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Abstract Study Objectives In-laboratory polysomnography is the current gold standard for objective sleep measurements in clinical trials, but this does not capture night-to-night variability in sleep parameters. This study analyzed variability in sleep parameters recorded over multiple nights of sleep in an ecological setting using a portable sleep monitor and then estimated the minimum sample sizes required to reliably account for inter- and intra-individual variability in sleep parameters. Methods Participants were males who self-reported the absence of sleep disorders, and used a sleep monitoring device (Dreem Headband, Dreem, France) over multiple nights of sleep. Night-to-night variability of sleep parameters was determined over five consecutive weeknights using coefficients of variation (CV), and the minimal number of individuals and nights needed to reliably determine each sleep parameter was assessed. Results Night-to-night variability for the whole group (n = 94; 470 nights) was high (CV 0.44–0.58) for N2, N3, sleep onset and persistent sleep latencies, and wake after sleep onset (WASO), medium (CV 0.22–0.28) for N1 and N3 percentage, awakenings and REM latency, and low (CV 0.04–0.19) for sleep efficiency, N2 and REM percentages, total sleep time (TST) and micro-arousal index. Minimum sample sizes for reliable assessment of TST and WASO were 2 nights with 10 participants and 4 nights with 50 participants, respectively. Conclusions Night-to-night variability of sleep parameters is underestimated and under-recognized. These data on variability in commonly used sleep parameters will facilitate better estimation of sample sizes and number of nights required in clinical trials based on the outcomes of interest. Graphical Abstract Graphical Abstract

The classification of obstructive sleep apnea is on the basis of sleep study criteria that may not adequately capture disease heterogeneity. Improved phenotyping may improve prognosis prediction and help select therapeutic strategies. This study used cluster analysis to investigate the clinical clusters of obstructive sleep apnea. An ascending hierarchical cluster analysis was performed on baseline symptoms, physical examination, risk factor exposure and co-morbidities from 18,263 participants in the OSFP (French national registry of sleep apnea). The probability for criteria to be associated with a given cluster was assessed using odds ratios, determined by univariate logistic regression. Six clusters were identified, in which patients varied considerably in age, sex, symptoms, obesity, co-morbidities and environmental risk factors. The main significant differences between clusters were minimally symptomatic versus sleepy obstructive sleep apnea patients, lean versus obese, and among obese patients different combinations of co-morbidities and environmental risk factors. Our cluster analysis identified six distinct clusters of obstructive sleep apnea. Our findings underscore the high degree of heterogeneity that exists within obstructive sleep apnea patients regarding clinical presentation, risk factors and consequences. This may help in both research and clinical practice for validating new prevention programs, in diagnosis and in decisions regarding therapeutic strategies.

Study Objectives: There is a lack of data regarding adherence trajectories when switching from continuous positive airway pressure (CPAP) to adaptive servoventilation (ASV) in the context of persistent or treatment-emergent central sleep apnea (CSA). This study investigated 90-day adherence rates in patients with sleep apnea based on the type of positive airway pressure (PAP) device used and any switching of PAP modality over time. Methods: Telemonitoring data were obtained from a United States PAP database. Eligible patients were a 30% random sample who started PAP, plus all who started ASV, from January 1, 2015 to October 2, 2015. All received PAP and had at least one session with usage of 1 hour or more. Adherence and device usage were determined in three groups: started on CPAP and stayed on CPAP (CPAP only); started on ASV and stayed on ASV (ASV only); started on CPAP, switched to ASV (Switch). The United States Medicare definition of adherence was used. Results: The study included 198,890 patients; 189,724 (CPAP only), 8,957 (ASV only) and 209 (Switch). In the Switch group, average apnea-hypopnea index decreased significantly on ASV versus CPAP. At 90 days, adherence rates were 73.8% and 73.2% in the CPAP only and ASV only groups. In the Switch group, CPAP adherence was 62.7%, improving to 76.6% after the switch to ASV. Mean device usage at 90 days was 5.27, 5.31, and 5.73 h/d in the CPAP only, ASV only, and Switch groups, respectively. Conclusions: Treatment-emergent or persistent CSA during CPAP reduced therapy adherence, but adherence improved early after switching from CPAP to ASV. Citation: Pépin JL, Woehrle H, Liu D, Shao S, Armitstead JP, Cistulli PA, Benjafield AV, Malhotra A. Adherence to positive airway therapy after switching from CPAP to ASV: a big data analysis. J Clin Sleep Med. 2018;14(1):57–63.

