Abstract
Obstructive sleep apnea (OSA) is thought to affect almost 1 billion people worldwide. OSA has well established cardiovascular and neurocognitive sequelae, although the optimal metric to ...assess its severity and/or potential response to therapy remains unclear. The apnea-hypopnea index (AHI) is well established; thus, we review its history and predictive value in various different clinical contexts. Although the AHI is often criticized for its limitations, it remains the best studied metric of OSA severity, albeit imperfect. We further review the potential value of alternative metrics including hypoxic burden, arousal intensity, odds ratio product, and cardiopulmonary coupling. We conclude with possible future directions to capture clinically meaningful OSA endophenotypes including the use of genetics, blood biomarkers, machine/deep learning and wearable technologies. Further research in OSA should be directed towards providing diagnostic and prognostic information to make the OSA diagnosis more accessible and to improving prognostic information regarding OSA consequences, in order to guide patient care and to help in the design of future clinical trials.
Symptom subtypes have been described in clinical and population samples of patients with obstructive sleep apnea (OSA). It is unclear whether these subtypes have different cardiovascular ...consequences.
To characterize OSA symptom subtypes and assess their association with prevalent and incident cardiovascular disease in the Sleep Heart Health Study.
Data from 1,207 patients with OSA (apnea-hypopnea index ≥ 15 events/h) were used to evaluate the existence of symptom subtypes using latent class analysis. Associations between subtypes and prevalence of overall cardiovascular disease and its components (coronary heart disease, heart failure, and stroke) were assessed using logistic regression. Kaplan-Meier survival analysis and Cox proportional hazards models were used to evaluate whether subtypes were associated with incident events, including cardiovascular mortality.
Four symptom subtypes were identified (disturbed sleep 12.2%, minimally symptomatic 32.6%, excessively sleepy 16.7%, and moderately sleepy 38.5%), similar to prior studies. In adjusted models, although no significant associations with prevalent cardiovascular disease were found, the excessively sleepy subtype was associated with more than threefold increased risk of prevalent heart failure compared with each of the other subtypes. Symptom subtype was also associated with incident cardiovascular disease (
< 0.001), coronary heart disease (
= 0.015), and heart failure (
= 0.018), with the excessively sleepy again demonstrating increased risk (hazard ratios, 1.7-2.4) compared with other subtypes. When compared with individuals without OSA (apnea-hypopnea index < 5), significantly increased risk for prevalent and incident cardiovascular events was observed mostly for patients in the excessively sleepy subtype.
OSA symptom subtypes are reproducible and associated with cardiovascular risk, providing important evidence of their clinical relevance.
•Drosophila sleep is regulated by multiple neurotransmitters and intracellular signaling pathways in the brain.•Many of the identified regulators of Drosophila sleep exhibit conserved role in ...mammalian systems.•Evidence in Drosophila and across multiple species indicates that sleep functions to regulates a wide range of physiological processes.•Technical considerations of fly studies include: limitations in single-fly sleep analysis, sex differences, and brain development effects.
Sleep is a biological enigma that has raised numerous questions about the inner workings of the brain. The fundamental question of why our nervous systems have evolved to require sleep remains a topic of ongoing scientific deliberation. This question is largely being addressed by research using animal models of sleep. Drosophila melanogaster, also known as the common fruit fly, exhibits a sleep state that shares common features with many other species. Drosophila sleep studies have unearthed an immense wealth of knowledge about the neuroscience of sleep. Given the breadth of findings published on Drosophila sleep, it is important to consider how all of this information might come together to generate a more holistic understanding of sleep. This review provides a comprehensive summary of the neurobiology of Drosophila sleep and explores the broader insights and implications of how sleep is regulated across species and why it is necessary for the brain.
Abstract
Three recent randomized control trials (RCTs) found that treatment of obstructive sleep apnea (OSA) with continuous positive airway pressure (CPAP) did not reduce rates of future ...cardiovascular events. This article discusses the biases in these RCTs that may explain their negative results, and how to overcome these biases in future studies.
