SUMMARYObstructive sleep apnoea is a highly prevalent but under-diagnosed disorder. The gold standard for diagnosis of obstructive sleep apnoea is inpatient polysomnography. This is resource intensive and inconvenient for the patient, and the development of ambulatory diagnostic modalities has been identified as a key research priority. SleepMinder (BiancaMed, NovaUCD, Ireland) is a novel, non-contact, bedside sensor, which uses radio-waves to measure respiration and movement. Previous studies have shown it to be effective in measuring sleep and respiration. We sought to assess its utility in the diagnosis of obstructive sleep apnoea. SleepMinder and polysomnographic assessment of sleep-disordered breathing were performed simultaneously on consecutive subjects recruited prospectively from our sleep clinic. We assessed the diagnostic accuracy of SleepMinder in identifying obstructive sleep apnoea, and how SleepMinder assessment of the apnoea-hypopnoea index correlated with polysomnography. Seventy-four subjects were recruited. The apnoea-hypopnoea index as measured by SleepMinder correlated strongly with polysomnographic measurement (r = 0.90; P 0.0001). When a diagnostic threshold of moderate-severe (apnoea-hypopnoea index ! 15 events h À1 ) obstructive sleep apnoea was used, SleepMinder displayed a sensitivity of 90%, a specificity of 92% and an accuracy of 91% in the diagnosis of sleep-disordered breathing. The area under the curve for the receiver operator characteristic was 0.97. SleepMinder correctly classified obstructive sleep apnoea severity in the majority of cases, with only one case different from equivalent polysomnography by more than one diagnostic class. We conclude that in an unselected clinical population undergoing investigation for suspected obstructive sleep apnoea, SleepMinder measurement of sleep-disordered breathing correlates significantly with polysomnography.

SUMMARYAmbulatory monitoring is of major clinical interest in the diagnosis of obstructive sleep apnoea syndrome. We compared a novel non-contact biomotion sensor, which provides an estimate of both sleep time and sleep-disordered breathing, with wrist actigraphy in the assessment of total sleep time in adult humans suspected of obstructive sleep apnoea syndrome. Both systems were simultaneously evaluated against polysomnography in 103 patients undergoing assessment for obstructive sleep apnoea syndrome in a hospital-based sleep laboratory (84 male, aged 55 AE 14 years and apnoea-hypopnoea index 21 AE 23). The biomotion sensor demonstrated similar accuracy to wrist actigraphy for sleep/wake determination (77.3%: biomotion; 76.5%: actigraphy), and the biomotion sensor demonstrated higher specificity (52%: biomotion; 34%: actigraphy) and lower sensitivity (86%: biomotion; 94%: actigraphy). Notably, total sleep time estimation by the biomotion sensor was superior to actigraphy (average overestimate of 10 versus 57 min), especially at a higher apnoea-hypopnoea index. In post hoc analyses, we assessed the improved apnoea-hypopnoea index accuracy gained by combining respiratory measurements from polysomnography for total recording time (equivalent to respiratory polygraphy) with total sleep time derived from actigraphy or the biomotion sensor. Here, the number of misclassifications of obstructive sleep apnoea severity compared with full polysomnography was reduced from 10/103 (for total respiratory recording time alone) to 7/103 and 4/103 (for actigraphy and biomotion sensor total sleep time estimate, respectively). We conclude that the biomotion sensor provides a viable alternative to actigraphy for sleep estimation in the assessment of obstructive sleep apnoea syndrome. As a non-contact device, it is suited to longitudinal assessment of sleep, which could also be combined with polygraphy in ambulatory studies.

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NIV can be safely used in acute severe asthma although further work is needed to delineate the precise patient selection process.

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