Research from JAMA — CPAP vs Mandibular Advancement Devices and Blood Pressure in Patients With Obstructive Sleep Apnea — A Systematic Review and Meta-analysis

Background It is current practice to use a single diagnostic sleep study in the diagnostic workup of obstructive sleep apnoea (OSA). However, a relevant night-to-night variability (NtNV) of respiratory events has been reported. Methods We evaluated the NtNV of respiratory events in adults with suspected or already diagnosed OSA who underwent more than one diagnostic sleep study. Data sources were PubMed, Cochrane and Embase up to 23 January 2019. Random-effects models were used for evidence synthesis. For moderator analysis, mixed-effects regression analysis was performed. The study was registered with PROSPERO (CRD42019135277). Results Of 2143 identified papers, 24 studies, comprising 3250 participants, were included. The mean Apnoea-Hypopnoea Index (AHI) difference between the first and second night was −1.70/hour (95% CI −3.61 to 0.02). REM time differences (first to second night) were significantly positive associated with differences in mean AHI (β coefficient 0.262 (95% CI 0.096 to 0.428). On average, 41% (95% CI 27% to 57%) of all participants showed changes of respiratory events >10/hour from night to night. Furthermore, 49% (95% CI 32% to 65%) of participants changed OSA severity class (severity thresholds at 5/hour, 15/hour and 30/hour) at least once in sequential sleep studies. Depending on the diagnostic threshold (5/hour, 10/hour or 15/hour), on average 12% (95% CI 9% to 15%), 12% (95% CI 8% to 19%) and 10% (95% CI 8% to 13%) of patients would have been missed during the first night due to single night testing. Conclusion While there was no significant difference between mean AHI in two sequential study nights on a group level, there was a remarkable intraindividual NtNV of respiratory events, leading to misdiagnosis and misclassification of patients with suspected OSA.

Obstructive sleep apnoea (OSA) has been shown to be a causal factor in the pathogenesis of vascular dysfunction and hypertension, conditions which can promote dilation and subsequent aortic dissection and rupture. The objective of this review is to summarise the current literature on the possible association between OSA and aortic disease and delineate the underlying mechanisms.Relevant studies were found by searching for terms including “obstructive sleep apnoea” in combination with “aortic aneurysm, dissection, and dilation” in the MEDLINE and EMBASE databases.Observational studies consistently reported that OSA is highly prevalent among patients with aortic aneurysms and aortic dissections. Patients with co-occurring OSA and Marfan's syndrome as well as patients at the more severe end of the spectrum of OSA seem to be especially vulnerable to aortic disease.Several mechanisms are discussed concerning the link between OSA and aortic disease: nocturnal negative intrathoracic pressure surges leading to mechanical stretching of the aorta and ultimately aortic distension; arousal-induced reflex sympathetic activation with subsequent hypertension; and intermittent hypoxia associated with autonomic nervous system activation and consequently increased oxidative stress. Further well controlled studies are needed in order to define the exact role of OSA as a risk factor for aortic disease.

New mass spectrometry (MS) techniques analysing exhaled breath have the potential to better define airway diseases. Here, we present our work to profile the volatile organic compounds (VOCs) in exhaled breath from patients with chronic obstructive pulmonary disease (COPD), using real-time MS, and relate this disease-specific breath profile to functional disease markers. In a matched cohort study, patients with COPD, according to GOLD criteria, were recruited. Exhaled breath analysis by untargeted MS was performed using secondary electrospray ionization – high-resolution MS (SESI-HRMS). Exhaled breath from 22 patients with COPD (mean age 58.6 ± 6.9 years, FEV₁ 58.5 ± 19.9% predicted, 32.4 ± 19.2 pack years smoking) and 14 controls (mean age 58.1 ± 8.1 years, FEV₁ 102.5 ± 11.3% predicted, 23.6 ± 12.5 pack years smoking) was analysed using SESI-HRMS. From 1441 different features, 43 markers were identified that allowed discrimination between the two groups with an accuracy of 89% (CI 74–97%), a sensitivity of 93%, and a specificity of 86%. The markers were determined to be metabolites of oxidative stress processes, such as fatty acids, aldehydes and amino acids, resulting from lung muscle degradation. Real-time breath analysis by SESI-MS allows molecular profiling of exhaled breath, can distinguish patients with COPD from matched healthy controls and provides insights into the disease pathogenesis.

Sleep is crucial to restore body functions and metabolism across nearly all tissues and cells, and sleep restriction is linked to various metabolic dysfunctions in humans. Using exhaled breath analysis by secondary electrospray ionization high-resolution mass spectrometry, we measured the human exhaled metabolome at 10-s resolution across a night of sleep in combination with conventional polysomnography. Our subsequent analysis of almost 2,000 metabolite features demonstrates rapid, reversible control of major metabolic pathways by the individual vigilance states. Within this framework, whereas a switch to wake reduces fatty acid oxidation, a switch to slow-wave sleep increases it, and the transition to rapid eye movement sleep results in elevation of tricarboxylic acid (TCA) cycle intermediates. Thus, in addition to daily regulation of metabolism, there exists a surprising and complex underlying orchestration across sleep and wake. Both likely play an important role in optimizing metabolic circuits for human performance and health.