ABSTRACT
Sleep apnoea is now regarded as a highly prevalent systemic, multimorbid, chronic disease requiring a combination of long‐term home‐based treatments. Optimization of personalized treatment ...strategies requires accurate patient phenotyping. Data to describe the broad variety of phenotypes can come from electronic health records, health insurance claims, socio‐economic administrative databases, environmental monitoring, social media, etc. Connected devices in and outside homes collect vast amount of data amassed in databases. All this contributes to ‘Big Data’ that, if used appropriately, has great potential for the benefit of health, well‐being and therapeutics. Sleep apnoea is particularly well placed with regards to Big Data because the primary treatment is positive airway pressure (PAP). PAP devices, used every night over long periods by millions of patients across the world, generate an enormous amount of data. In this review, we discuss how different types of Big Data have, and could be, used to improve our understanding of sleep‐disordered breathing, to identify undiagnosed sleep apnoea, to personalize treatment and to adapt health policies and better allocate resources. We discuss some of the challenges of Big Data including the need for appropriate data management, compilation and analysis techniques employing innovative statistical approaches alongside machine learning/artificial intelligence; closer collaboration between data scientists and physicians; and respect of the ethical and regulatory constraints of collecting and using Big Data. Lastly, we consider how Big Data can be used to overcome the limitations of randomized clinical trials and advance real‐life evidence‐based medicine for sleep apnoea.
Find the whole series here
Central illustration: Mechanisms involved in deleterious consequences of obstructive sleep apnoea (OSA). Intermittent hypoxia (IH) leads to sympathetic nervous system overactivity, inflammation, ...oxidative stress and endoplasmic reticulum stress. Hypoxia-inducible factor-1 (HIF-1) seems to play a major role in OSA and IH consequences. Mitochondrial integrity could also be an interesting target to explain OSA-associated pathologies. Adapted from 61. ▪
Obstructive sleep apnoea syndrome is a growing health concern, affecting nearly one billion people worldwide; it is an independent cardiovascular risk factor, associated with incident obesity, insulin resistance, hypertension, arrhythmias, stroke, coronary artery disease and heart failure. Obstructive sleep apnoea-related cardiovascular and metabolic co-morbidities are a major concern for prognosis and the complexity of obstructive sleep apnoea integrated care. Continuous positive airway pressure, the first-line therapy for the treatment of obstructive sleep apnoea, is highly effective at improving symptoms and quality of life, but has limited effect on co-morbidities. Deciphering the molecular pathways involved in obstructive sleep apnoea metabolic and cardiovascular consequences is a priority to make new pharmacological targets available, in combination with or as an alternative to continuous positive airway pressure. Intermittent hypoxia, a landmark feature of obstructive sleep apnoea, is the key intermediary mechanism underlying metabolic and cardiovascular complications. Experimental settings allowing intermittent hypoxia exposure in cells, rodents and healthy humans have been established to dissect the molecular mechanisms of obstructive sleep apnoea-related co-morbidities. The main objective of this review is to recapitulate the molecular pathways, cells and tissue interactions contributing to the cardiometabolic consequences of intermittent hypoxia. Sympathetic activation, low-grade inflammation, oxidative stress and endoplasmic reticulum stress are triggered by intermittent hypoxia and play a role in cardiometabolic dysfunction. The key role of hypoxia-inducible factor-1 transcription factor will be detailed, as well as the underestimated and less described importance of mitochondrial functional changes in the intermittent hypoxia setting.
Le syndrome d’apnées obstructives du sommeil (SAOS) affecte un milliard de personnes dans le monde. Le SAOS est un facteur de risque indépendant de la survenue d’évènements cardiovasculaires tels que l’hypertension, les troubles du rythme et les pathologies coronariennes. Le SAOS est aussi associé à des troubles du métabolisme tels que l’obésité et l’insulino-résistance. Le traitement de référence du SAOS, la pression positive continue (PPC) est un traitement qui améliore la qualité de vie des patients mais qui a un effet limité sur les comorbidités associées au SAOS. Ainsi, la compréhension des mécanismes à l’origine des conséquences cardiovasculaires et métaboliques du SAOS est un enjeu majeur et ce, afin de proposer de nouvelles cibles thérapeutiques complémentaires ou alternatives à la PPC. Les expériences pré-cliniques ont pour objectifs d’appliquer l’hypoxie intermittente (HI) chez le sujet sain, le rongeur ou encore la cellule afin de décortiquer les mécanismes sous-jacents. À ce jour, les mécanismes induits par l’HI et reconnus comme étant contributeurs des pathologies cardiométaboliques associées au SAOS sont : l’hyper-activation sympathique, l’inflammation de bas grade, le stress oxydant ou encore le stress du réticulum endoplasmique. Dans cette revue, en interaction avec les mécanismes suscités, le rôle central du facteur de transcription induit par l’hypoxie, l’hypoxia inducible factor-1 sera abordé. Par ailleurs, l’altération potentielle structurale et/ou fonctionnelle mitochondriale sera évoquée en tant que nouvelle perspective d’exploration.
