Obstructive sleep apnoea syndrome: Comparison between polysomnography and portable sleep monitoring based on jaw recordings

Summary Introduction Obstructive sleep apnoea syndrome (OSAS) constitutes a new major public health problem because of its several pathophysiologic consequences such as cognitive disorders, excessive daytime sleepiness with risks of traffic accidents, cardiovascular implications, and decrease of quality of life. The necessity of a gold-standard polysomnography to ensure an accurate diagnosis implies an expensive, technical and time-consuming examination. Thus, it seems logical to develop new systems so as to diagnose SAS and to make it possible to detect apnoeas/hypopnoeas easily during sleep even at home. Aim of the study To assess a novel type-3 portable monitoring (PM) device, the Somnolter, and dedicated automatic analysis of several signals, one of which is the mandibular movement signal. Method We studied patients suffering from OSAS. For all the patients, a nocturnal diagnosis polysomnography (PSG) was recorded in hospital settings, based on six EEG channels, two EOG channels, chin EMG channel, EKG, and respiratory parameters. At the same time, the Somnolter PM device recorded the physiological parameters from its own nasal prongs, thoracic belt, pulse oxymeter, body position, and jaw movement sensors. A visual analysis of PSG recordings was made leading to the detection of apnoea/hypopnoea index (AHI-PSG) and an automatic analysis of the Somnolter traces was performed to get automatic apnoea/hypopnoea index (AHI-A). The added value of the mandible movement signals was the particular jaw movements related to arousals, to respiratory efforts and to sleep/wake state. A comparison was made between the automatic and gold AHIs standard and the correlation was calculated between them. Results Ninety patients, aged between 47 and 70 years (mean age: 55.4 ± 8.7) took part in the study. The linear regression and the correlation coefficient between AHI-PSG and AHI-A showed the good reliability of the automatic method. The Bland Altman analysis shows a correlation of 0.95 with a sensitivity of 83.6 and specificity of 81.8. Conclusion The dedicated automatic analysis based on mandibular movements presents a good potential for the diagnosis of OSAS. The AHI computed by the automatic method is correlated with the AHI-PSG and the Somnolter could easily be used both in hospital, and in ambulatory settings.