New acoustic method for detecting upper airway obstruction in patients with sleep apnoea
Article first published online: 26 JAN 2010
DOI: 10.1111/j.1440-1843.2009.01689.x
© 2010 The Authors. Journal compilation © 2010 Asian Pacific Society of Respirology
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How to Cite
STOCKX, E. M., CAMILLERI, P., SKUZA, E. M., CHURCHWARD, T., HOWES, J. M., HO, M., MCDONALD, T., FREEZER, N., HAMILTON, G., WILKINSON, M. H. and BERGER, P. J. (2010), New acoustic method for detecting upper airway obstruction in patients with sleep apnoea. Respirology, 15: 326–335. doi: 10.1111/j.1440-1843.2009.01689.x
Publication History
- Issue published online: 26 JAN 2010
- Article first published online: 26 JAN 2010
- Received 28 July 2009; invited to revise 7 September 2009, 30 September 2009; revised 10 September 2009, 30 September 2009; accepted 12 October 2009 (Associate Editor: Robin Taylor).
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Keywords:
- acoustic method;
- diagnosis of apnoea;
- obstructive sleep apnoea;
- polysomnography;
- sound attenuation
This article investigates a new acoustic device to assess the behaviour of the upper airway in patients with OSA. Currently there is no simple non-invasive method to perform such measurements. As such this paper describes the device in probing the patency of the airway during sleep and increasing the efficiency of diagnosing OSA.
ABSTRACT
Background and objective: OSA is a common disorder resulting in health and economic burdens. Currently identifying OSA in patients involves expensive techniques that require overnight studies in a laboratory setting with qualified staff. This paper tests a new acoustic device (AirwayClear (AC)) for assessing upper airway patency in human subjects with OSA. We hypothesize that obstructive apnoeas would be detected equally well with AC and polysomnography (PSG).
Methods: Twenty-three patients with severe OSA underwent an overnight CPAP titration study. We introduced pseudorandom noise (600–1200 Hz) using AC to the patient's nasal mask during 1 h of subtherapeutic CPAP. AC determined a measure of airway patency based on the level of pseudorandom noise reaching a sternal notch sensor. The ability of AC to detect obstructive respiratory events was compared with standard PSG.
Results: Three hundred and twenty-two obstructive events (obstructive and mixed apnoeas) were identified by PSG. AC scored 80% as complete obstructions and 16% as partial obstructions. Conversely, AC detected 281 complete obstructions. PSG recognized 84% as apnoeas and scored 11% as hypopnoeas. Of the 204 hypopnoeas identified with PSG, AC indicated the airway was partially or completely obstructed in 69% of patients. A Bland–Altman analysis for the apnoeas from the two measures showed a mean difference of 2.3 events/h and 95% confidence intervals of ±15.5 events/h.
Conclusions: We conclude that AC is able to track airway patency and to identify airway closure in patients with OSA.

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