Research team

Expertise

Diagnostic sleep research (medical head Sleep Disorders Center UZA-UA) Treatment sleep apnoea. Control of breathing during sleep.

Towards non-invasive prediction of treatment outcome for obstructive sleep apnea: development of a holistic model combining anatomical and non-anatomical endotypes. 01/10/2024 - 30/09/2027

Abstract

Obstructive sleep apnea (OSA) is a highly prevalent respiratory sleep disorder. As it is associated with multiple comorbidities including cardio- and cerebrovascular burden, appropriate treatment is crucial. To achieve optimal treatment, both efficacy and adherence should be optimized. Endotyping OSA patients has shown promise for treatment optimization, yet gold-standard assessment is impossible in clinical practice. The site, pattern and degree of collapse is a key factor driving OSA treatment outcome. In current clinical practice, drug-induced sleep endoscopy (DISE) is used to visualize the upper airway during sedation. However, this technique does not allow site of collapse assessment during longer periods and different sleep stages. Recently, I developed a non-invasive means to assess probability of site of collapse using clinical polysomnography that could overcome this issue. Yet, the underlying mechanisms remain unknown. Furthermore, associations with and relative importance of this parameter compared to other non-invasive endotypes remain unclear. Therefore, I aim to 1) assess the underlying mechanistic effects underlying non-invasive site of collapse detection throughout the night to augment the novel method, 2) predict OSA treatment outcome using this method, and 3) develop a holistic model combining anatomical and non-anatomical non-invasive endotypes. As such, I aim to attain precision OSA medicine using endotype-driven instead of guideline-based treatment.

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  • Research Project

Type D personality and outcome OSAS-CSAS 01/10/2024 - 30/09/2026

Abstract

Obstructive sleep apnea (OSA) is a highly prevalent disorders which occurs in 4% of males and 2% of females. Patients with OSA present a high risk to develop cardiovascular and metabolic disorders and malignicies, resulting in a decreased quality of life. In small size studies it has shown that the presence of type D personality (social inhibition, negative emotions) can be associated with more fatigue, and more side effects during treatment. Type D personality occurs in 21% of the general population. When evaluating the efficiency of sleep apnea treatment, the effect on the apnea-hypopnea index (AHI) has to be taken into account that, but also the number of hours that the treatment is effectively use, called the "mean disease alleviation". Up to present large scale studies are missing looking at the impact of type D personality on symptoms and compliance for different treatment modalities that are applied in patients with sleep apnea. In the first part of the research the prevalence of type D will be assessed in the sleep apnea population, in patients with OSA as well as in patients with central sleep apnea (CSA). In the second part the impact of type D personality will be assessed on the presence of symptoms, burden of treatment, mean disease alleviation, and compliance for a) CPAP (continuous positive airway pressure) b) BiPAP (bilevel positive airway pressure) c) ASV (adaptive servo ventilation) In the third part i twill be evaluatied whether type D persoonlijkheid plays a role in the decision making of OSA patients to opt for bariatric surgery. In the last part the effect of type D personality will be assessed on the number of comorbidities OSA patients develop on the long-run (from diagnosis to treatment). The comorbidities that will be evaluated in (un)treated OSA patients, are cardiovascular, metabolic and malignant disorders. For this purpose we will make use of our own data processed the European Sleep Apnea Database (ESADA).

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  • Research Project

UZA-Addressing multimorbidity in elderly atrial fibrillation patients through interdisciplinary, tailored, patient-centered care pathways (EHRA PATHS). 01/04/2021 - 31/03/2026

Abstract

Optimization of atrial fibrillation (AF) disease management is highly needed. The AF prevalence is 7.8% above the age of 65 years and it will further increase as the population ages and predisposing factors become more prevalent. Multimorbidity (93.5%) and polypharmacy (76.5%) are very common in these patients. The mean number of comorbidities is 5.0 in those ≥65 years old. There is a great need to optimize the management of AF patients - and not only the arrhythmia - to reduce the burden on patients, society, healthcare system and the economy. The aim of the EHRA-PATHS project is to create well founded, innovative systematic care pathways to tackle multimorbidity in elderly AF patients. We hypothesize that such a well-structured, interdisciplinary, and patient-tailored care program is feasible throughout all healthcare systems in Europe, and effective to optimize outcomes.