Obesity hypoventilation syndrome (OHS) is defined as a combination of obesity (body mass index ≥30 kg·m
), daytime hypercapnia (arterial carbon dioxide tension ≥45 mmHg) and sleep disordered ...breathing, after ruling out other disorders that may cause alveolar hypoventilation. OHS prevalence has been estimated to be ∼0.4% of the adult population. OHS is typically diagnosed during an episode of acute-on-chronic hypercapnic respiratory failure or when symptoms lead to pulmonary or sleep consultation in stable conditions. The diagnosis is firmly established after arterial blood gases and a sleep study. The presence of daytime hypercapnia is explained by several co-existing mechanisms such as obesity-related changes in the respiratory system, alterations in respiratory drive and breathing abnormalities during sleep. The most frequent comorbidities are metabolic and cardiovascular, mainly heart failure, coronary disease and pulmonary hypertension. Both continuous positive airway pressure (CPAP) and noninvasive ventilation (NIV) improve clinical symptoms, quality of life, gas exchange, and sleep disordered breathing. CPAP is considered the first-line treatment modality for OHS phenotype with concomitant severe obstructive sleep apnoea, whereas NIV is preferred in the minority of OHS patients with hypoventilation during sleep with no or milder forms of obstructive sleep apnoea (approximately <30% of OHS patients). Acute-on-chronic hypercapnic respiratory failure is habitually treated with NIV. Appropriate management of comorbidities including medications and rehabilitation programmes are key issues for improving prognosis.
Abstract Obstructive sleep apnea (OSA) and more importantly its hallmark chronic intermittent hypoxia (CIH), are established factors in the pathogenesis and exacerbation of nonalcoholic fatty liver ...disease (NAFLD). This has been clearly demonstrated in rodent models exposed to intermittent hypoxia, and strong evidence now also exists in both paediatric and adult human populations. OSA and CIH induce insulin-resistance and dyslipidemia which are involved in NAFLD physiopathogenesis. CIH increases the expression of the hypoxia inducible transcription factor HIF1α and that of downstream genes involved in lipogenesis, thereby increasing β-oxidation and consequently exacerbating liver oxidative stress. OSA also disrupts the gut liver axis, increasing intestinal permeability and with a possible role of gut microbiota in the link between OSA and NAFLD. OSA patients should be screened for NAFLD and vice versa those with NAFLD for OSA. To date there is no evidence that treating OSA with continuous positive airway pressure (CPAP) will improve NAFLD but it might at least stabilize and slow its progression. Nevertheless, these multimorbid patients should be efficiently treated for all their metabolic co-morbidities and be encouraged to follow weight stabilization or weight loss programs and physical activity life style interventions.
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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Recent advances in obstructive sleep apnoea (OSA) pathophysiology and translational research have opened new lines of investigation for OSA treatment and management. Key goals of such investigations ...are to provide efficacious, alternative treatment and management pathways that are better tailored to individual risk profiles to move beyond the traditional continuous positive airway pressure (CPAP)-focused, "one size fits all" trial-and-error approach, which is too frequently inadequate for many patients. Identification of different clinical manifestations of OSA (clinical phenotypes) and underlying pathophysiological phenotypes (endotypes) that contribute to OSA have provided novel insights into underlying mechanisms and have underpinned these efforts. Indeed, this new knowledge has provided the framework for precision medicine for OSA to improve treatment success rates with existing non-CPAP therapies such as mandibular advancement devices and upper airway surgery, and newly developed therapies such as hypoglossal nerve stimulation and emerging therapies such as pharmacotherapies and combination therapy. Additionally, these concepts have provided insight into potential physiological barriers to CPAP adherence for certain patients. This review summarises the recent advances in OSA pathogenesis, non-CPAP treatment, clinical management approaches and highlights knowledge gaps for future research. OSA endotyping and clinical phenotyping, risk stratification and personalised treatment allocation approaches are rapidly evolving and will further benefit from the support of recent advances in e-health and artificial intelligence.
Background
Obstructive sleep apnea (OSA) is a chronic disease characterized by recurrent pharyngeal collapses during sleep. In most severe cases, continuous positive airway pressure (CPAP) consists ...in keeping the airways open by administering mild air pressure. This treatment faces adherence issues.
