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A Framework for Information Processing in the Diagnosis of Sleep Apnea

A Framework for Information Processing in the Diagnosis of Sleep Apnea
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Author(s): Udantha R. Abeyratne (The University of Queensland, Australia)
Copyright: 2011
Pages: 10
Source title: Clinical Technologies: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-60960-561-2.ch203

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Abstract

Obstructive sleep apnea (OSA) is one of the most common sleep disorders. It is characterized by repetitive obstruction of the upper airways during sleep. The frequency of such events can range up to hundreds of events per sleep-hour. Full closure of the airways is termed apnea, and a partial closure is known as hypopnea. The number of apnea/hypopnea events per hour is known as the AHI-index, and is used by clinical community as a measure of the severity of OSA. OSA, when untreated, presents as a major public health concern throughout the world. OSA patients use health facilities at twice the average rate (Delaive, Roos, Manfreda, & Kryger, 1998), causing huge pressures on national healthcare systems. OSA is associated with serious complications such as cardiovascular disease, stroke, (Barber & Quan, 2002; Kryger, 2000,), and sexual impotence. It also causes cognitive deficiencies, low IQ in children, fatigue, and accidents. Australian Sleep Association reported (ASA, 1999) that in the state of New South Wales alone 11,000–43,000 traffic accidents per year were attributable to untreated-OSA.

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