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Daytime sleepiness is an important symptom of obstructive sleep apnoea syndrome (OSAS). The standard tests for its objective quantification use EEG recordings, and are time consuming and expensive, which makes them difficult to use for large studies. This study assesses the ability of a simple test of sustained 'wakefulness' to discriminate the excessive somnolence of severe symptomatic obstructive sleep apnoea from normality, and compares its results to the traditional EEG based Maintenance of Wakefulness Test (MWT). Ten subjects (7M 3F) with severe sleep apnoea (> 4% SaO2 dip rate median 32.7 (90% central range 9.7-65.6)) and symptoms of daytime sleepiness, (Epworth Sleepiness Score (ESS)17(10-24)) and 10 normal subjects (4M 6F, ESS 3.5(1-8)) were studied. The MWT and the behavioural test (Oxford SLEep Resistance test - OSLER test) were performed on each subject in random order on 2 separate days. The protocol for both tests was the same with 4 X 40 min sleep resistance challenges throughout the day while sound isolated in a darkened room. During the OSLER test subjects were asked to press a switch in response to a light emitting diode (LED), which was lit for 1 s in every three. Both the switch and the light were connected to a computer that stored both the number of times the light was illuminated and whether a correct response was made. The OSLER test discriminated the normal subjects from the sleep apnoea group (mean sleep latency (min) normal group 39.8, OSA group 10.5) as well as the traditional MWT (normal group 38.1 OSA group 7.3) and was much simpler to administer. This test has the advantage that sleep onset is defined objectively and automatically as a failure to respond to the light, rather than from EEG interpretation, which is inevitable partly subjective. This technique may provide a simple and robust method of objectively quantifying daytime sleepiness for large studies.

Type

Journal article

Journal

J Sleep Res

Publication Date

06/1997

Volume

6

Pages

142 - 145

Keywords

Adult, Disorders of Excessive Somnolence, Electroencephalography, Humans, Sleep Apnea Syndromes