime drowsiness, neurocognitive disorders, cardiovascular and metabolic disorders

The mobile sleep medicine model in neurologic practice: Rationale and application

BACKGROUND: Undiagnosed obstructive sleep apnea (OSA) is prevalent in neurological practice and significantly contributes to morbidity and mortality. OSA is prevalent in US adults and causes poor quality sleep and significant neurocognitive, cardiovascular, and cerebrovascular impairments. Timely treatment of OSA reduces cardio-cerebrovascular risks and improves quality of life. However, most of the US population has limited systematic access to sleep medicine care despite its clinical significance. FOCUS: We discuss the importance of systematic screening, testing, and best-practice management of OSA and hypoventilation/hypoxemia syndromes (HHS) in patients with stroke, neurocognitive impairment, and neuromuscular conditions. This review aims to introduce and describe a novel integrated Mobile Sleep Medicine (iMSM) care model and provide the rationale for using an iMSM in general neurological practice to assist with systematic screening, testing and best-practice management of OSA, HHS, and potentially other sleep conditions. KEY POINTS: The iMSM is an innovative, patient-centered, clinical outcome-based program that uses a Mobile Sleep Medicine Unit-a sleep lab on wheels -designed to improve access to OSA management and sleep care at all levels of health care system. The protocol for the iMSM care model includes three levels of operations to provide effective and efficient OSA screening, timely testing/treatment plans, and coordination of further sleep medicine care follow-up. The iMSM care model prioritizes effective, efficient, and patient-centered sleep medicine care; therefore, all parties and segments of care that receive and provide clinical sleep medicine services may benefit from adopting this innovative approach