From sleep medicine to medicine during sleep: a new paradigm

Abstract

Sleep has a profound influence on the physiology of body systems and biological processes. Molecular studies have shown circadian-regulated shifts in protein expression patterns across human tissues, further emphasizing the unique functional, behavioral and pharmacokinetic landscape of sleep. Thus, many pathological processes are also expected to exhibit sleep-specific manifestations. Nevertheless, sleep is seldom utilized for the study, detection and treatment of non-sleep-specific pathologies. Modern advances in biosensor technologies have enabled remote, non-invasive recording of a growing number of physiologic parameters and biomarkers. Sleep is an ideal time frame for the collection of long and clean physiological time series data which can then be analyzed using data-driven algorithms such as deep learning. In this perspective paper, we aim to highlight the potential of sleep as an auspicious time for diagnosis, management and therapy of nonsleep-specific pathologies. We introduce key clinical studies in selected medical fields, which leveraged novel technologies and the advantageous period of sleep to diagnose, monitor and treat pathologies. We then discuss possible opportunities to further harness this new paradigm and modern technologies to explore human health and disease during sleep and to advance the development of novel clinical applications-from sleep medicine to medicine during sleep.

Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use

“…For example, a study by Kulkas et al 47 studied the gender difference in the distribution of the desaturation lengths, depths, and areas caused by hypopnea and apnea events. Desaturations are not only caused by apnea or hypopnea events 48 and thus desaturation events and their statistical descriptors may capture the expression of other conditions during sleep. Oxygen desaturation index (ODI x ).…”

Machine learning for nocturnal diagnosis of chronic obstructive pulmonary disease using digital oximetry biomarkers

“…A pulmonary evaluation would be particularly relevant for patients with smoking history, obesity, or those showing major respiratory symptoms, such as dyspnea (Lemarié et al 2010). In a recent perspective paper (Behar 2020) we motivated using overnight physiological recordings for the study, diagnosis and monitoring of non-sleep specific conditions. In the case of COPD, oximetry is of particular interest as it reflects respiratory function.…”

Machine learning for nocturnal mass diagnosis of atrial fibrillation in a population at risk of sleep-disordered breathing

“…We motivate the clinical relevance and feasibility for performing overnight systematic AF screening in population sample at risk of sleep disordered breathing 5 with three arguments: (1) Interaction of AF with sleep disordered breathing: there is incentive in performing systematic AF screening in individuals suspected of sleep-disordered breathing. Several pivotal studies conducted over the past decade have highlighted a strong association between obstructive sleep apnea (OSA) and AF 6 .…”

“…There is however value in performing systematic screening for specific at-risk groups such as individuals suspected of sleep-disordered breathing, where an important association between AF and obstructive sleep apnea (OSA) has been demonstrated. We motivate the clinical relevance and feasibility for performing overnight systematic AF screening in a population sample at risk of sleep-disordered breathing (Behar 2019) with three arguments. (1) Interaction of AF with sleep-disordered breathing: there is value in performing systematic AF screening in individuals suspected of sleep-disordered breathing.…”

“…Yet, the data collected with PSG or home sleep tests gather valuable physiological measurements that extend beyond the pure traditional sleep diagnosis paradigm. In this paper we highlight the diagnostic potential of data collected during sleep for non-sleep specific conditions, a paradigm coined earlier as 'medicine during sleep' (Behar 2019). Although such novel analysis of the data may be fully automated in the distant future, it is likely, in the near future, that the data and its automated analysis will be presented to a medical doctor for review.…”