Abstract
Introduction Obstructive sleep apnoea (OSA) is underdiagnosed, necessitating an expansion of clinical testing.1 The novel Sunrise™ monitor (Sunrise, Belgium) provides an automated approach for diagnosing OSA, utilising mandibular movement and machine learning to estimate the apnoea-hypopnea index (AHI). AHI varies across consecutive nights of sleep analysis.2 This study aimed to evaluate the night-to-night variability in the estimated AHI as detected by the Sunrise™ monitor in healthy adults.
Methods Nineteen healthy volunteers (mean ± SD 38.1 ± 18.2 years), who reported snoring but had no diagnosed sleep disorders were invited to participate. Each participant underwent a home sleep study, wearing both the Sunrise monitor™ and a respiratory polygraphy device (Apnoealink, Resmed, Australia) simultaneously, on two consecutive nights. The Sunrise™ monitor provided an automated estimated AHI; the polygraphy data was automatically analysed using AASM 2012 scoring criteria, and then manually reviewed.3 The change in AHI across the two nights was evaluated using the Wilcoxon signed-rank test, and the agreement in the AHI across the two nights was evaluated using the intraclass correlation coefficient (ICC).
The study was approved by the Imperial College London’s ethics committee, which granted the supervisors the ability to review after submitting the Research Governance and Integrity Team (RGIT) ethics checklist.
Results The change in AHI for both the Sunrise™ monitor and respiratory polygraphy differed from night-to-night by -0.6 events/hour and -1.1 events/hour respectively (table 1). These differences were not statistically significant. The Sunrise™ monitor exhibited a higher level of agreement in AHI measurements from night-to-night compared to respiratory polygraphy; ICC 0.77 (0.50 to 0.91) vs 0.59 (0.21 to 0.82).
Discussion Both devices displayed a variability in the AHI between the two nights, the variability was less for the Sunrise™ monitor compared to Respiratory Polygraphy. Further investigation is necessary to assess its impact on OSA diagnosis and severity.
References
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