The Epidemiology of Adult Obstructive Sleep Apnea

Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD 21224, USA.
Proceedings of the American Thoracic Society 03/2008; 5(2):136-43. DOI: 10.1513/pats.200709-155MG
Source: PubMed


Obstructive sleep apnea is a chronic condition characterized by frequent episodes of upper airway collapse during sleep. Its effect on nocturnal sleep quality and ensuing daytime fatigue and sleepiness are widely acknowledged. Increasingly, obstructive sleep apnea is also being recognized as an independent risk factor for several clinical consequences, including systemic hypertension, cardiovascular disease, stroke, and abnormal glucose metabolism. Estimates of disease prevalence are in the range of 3% to 7%, with certain subgroups of the population bearing higher risk. Factors that increase vulnerability for the disorder include age, male sex, obesity, family history, menopause, craniofacial abnormalities, and certain health behaviors such as cigarette smoking and alcohol use. Despite the numerous advancements in our understanding of the pathogenesis and clinical consequences of the disorder, a majority of those affected remain undiagnosed. Simple queries of the patient or bed-partner for the symptoms and signs of the disorder, namely, loud snoring, observed apneas, and daytime sleepiness, would help identify those in need of further diagnostic evaluation. The primary objective of this article is to review some of the epidemiologic aspects of obstructive sleep apnea in adults.

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    • "Some patients tolerate sleep apnea more than 300 times a night and this will consequently lead to daytime sleepiness, headaches, decreased quality of life and depression [2], [3]. Approximately, 3-7% of male subgroups and 2-5% of females in general adult categories suffer from SAS difficulties [4]. A direct relationship has been elucidated between OSA and cardiovascular diseases, but it is not clear that OSA is the main cause for greater prevalence of cardiac arrhythmia in these patients, or both of these obstacles are originated from a common factor such as obesity; since obesity and high blood pressure are the leading factors in cardiovascular diseases occurrence [3]. "
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    ABSTRACT: The obstructive sleep apnea (OSA) is one of the most important sleep disorders characterized by obstruction of the respiratory tract and cessation in respiratory flow level. Currently, apnea diagnosis is mainly based on the Polysomnography (PSG) testing during sleeping hours, however, recording the entire signals during nights is a very costly, time-consuming and difficult task. The goal of this study is to provide and validate an automatic algorithm to analyze four PSG-recordings and detect the occurrence of sleep apnea by non-invasive features. Four PSG signals were extracted from oxygen saturation (SaO2), Transitional air flow (Air Flow), abdominal movements during breathing (Abdomen mov.) and movements of the chest (Thoracic mov.). We describe a fuzzy algorithm to compensate the imprecise information about the range of signal loss, regarding the expert opinions. Signal classification is implemented minute-by-minute and for 30 labeled samples of MIT/BIH data sets (acquired from PhysioNet). The obtained data from 18 apnea subjects (11 males and 7 females, mean age 43 years) were categorized in three output signals of apnea, hypopnea and normal breathing. The proposed algorithm shows proficiency in diagnosing OSA with acceptable sensitivity and specificity, respectively 86% and 87%.
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    • "Obstructive sleep apnea (OSA) is characterized by repeated episodes of complete obstruction of the upper airway, resulting in oxygen desaturation and arousal from sleep. The prevalence of OSA is 2e5% in adult women and 3e7% in adult men [1]. The symptoms that these patients may experience are sleepiness, morning headaches , tiredness and fatigue, reduced vigilance and executive function, memory impairment, depression and impotence. "
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    ABSTRACT: This systematic review summarizes the evidence regarding the quality of patient-reported outcome measures (PROMs) validated in patients with obstructive sleep apnea (OSA). We performed a systematic literature search of all PROMs validated in patients with OSA, and found 22 measures meeting our inclusion criteria. The quality of the studies was assessed using the consensus-based standards for the selection of health status measurement instruments (COSMIN) checklist. The results showed that most of the measurement properties of the PROMs were not, or not adequately, assessed. For many identified PROMs there was no involvement of patients with OSA during their development or before the PROM was tested in patients with OSA. Positive exceptions and the best current candidates for assessing health status in patients with OSA are the sleep apnea quality of life index (SAQLI), Maugeri obstructive sleep apnea syndrome (MOSAS) questionnaire, Quebec sleep questionnaire (QSQ) and the obstructive sleep apnea patient-oriented severity index (OSAPOSI). Even though there is not enough evidence to fully judge the quality of these PROMs as outcome measure, when interpreted with caution, they have the potential to add value to clinical research and clinical practice in evaluating aspects of health status that are important to patients.
    Preview · Article · Oct 2015 · Sleep Medicine Reviews
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    • "Sleep Apnea-Hypopnea Syndrome (SAHS) is one of the most common disorders affecting sleep, characterized by the repeated occurrence of involuntary episodes of total or partial reduction in patient's respiration during the night [1]. Several studies have been carried around the world during the last years, which estimate that the prevalence of SAHS is between the 3% and the 7% of the adult population [2] [3]. Patients suffering from SAHS present involuntary respiratory pauses that repeats throughout the night. "
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    ABSTRACT: Automatic diagnosis of the Sleep Apnea-Hypopnea Syndrome (SAHS) has become an important area of research due to the growing interest in the field of sleep medicine and the costs associated with its manual diagnosis. The increment and heterogeneity of the different techniques, however, make it somewhat difficult to adequately follow the recent developments. A literature review within the area of computer-assisted diagnosis of SAHS has been performed comprising the last 15 years of research in the field. Screening approaches, methods for the detection and classification of respiratory events, comprehensive diagnostic systems, and an outline of current commercial approaches are reviewed. An overview of the different methods is presented together with validation analysis and critical discussion of the current state of the art.
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