Objectives
Eight hundred and forty‐eight subjects were equipped with CPAP prescribed at the Grenoble University Hospital between 2016 and 2018. Their daily CPAP uses have been recorded during the first 3 months. Our aim is to cluster these adherence time series. With hierarchical agglomerative clustering, we focused on the choices of the dissimilarity measure and the internal cluster validation index (CVI).
Methods
The Euclidean distance, the dynamic time warping (DTW) and the generalized summed discrete Fréchet dissimilarity were implemented with three linkage strategies (“average,” “complete,” and “Ward”). The performances of each method (dissimilarity and linkage) were evaluated on a simulation study through the adjusted Rand index (ARI). The Ward linkage with DTW dissimilarity provided the best ARI. Then six different internal CVIs (Silhouette, Calinski Harabasz, Davies Bouldin, Modified Davies Bouldin, Dunn, and COP) were compared on their ability to choose the best number of clusters. The Dunn index beat the others.
Results
CPAP data were clustered with the Ward linkage, the DTW dissimilarity and the Dunn index. It identified six clusters, from a cluster of patients (N = 29 subjects) whose stopped the therapy early on to a cluster (N = 105) with increasing adherence over time. Other clusters were extremely good users (N = 151), good users (N = 150), moderate users (N = 235), and poor adherers (N = 178).
Aim
To determine the association between total sleep time (TST) spent in increased respiratory effort (RE) and the prevalence of type 2 diabetes in a large cohort of individuals with suspected ...obstructive sleep apnoea (OSA) referred for in‐laboratory polysomnography (PSG).
Materials and Methods
We conducted a retrospective cross‐sectional study using the clinical data of 1128 patients. Non‐invasive measurements of RE were derived from the sleep mandibular jaw movements (MJM) bio‐signal. An explainable machine‐learning model was built to predict prevalent type 2 diabetes from clinical data, standard PSG indices, and MJM‐derived parameters (including the proportion of TST spent with increased respiratory effort REMOV %TST).
Results
Original data were randomly assigned to training (n = 853) and validation (n = 275) subsets. The classification model based on 18 input features including REMOV showed good performance for predicting prevalent type 2 diabetes (sensitivity = 0.81, specificity = 0.89). Post hoc interpretation using the Shapley additive explanation method found that a high value of REMOV was the most important risk factor associated with type 2 diabetes after traditional clinical variables (age, sex, body mass index), and ahead of standard PSG metrics including the apnoea‐hypopnea and oxygen desaturation indices.
Conclusions
These findings show for the first time that the proportion of sleep time spent in increased RE (assessed through MJM measurements) is an important predictor of the association with type 2 diabetes in individuals with OSA.
ABSTRACT
Background and objective
Average volume‐assured pressure support—automated expiratory positive airway pressure (AVAPS‐AE) combines an automated positive expiratory pressure to maintain upper ...airway patency to an automated pressure support with a targeted tidal volume. The aim of this study was to compare the effects of 2‐month AVAPS‐AE ventilation versus pressure support (ST) ventilation on objective sleep quality in stable patients with OHS. Secondary outcomes included arterial blood gases, health‐related quality of life, daytime sleepiness, subjective sleep quality and compliance to NIV.
Methods
This is a prospective multicentric randomized controlled trial. Consecutive OHS patients included had daytime PaCO2 > 6 kPa, BMI ≥ 30 kg/m2, clinical stability for more than 2 weeks and were naive from home NIV. PSG were analysed centrally by two independent experts. Primary endpoint was sleep quality improvement at 2 months.
Results
Among 69 trial patients, 60 patients had successful NIV setup. Baseline and follow‐up PSG were available for 26 patients randomized in the ST group and 30 in the AVAPS‐AE group. At baseline, PaCO2 was 6.94 ± 0.71 kPa in the ST group and 6.61 ± 0.71 in the AVAPS‐AE group (P = 0.032). No significant between‐group difference was observed for objective sleep quality indices. Improvement in PaCO2 was similar between groups with a mean reduction of −0.87 kPa (95% CI: −1.12 to −0.46) in the ST group versus −0.87 kPa (95% CI: −1.14 to −0.50) in the AVAPS‐AE group (P = 0.984). Mean NIV use was 6.2 h per night in both groups (P = 0.93). NIV setup duration was shorter in the AVAPS‐AE group (P = 0.012).
Conclusion
AVAPS‐AE and ST ventilation for 2 months had similar impact on sleep quality and gas exchange.
Automated expiratory positive airway pressure (EPAP) and volume‐targeted non‐invasive ventilation achieve similar control of sleep‐disordered breathing as pressure support ventilation in patients with obesity hypoventilation syndrome. Objective sleep quality at 2 months of ventilation therapy is not altered by the use of automated EPAP and volume‐targeted ventilation compared to pressure support ventilation.
See related Editorial
PDF