More advanced knowledge is needed on how COPD alters the clinical presentation of obstructive sleep apnea (OSA) and how the association of both diseases, known as 'overlap syndrome' (OVS), impacts on cardiovascular health. To investigate differences between patients with OVS and those with moderate-to-severe OSA alone. A cross-sectional study conducted in the French National Sleep Apnea Registry between January 1997 and January 2017. Univariable and multivariable logistic regression models were used to compare OVS versus OSA alone on symptoms and cardiovascular health. 46,786 patients had moderate-to-severe OSA. Valid spirometry was available for 16,466 patients: 14,368 (87%) had moderate-to-severe OSA alone and 2098 (13%) had OVS. A lower proportion of OVS patients complained of snoring, morning headaches and excessive daytime sleepiness compared to OSA alone (median Epworth Sleepiness Scale score: 9 [interquartile range (IQR) 6-13] versus 10 (IQR 6-13), respectively; P <0.02). Similarly, a lower proportion of OVS patients (35.6% versus 39.4%, respectively; P <0.01) experienced sleepiness while driving. In contrast, 63.5% of the OVS population experienced nocturia compared to 58.0% of the OSA population (P<0.01). Apnea hypopnea index (36 [25; 52] vs 33.1 [23.3; 50]), oxygen desaturation index (28 [15; 48] vs 25.2 [14; 45]) and mean nocturnal SaO2 (92 [90; 93.8] vs 93 [91.3; 94]) were significantly more altered in the OVS group. Associated COPD had no effect on the prevalence of hypertension and stroke. After controlling for main confounders, COPD severity was associated in a dose-response relationship with a higher prevalence of coronary heart disease, heart failure and peripheral arteriopathy. In adults with moderate-to-severe OSA, OVS was minimally symptomatic, but exhibited higher odds for prevalent coronary heart disease, heart failure and peripheral arteriopathy.

Data from women (n = 305, aged 43 [34; 53] years-old, BMI 44.2 [40.8; 48.2] kg/m2) included in the Severe Obesity Outcome Network (SOON) cohort were analyzed (i) to evaluate collinearity between the different anthropometric markers, (ii) to compare the association of markers with hypertension, type 2 diabetes, obstructive sleep apnea syndrome (OSAS) and other cardiometabolic risks. Hip, waist and neck circumferences correlated with BMI with respectively less collinearity (r = 0.70, r = 0.59 and r = 0.37, respectively, p<0.001) whereas waist-to-hip ratio was not correlated (r = 0.11, p = 0.072). Waist and neck circumferences were significantly associated with hypertension, type 2 diabetes and OSAS in univariate logistic regressions, waist-to-hip ratio with hypertension and type 2 diabetes. Hip circumference was inversely correlated with type 2 diabetes (OR 0.970 (95CI: 0.948; 0.991) p = 0.006). BMI was only linked to OSAS (OR 1.092 (95CI: 1.043; 1.143) p<0.001). Neck circumference was the only marker significantly associated with all cardiometabolic risk markers (HOMA-IR, apnea-hypopnea index, Log Triglycerides/HDL-c, alanin-aminotransferase, aspartate-aminotransferase, gammaglutamyl transpeptidase). Neck circumference appears the most appropriate anthropometric marker to identify the fat distribution associated with high cardiometabolic risk in women with severe obesity.