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  • Research Project

UZA-Revolution of sleep diagnostics and personalized health care based on digital diagnostics and therapeutics with health data integration (SLEEP REVOLUTION). 01/03/2021 - 28/02/2025

Abstract

Obstructive sleep apnea (OSA) is associated with various negative health consequences including increased risk of heart disease, hypertension and daytime sleepiness causing road accidents. The economic burden of OSA is rising as almost 1 billion people worldwide are estimated to have OSA. The current diagnostic metric, however, relates poorly to these symptoms and comorbidities. It merely measures the frequency of breathing cessations without assessing OSA severity in any other physiologically relevant way. Furthermore, the clinical methods for analyzing PSG signals are outdated, expensive and laborious. Due to this, the majority of OSA patients remain without diagnosis or have an inaccurate diagnosis leading to sub-optimal treatment. Thus, it is evident that more personalized diagnostics are required including predictive and preventive health care and patient participation. The SLEEP REVOLUTION aims to develop machine learning techniques to better estimate OSA severity and treatment needs to improve health outcomes and quality of life. These techniques are implemented to high-end wearables developed in this project to alleviate the costs and increase the availability of PSGs. Finally, we aim to design a digital platform that functions as a bridge between researchers, patients and healthcare professionals. We will achieve these ambitious goals throughout extensive collaboration between sleep specialists, computer scientists and industry partners. The collaboration network consists of over 30 sleep centers working together to provide the needed retrospective data (over 10.000 sleep studies). The multi-center prospective trials involve experts and end-users to assess and validate the new SLEEP REVOLUTION diagnostic algorithms, wearables and platforms. With the commitment of the European Sleep Research Society and Assembly of National Sleep Societies (over 8000 members), we have the unique possibility to create new standardized guidelines for sleep medicine in the EU.

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  • Research Project

Development of a predictive model for endotype-based patient selection for obstructive sleep apnea treatment. 01/10/2021 - 30/09/2024

Abstract

Obstructive sleep apnea (OSA) is a highly prevalent disease, associated with several cardiovascular and cerebrovascular comorbidities. Adequate treatment is thus crucial. Based on the current guidelines, continuous positive airway pressure (CPAP) is considered the standard OSA treatment. While CPAP efficacy is high, patient tolerance and acceptance is only moderate. In general, alternative non-CPAP treatments like mandibular advancement devices, hypoglossal nerve stimulation or pharmacotherapy are well-received, however, their efficacy is potent in some patients but incomplete in others. Efficacy of emerging therapies depends largely on the site of obstruction of the upper airway, key diagnostic information that is notoriously challenging to obtain. In current clinical practice this information is captured during drug-induced sleep endoscopy (DISE), assessing the upper airway during sedation. However, this DISE procedure still requires an additional step in the clinical path involving specialized personnel, time and equipment at the operating theatre. Therefore, I aim to 1) correlate the collapse patterns during DISE with parameters extracted from baseline clinical data in order to develop a prediction model to predict collapse patterns without the need of drug-induced sedation and 2) to apply this model to patients treated with a non-CPAP treatment. In this way, I aim to attain precision OSA medicine using endotype-driven instead of guideline-based OSA treatment.

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  • Research Project

Mobile and technological solutions for occupational drivers (MILESTONE). 01/09/2021 - 31/08/2024

Abstract

Objective 1: Understanding the impact of personal state and contextual stressors, on driving behaviour and traffic safety aims to analyse the relationship between physiological and mental states (sleep quality, fatigue, sleepiness, stress, thermal comfort), general health, work-related factors, external stressors, and driving parameters linked with traffic safety. We examine how stress builds up for occupational drivers due to environmental conditions. We also analyse whether sleep quality, and combinations of stress, sleepiness and thermal comfort, can be estimated in controlled lab conditions using wearables; and furthermore whether this can also be continuously monitored in practical driving conditions using wearables combined with approaches from artificial intelligence. We identify external factors which are causing these different states throughout the day, and in real driving conditions, and its impact on driving behaviour and traffic safety. Deliverables are the development of a tool/app tailored to the living and working conditions of drivers, to monitor stress levels, sleepiness, thermal comfort levels 24/7; as well as more insight in the relation between stress, sleep quality and driving parameters (related to safety and eco-driving), and in external stressors, both trip- and work-related. Insights will be used to develop technological interventions in the following work packages. Objective 2: Development of system-level intervention to keep drivers within their 'stress tolerance zone' (STZ) aims to analyse the individual safe STZ, consisting of the personal stress (physiological and mental state) accumulated with contextual stress; and to develop a system-level intervention to keep drivers in a state of normal driving without too much stress, with the lowest possible risk of a crash scenario developing. The system-level intervention will be developed based on a user-centered design approach with gamification principles, focussing on acute and chronic stress, and different levels of employer's involvement. After workshops with drivers, the intervention will be developed and pilot tested by a small group of drivers based on usability/technical aspects. A dashboard will be developed, which will allow the employer to detect individual stress situations and driver's performance; and provide useful aggregated insights about the efficiency of the planning system. Objective 3: Development of job-facilitating solutions aims to work out several solutions to facilitate the occupational driver working conditions, based on the identified stressors, related to technological issues to improve the cabin domotics, the development of guidelines, and other (future) development opportunities. We will use the insights related to Objectives 1/2 as a basis for developing the solutions. Objective 4: Implementation of MILESTONE intervention and job-facilitating solutions aims to analyze the impact of the personalized intervention for drivers for different driver categories (long-haul, short-haul and local delivery), in relation to a control group, and for different feedback types. The impact of the job-facilitating solutions on drivers' experiences will be determined as well.

