Technologic advances in the assessment and management of obstructive sleep apnoea beyond the apnoea-hypopnoea index: a narrative review

Abstract

Obstructive sleep apnoea (OSA) is a growing and serious worldwide health problem with significant health and socioeconomic consequences. Current diagnostic testing strategies are limited by cost, access to resources and over reliance on one measure, namely the apnoea-hypopnoea frequency per hour (AHI). Recent evidence supports moving away from the AHI as the principle measure of OSA severity towards a more personalised approach to OSA diagnosis and treatment that includes phenotypic and biological traits. Novel advances in technology include the use of signals such as heart rate variability (HRV), oximetry and peripheral arterial tonometry (PAT) as alternative or additional measures. Ubiquitous use of smartphones and developments in wearable technology have also led to increased availability of applications and devices to facilitate home screening of at-risk populations, although current evidence indicates relatively poor accuracy in comparison with the traditional gold standard polysomnography (PSG). In this review, we evaluate the current strategies for diagnosing OSA in the context of their limitations, potential physiological targets as alternatives to AHI and the role of novel technology in OSA. We also evaluate the current evidence for using newer technologies in OSA diagnosis, the physiological targets such as smartphone applications and wearable technology. Future developments in OSA diagnosis and assessment will likely focus increasingly on systemic effects of sleep disordered breathing (SDB) such as changes in nocturnal oxygen and blood pressure (BP); and may also include other factors such as circulating biomarkers. These developments will likely require a re-evaluation of the diagnostic and grading criteria for clinically significant OSA.

Keywords: Obstructive sleep apnoea (OSA); beyond the apnoea-hypopnoea index (beyond the AHI); diagnosis; screening; smartphones; wearable technology.

Figure 1

Graphic representation of a three-dimensional model of OSA disease severity. The X-axis represents respiratory events such as apnoeas and hypopnoeas; the Y-axis represents the acute systemic effects of sleep-disordered breathing such as oxygen desaturation and increased blood pressure. The intermediate axis represents end-organ effects such as vascular and metabolic, predisposing to comorbidities such as hypertension and diabetes. The grey triangular zone is intended to convey the variability in susceptibility to comorbidity. OSA, obstructive sleep apnoea.

Figure 2

Potential physiological signals for the diagnosis and monitoring of OSA. Signals can be fed wirelessly, for example, using Bluetooth to a router or Smartphone and then uploaded to a secured database, whereby end users (i.e., physician) may access and review the data. OSA, obstructive sleep apnoea; EEG, electroencephalogram; ECG, electrocardiogram; HRV, heart rate variability; PTT, pulse transit time; PAT, peripheral arterial tone; BP, blood pressure; ABPM, ambulatory blood pressure monitor

Figure 3

Signals potentially available with smartphone technology that may be relevant to evaluating sleep disordered breathing.