The association between obstructive sleep apnea (OSA) and cardiovascular morbidity and mortality is largely the result of myocardial anomalies. In this Review, the authors discuss the mechanisms that lead to myocardial damage and cardiac dysfunction in patients with OSA, and the potential beneficial effects of nasal continuous positive airway pressure on cardiac symptoms and hemodynamic parameters in these patients. Obstructive sleep apnea (OSA) is associated with cardiovascular morbidity and mortality, largely as a result of myocardial anomalies. Numerous mechanisms cause OSA-related myocardial damage. The majority are initiated as a result of OSA-induced, chronic, intermittent hypoxia. The most-important mechanisms that lead to myocardial damage are increased sympathetic activity, endothelial dysfunction, systemic inflammation, oxidative stress, and metabolic anomalies. All these mechanisms promote the development of hypertension, which is common in patients with OSA. Hypertensive cardiomyopathy and coronary heart disease, as well as obesity-related, diabetic, and tachycardia-induced cardiomyopathies, are also associated with OSA. Left ventricular hypertrophy, myocardial fibrosis, atrial dilatation, and left ventricular systolic and diastolic dysfunction in patients with OSA explain the association of the disease with these clinical outcomes. The gold-standard treatment for OSA, nasal continuous positive airway pressure (CPAP), might improve cardiac symptoms and hemodynamic parameters in patients with the disease. However, large clinical trials are required to improve our understanding of the cardiac consequences of OSA, and determine the effect of treatment, particularly CPAP, on myocardial damage in symptomatic patients and primary prevention of cardiovascular disorders. Key Points Obstructive sleep apnea (OSA) causes chronic, intermittent hypoxia, which leads to an increase in sympathetic activity, endothelial dysfunction, systemic inflammation, oxidative stress, metabolic anomalies, and myocardial damage Hypertension is common in patients with OSA Hypertensive cardiomyopathy, coronary heart disease, and obesity-related, diabetic, and tachycardia-induced cardiomyopathies are associated with OSA The main myocardial anomalies observed during OSA are left ventricular hypertrophy, myocardial fibrosis, and atrial dilatation Nasal continuous positive airway pressure (CPAP) could improve cardiac symptoms and hemodynamic parameters in patients with OSA Large clinical trials are needed to determine the impact of CPAP treatment on myocardial damage in patients with OSA

The progression of chronic obstructive pulmonary disease (COPD) is characterized by episodes of acute exacerbation (AECOPD) of symptoms, decline in respiratory function, and reduction in quality-of-life increasing morbi-mortality and often requiring hospitalization. Exacerbations can be triggered by environmental exposures, changes in lifestyle, and/or physiological and psychological factors to greater or lesser extents depending on the individual’s COPD phenotype. The prediction and early detection of an exacerbation might allow patients and physicians to better manage the acute phase. We summarize the recent scientific data on remote telemonitoring (TM) for the prediction and management of acute exacerbations in COPD patients. We discuss the components of remote monitoring platforms, including the integration of environmental monitoring data; patient reported outcomes collected via interactive Smartphone apps, with data from wearable devices that monitor physical activity, heart rate, etc.; and data from medical devices such as connected non-invasive ventilators. We consider how telemonitoring and the deluge of data it potentially generates could be combined with electronic health records to provide personalized care and multi-disease management for COPD patients.

Abstract Background Overweight/obesity is a common, reversible risk factor for obstructive sleep apnea severity (OSA). The purpose of this guideline is to provide evidence-based recommendations for the management of overweight/obesity in patients with OSA. Methods The Grading of Recommendations, Assessment, Development and Evaluation approach was used to evaluate the literature. Clinical recommendations were formulated by a panel of pulmonary, sleep medicine, weight management, and behavioral science specialists. Results Behavioral, pharmacological, and surgical treatments promote weight loss and can reduce OSA severity, reverse common comorbidities, and improve quality of life, although published studies have methodological limitations. After considering the quality of evidence, feasibility, and acceptability of these interventions, the panel made a strong recommendation that patients with OSA who are overweight or obese be treated with comprehensive lifestyle intervention consisting of 1) a reduced-calorie diet, 2) exercise or increased physical activity, and 3) behavioral guidance. Conditional recommendations were made regarding reduced-calorie diet and exercise/increased physical activity as separate management tools. Pharmacological therapy and bariatric surgery are appropriate for selected patients who require further assistance with weight loss. Conclusions Weight-loss interventions, especially comprehensive lifestyle interventions, are associated with improvements in OSA severity, cardiometabolic comorbidities, and quality of life. The American Thoracic Society recommends that clinicians regularly assess weight and incorporate weight management strategies that are tailored to individual patient preferences into the routine treatment of adult patients with OSA who are overweight or obese.

