Variability of respiratory mechanics during sleep in overweight and obese subjects with and without asthma

REM-OSA as a Tool to Understand Both the Architecture of Sleep and Pathogenesis of Sleep Apnea-Literature Review

Sleep is a complex physiological state, which can be divided into the non-rapid eye movement (NREM) phase and the REM phase. Both have some unique features and functions. This difference is best visible in electroencephalography recordings, respiratory system activity, arousals, autonomic nervous system activity, or metabolism. Obstructive sleep apnea (OSA) is a common condition characterized by recurrent episodes of pauses in breathing during sleep caused by blockage of the upper airways. This common condition has multifactorial ethiopathogenesis (e.g., anatomical predisposition, sex, obesity, and age). Within this heterogenous syndrome, some distinctive phenotypes sharing similar clinical features can be recognized, one of them being REM sleep predominant OSA (REM-OSA). The aim of this review was to describe the pathomechanism of REM-OSA phenotype, its specific clinical presentation, and its consequences. Available data suggest that in this group of patients, the severity of specific cardiovascular and metabolic complications is increased. Due to the impact of apneas and hypopneas predominance during REM sleep, patients are more prone to develop hypertension or glucose metabolism impairment. Additionally, due to the specific function of REM sleep, which is predominantly fragmented in the REM-OSA, this group presents with decreased neurocognitive performance, reflected in memory deterioration, and mood changes including depression. REM-OSA clinical diagnosis and treatment can alleviate these outcomes, surpassing the traditional treatment and focusing on a more personalized approach, such as using longer therapy of continuous positive airway pressure or oral appliance use.

The Constrained Disorder Principle Accounts for the Variability That Characterizes Breathing: A Method for Treating Chronic Respiratory Diseases and Improving Mechanical Ventilation

Variability characterizes breathing, cellular respiration, and the underlying quantum effects. Variability serves as a mechanism for coping with changing environments; however, this hypothesis does not explain why many of the variable phenomena of respiration manifest randomness. According to the constrained disorder principle (CDP), living organisms are defined by their inherent disorder bounded by variable boundaries. The present paper describes the mechanisms of breathing and cellular respiration, focusing on their inherent variability. It defines how the CDP accounts for the variability and randomness in breathing and respiration. It also provides a scheme for the potential role of respiration variability in the energy balance in biological systems. The paper describes the option of using CDP-based artificial intelligence platforms to augment the respiratory process's efficiency, correct malfunctions, and treat disorders associated with the respiratory system.

Perspectives of patients and healthcare professionals on mHealth for asthma self-management

Mobile healthcare (mHealth) has the potential to revolutionise the self-management of long-term medical conditions such as asthma. A user-centred design is integral if mHealth is to be embraced by patients and healthcare professionals.The aim of this study was to determine the perspectives of individuals with asthma and healthcare professionals on the use of mHealth for asthma self-management.We used a sequential exploratory mixed methods design; focus groups informed the development of questionnaires, which were disseminated to individuals with asthma and healthcare professionals.Focus group participants (18 asthma patients and five healthcare professionals) identified 12 potential uses of mHealth. Questionnaire results showed that individuals with asthma (n=186) most frequently requested an mHealth system to monitor asthma over time (72%) and to collect data to present to healthcare teams (70%). In contrast, healthcare professionals (n=63) most frequently selected a system alerting patients to deteriorating asthma control (86%) and advising them when to seek medical attention (87%). Individuals with asthma were less likely than healthcare professionals (p<0.001) to believe that assessing medication adherence and inhaler technique could improve asthma control.Our data provide strong support for mHealth for asthma self-management, but highlight fundamental differences between the perspectives of patients and healthcare professionals.

MyAirCoach: the use of home-monitoring and mHealth systems to predict deterioration in asthma control and the occurrence of asthma exacerbations; study protocol of an observational study

INTRODUCTION

Asthma is a variable lung condition whereby patients experience periods of controlled and uncontrolled asthma symptoms. Patients who experience prolonged periods of uncontrolled asthma have a higher incidence of exacerbations and increased morbidity and mortality rates. The ability to determine and to predict levels of asthma control and the occurrence of exacerbations is crucial in asthma management. Therefore, we aimed to determine to what extent physiological, behavioural and environmental data, obtained by mobile healthcare (mHealth) and home-monitoring sensors, as well as patient characteristics, can be used to predict episodes of uncontrolled asthma and the onset of asthma exacerbations.

METHODS AND ANALYSIS

In an 1-year observational study, patients will be provided with mHealth and home-monitoring systems to record daily measurements for the first-month (phase I) and weekly measurements during a follow-up period of 11 months (phase II). Our study population consists of 150 patients, aged ≥18 years, with a clinician's diagnosis of asthma, currently on controller medication, with uncontrolled asthma and/or minimally one exacerbation in the past 12 months. They will be enrolled over three participating centres, including Leiden, London and Manchester. Our main outcomes are the association between physiological, behavioural and environmental data and (1) the loss of asthma control and (2) the occurrence of asthma exacerbations.

ETHICS

This study was approved by the Medical Ethics Committee of the Leiden University Medical Center in the Netherlands and by the NHS ethics service in the UK.

TRIAL REGISTRATION NUMBER

NCT02774772.

Correlated variability in the breathing pattern and end-expiratory lung volumes in conscious humans

In order to characterize the variability and correlation properties of spontaneous breathing in humans, the breathing pattern of 16 seated healthy subjects was studied during 40 min of quiet breathing using opto-electronic plethysmography, a contactless technology that measures total and compartmental chest wall volumes without interfering with the subjects breathing. From these signals, tidal volume (V_T), respiratory time (T_TOT) and the other breathing pattern parameters were computed breath-by-breath together with the end-expiratory total and compartmental (pulmonary rib cage and abdomen) chest wall volume changes. The correlation properties of these variables were quantified by detrended fluctuation analysis, computing the scaling exponentα. V_T, T_TOT and the other breathing pattern variables showed α values between 0.60 (for minute ventilation) to 0.71 (for respiratory rate), all significantly lower than the ones obtained for end-expiratory volumes, that ranged between 1.05 (for rib cage) and 1.13 (for abdomen) with no significant differences between compartments. The much stronger long-range correlations of the end expiratory volumes were interpreted by a neuromechanical network model consisting of five neuron groups in the brain respiratory center coupled with the mechanical properties of the respiratory system modeled as a simple Kelvin body. The model-based α for V_T is 0.57, similar to the experimental data. While the α for T_TOT was slightly lower than the experimental values, the model correctly predicted α for end-expiratory lung volumes (1.045). In conclusion, we propose that the correlations in the timing and amplitude of the physiological variables originate from the brain with the exception of end-expiratory lung volume, which shows the strongest correlations largely due to the contribution of the viscoelastic properties of the tissues. This cycle-by-cycle variability may have a significant impact on the functioning of adherent cells in the respiratory system.