Struggling with comorbid sleep disturbances: insights from the ELSA-Brasil study

The initial classification of sleep disorders were reported in 19th century using three categories: insomnia, hypersomnia and nightmare. In the following century (mainly in the last half of it), technological discoveries led to rapid advances in the understanding of sleep and recognition of several sleep disorders. Nowadays, the three systems of classification in use worldwide include the International Classification of Diseases (ICD, developed by World Health Organization), the Diagnostic and Statistical Manual of Mental Disorders (DSM, from the American Psychiatric Association) and the International Classification of Sleep Disorders (ICSD, produced by the American Academy of Sleep Medicine)[1] ^- [3]. All three systems had different strategies of sleep disorders classification with some confluence, but they are unanimous to present a huge number of sleep disorders in the humankind. Currently, there are more than 83 sleep disorders challenging not only sleep specialists but also non-specialists, frequently facing sleep issues in their clinical practice.

From the research perspective, we traditionally addressed sleep disorders as distinct compartments ([Figure 1]). Using this approach, considerable advancements were made in the last decades to understanding the major health consequences of sleep deprivation, long sleep duration, insomnia, sleep disordered breathing including obstructive sleep apnea (OSA), circadian disorders, sleep-related movement disorders, narcolepsy, parasomnias, etc. This traditional view made significant contributions for each sleep condition highlighting a myriad of consequences that made sleep an interdisciplinary area.

Figure 1 Classical view of the clinical approach of sleep disorders.

Despite the advances, researchers overseas are facing heterogeneous clinical presentations and prognosis related to each of the sleep disorders. For instance, even patients with severe OSA may not be at risk of cardiovascular events. Recent investigations pointed out that particular signatures such as daytime sleepiness[4] or higher burden of hypoxia[5] are more susceptible to the cardiovascular consequences than non-sleepy or OSA patients with mild hypoxia during sleep. In this complex scenario, a lot of attention has been devoted to explore potential phenotypes and biomarkers that predicts risk and response to therapies[6] ^- [8].

Publication History

Received: 01 June 2020

Accepted: 10 June 2020

Article published online:
09 November 2023

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