Background Dyspnea is one of the most common symptoms in the post-acute phase of COVID-19 pneumonia. Conventional pulmonary function tests and computed tomography (CT) scores often fail to show correlation with symptom severity, highlighting the need for more sensitive imaging biomarkers. Machine-learning–based quantitative CT analysis and parametric response mapping (PRM) can capture subtle structural and functional abnormalities that may be associated with persistent dyspnea. Methods We analyzed inspiratory and paired inspiratory–expiratory CT scans of early (3–6 months) post-COVID-19 pneumonia patients. Inspiratory CT images were segmented using a random forest algorithm to quantify lung parenchymal patterns. Paired inspiratory/expiratory scans were co-registered to derive ventilation metrics and PRM-defined functional small airway disease (fSAD), emphysema, emptying emphysema, and normal lung. Associations between imaging metrics and patient-reported dyspnea assessed by a visual analogue scale (VAS) were evaluated using univariable and multivariable linear regression, with adjustment for age, sex, BMI, and smoking history. Results One hundred twenty-three patients had usable inspiratory CT scans, and 116 patients had paired inspiratory/expiratory scans of sufficient quality for analysis. In the adjusted multivariable models, greater PRM-defined functional small airway disease (fSAD) was positively associated with dyspnea (standardized β = 1.21, p  = 0.002). Moreover, a lower standard deviation of dense ground-glass attenuation in the left lung (standardized β = −0.82, p  = 0.033) and greater total volume of dense ground-glass opacities (standardized β = 0.71, p  = 0.033) were independently associated with dyspnea. Conclusions In early post-COVID-19 pneumonia, machine-learning–based CT pattern recognition and PRM revealed that functional small airway disease, and the total volume and heterogeneity of lung dense ground-glass opacities are significantly associated with persistent dyspnea. These findings highlight the potential of quantitative CT to identify pulmonary imaging biomarkers relevant to long COVID symptom burden. Trial registration ClinicalTrials.gov (NCT04406324).

The symptomatic response to continuous positive airway pressure (CPAP) therapy in COPD-obstructive sleep apnea overlap syndrome (OVS) compared to OSA syndrome (OSA) alone has not been well studied so far. The aim of this study is to explore main differences in the clinical response to CPAP treatment in OVS compared to OSA alone. Using prospective data from the French National Sleep Apnea Registry, we conducted an observational study among 6320 patients with moderate-to-severe OSA, available spirometry, and at least one follow-up visit under CPAP therapy. CPAP efficacy measured on the residual apnea-hypopnea index and median adherence were similar between OVS and OSA patients. In both groups, the overall burden of symptoms related to sleep apnea improved with CPAP treatment. In a multivariable model adjusted for age, gender, body mass index, adherence to treatment and residual apnea-hypopnea index, OVS was associated with higher odds for persistent morning headaches (OR: 1.37 [95% CI; 1.04; 1.79]; P = 0.02), morning tiredness (OR: 1.33 [95% CI: 1.12; 1.59]; P<0.01), daytime sleepiness (OR; 1.24 [95% CI: 1.4; 1.46]: P<0.01) and exertional dyspnea (OR: 1.26 [95% CI: 1.00;1.58]; P = 0.04) when compared with OSA alone. CPAP therapy was effective in normalizing the apnea-hypopnea index and significantly improved OSA-related symptoms, regardless of COPD status. CPAP should be offered to patients with OVS on a trial basis as a significant improvement in OSA-related symptoms can be expected, although the range of response may be less dramatic than in OSA alone.