First, sample selection bias affected each RCT. The subjects recruited were not patients typically presenting for treatment of OSA. In particular, subjects with excessive sleepiness were excluded due to ethical concerns. As recent data indicate that the excessively sleepy OSA subtype has increased cardiovascular risk, subjects most likely to benefit from treatment were excluded. Second, RCTs had low adherence to therapy. Reported adherence is lower than found clinically, suggesting it is in part related to selection bias. Each RCT showed a CPAP benefit consistent with epidemiological studies when restricting to adherent patients, but was underpowered.
Future studies need to include sleepy individuals and maximize adherence. Since it is unethical and impractical to randomize very sleepy subjects to no therapy, alternative designs are required. Observational designs using propensity scores, which are accepted by FDA for studies of medical devices, provide an opportunity. The design needs to ensure covariate balance, including measures assessing healthy user and healthy adherer biases, between regular users of CPAP and non-users. Sensitivity analyses can evaluate the robustness of results to unmeasured confounding, thereby improving confidence in conclusions. Thus, these designs can robustly assess the cardiovascular benefit of CPAP in real-world patients, overcoming biases in RCTs.
Obstructive sleep apnea (OSA) is a worldwide disease whose prevalence is increasing as obesity rates increase. The link between obesity and OSA is likely to be the deposition of fat in the tongue, ...compromising upper airway size. The role of obesity varies in different ethnic groups, with Chinese being particularly sensitive to increases in weight. OSA lends itself to a personalized approach to diagnosis and therapy. For example, different clinical OSA subtypes likely benefit from therapy in different ways. Hypoglossal nerve stimulation is a useful second-line therapy in patients who cannot tolerate continous positive airway pressure (CPAP) machines or intraoral devices. Technological advances allow patients to participate in their own care, and doing so improves CPAP compliance. We are entering a future where we can focus efforts to predict and prevent OSA on an individual level.
Dr. Leroy Hood promotes a paradigm to advance medical care that he calls P4 medicine. The four Ps are: personalized, predictive, preventative, and participatory. P4 medicine encourages a convergence ...of systems medicine, the digital revolution, and consumer-driven healthcare. Might P4 medicine be applicable to obstructive sleep apnea (OSA)? OSA should be personalized in that there are different structural and physiological pathways to disease. Obesity is a major risk factor. The link between obesity and OSA is likely to be fat deposits in the tongue compromising the upper airway. Clinical features at presentation also vary between patients. There are three distinct subgroups: (1) patients with a primary complaint of insomnia, (2) relatively asymptomatic patients with a high prevalence of cardiovascular comorbidities, and (3) excessively sleepy patients. Currently, there have been limited efforts to identify subgroups of patients on the basis of measures obtained by polysomnography. Yet, these diagnostic studies likely contain considerable predictive information. Likewise, there has currently been limited application of -omic approaches. Determining the relative role of obesity and OSA for particular consequences is challenging, because they both affect the same molecular pathways. There is evidence that the effects of OSA are modified by the level of obesity. These insights may lead to improvements in predicting outcomes to personalized therapies. The final P-participatory-is ideally suited to OSA, with technology to obtain extensive data remotely from continuous positive airway pressure machines. Providing adherence data directly to patients increases their use of continuous positive airway pressure. Thus, the concept of P4 medicine is very applicable to obstructive sleep apnea and can be the basis for future research efforts.
Although commonly observed in clinical practice, the heterogeneity of obstructive sleep apnoea (OSA) clinical presentation has not been formally characterised. This study was the first to apply ...cluster analysis to identify subtypes of patients with OSA who experience distinct combinations of symptoms and comorbidities. An analysis of baseline data from the Icelandic Sleep Apnoea Cohort (822 patients with newly diagnosed moderate-to-severe OSA) was performed. Three distinct clusters were identified. They were classified as the "disturbed sleep group" (cluster 1), "minimally symptomatic group" (cluster 2) and "excessive daytime sleepiness group" (cluster 3), consisting of 32.7%, 24.7% and 42.6% of the entire cohort, respectively. The probabilities of having comorbid hypertension and cardiovascular disease were highest in cluster 2 but lowest in cluster 3. The clusters did not differ significantly in terms of sex, body mass index or apnoea-hypopnoea index. Patients with OSA have different patterns of clinical presentation, which need to be communicated to both the lay public and the professional community with the goal of facilitating care-seeking and early identification of OSA. Identifying distinct clinical profiles of OSA creates a foundation for offering more personalised therapies in the future.
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