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Clinical Trial Summary

The objective of this study is to compare the modified adaptive servoventilation control algorithm of the with the standardised algorithms of routinely-used servoventilation processes (AutoSet CS2) in terms of the effect on obstructive and central events. The aim is to normalise breathing during sleep and hence eliminate the sleep-related breathing disorder, resulting in even more effective treatment of nocturnal breathing disorders in patients with cardiovascular diseases and sleep apnoea, to ensure optimum therapy success.


Clinical Trial Description

Patients with cardiovascular disorders frequently suffer from sleep-related respiratory disorders (SRRD), such as obstructive sleep apnea (OSA) or a specific form of central sleep apnea, Cheyne-Stokes breathing (CSB, periodic breathing). However there is also a significant incidence of complex nocturnal breathing disorders, with both obstructive and central components. Sleep-related breathing disorders of this kind cause decreases in arterial oxygen saturation through brief hypopneas and apneas. Disturbed breathing also causes the patient to wake frequently during the night (arousals), usually during the hyperventilatory phase of CSB. Repeated arousals cause fragmentation of sleep, and therefore a deep sleep deficit. This leads to increased sleepiness during the day and impaired cognitive performance. Previous studies have shown that Cheyne-Stokes breathing can be treated effectively with adaptive servoventilation. An enhancement to the routinely used algorithm (AutoSet CS2) has been created which allows the algorithm to differentiate between obstructive events and Cheyne-Stokes breathing, and better respond to apneas and hypopneas to eliminate the sleep-related breathing disorder and normalise breathing during sleep. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT01037439
Study type Interventional
Source ResMed
Contact
Status Completed
Phase N/A
Start date June 2008
Completion date December 2009

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