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  • Research Project

The development of a multifactorial model to predict the outcome of mandibular advancement device therapy for obstructive sleep apnea based on the patients' phenotype. 01/10/2019 - 30/09/2023

Abstract

Obstructive sleep apnea (OSA) is a prevalent public health issue with an attributable risk of cardio- and cerebrovascular morbidity and mortality. Furthermore, OSA is related to a high socioeconomic burden due to its clinical daytime consequences such as excessive daytime sleepiness, impaired cognitive performance and reduced quality of life. Oral appliances that protrude the mandible, the mandibular advancement devices (MAD), significantly reduce OSA severity in the majority of patients. However, in a third of patients, the efficacy is not medically appropriate to reduce the long-term consequences of OSA. Furthermore, the efficacy of MAD therapy is inconsistent among patients. Therefore, a high need exists for upfront prediction of treatment outcome in the individual OSA patient. There is no validated method that can achieve upfront selection of candidates for MAD therapy in an accurate and reliable way. Nowadays, it is increasingly recognized that OSA is a multifactorial disease. In the proposed research project, a prospective prediction model with a combination of different pathophysiological traits will be assessed. Furthermore, up to now, our understanding of MAD therapy relies on relatively small studies lacking power. Therefore, we will evaluate this predictive model, as well as the long-term effectiveness, morbidity and mortality in a large international cohort of patients treated with MAD.

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  • Research Project

Reboot Sleep Medicine. 01/04/2019 - 31/03/2023

Abstract

Ectosense devloped a miniaturized, comfortable and clinically accurate home sleep test for the diagnosis of sleep apnea, based on 'Perhipheral Arterial Tonometry' (PAT). In this research, we would like to evaluate i) the underlying physiological phenomena which explain this performance but also limitations, ii) which technologies can be complementary used via incorporation or extension of the current technology, iii) how these technologiees can fit in new care paths.

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  • Research Project

A functional imaging study of the vascular wall in sleep apnea patients. 01/03/2010 - 28/02/2011

Abstract

Study of the vascular wall by means of functional imaging in patients with sleep apnea Obstructive sleep apnea (OSA) is a disorder with a high prevalence, which is present in 5 to 10% of the general population, depending on its severity. Untill recently sleepiness during the daytime, fatigue and concentration problems are considered as the most important consequences of the disease. These symptoms are often present and disappear quickly after the start of adequate treatment with CPAP (1). The last decennium it has become clear that sleep apnea, which is characterized by repetitive oxygen desaturation, with inherent reoxygenation, is an important source of oxidative stress and systemic inflammation. More recently these changes have been associated with increasing vascular pathology. Indeed, sleep apnea is associated with hypertension and an increasing cardiovascular morbidity and mortality. The link between severe OSA and cardiovascular burden has been shown convincingly by a very significant reduction of cardiovascular morbidity in patients with adequate nCPAP therapy compared to untreated OSA patients (2). OSA can lead to cardiovascular pathology by an incrase in sympathetic tone, but probably also by complex inflammatory processes and oxidative stress at the vascular wall (3). Therefore it is extremely important to describe in a very sensitive and adequate manner the changes in the structure of the vascular wall in OSA patients. The structural changes in the larger vessels can only be detected by means of a threedimensional reconstruction. Moreover, it is of interest to calculate the vascular resistance. Only recently, an analysis method has become available which makes it able to calculate resistances in geometries, when boundary conditions like pressure and flow are known. This method is known as 'computational fluid dynamics' or CFD. There is already some experience with biomedical applications of CFD in both the cardiovascular (4) and respiratory field (5). In the current research project we will study patients with different degrees of sleep apnea, before and after adequate treatment, with focus on the structure of the vascular wall, using CFD. The treatments which will be considered are antioxidants and anti-inflammatory drugs compared to CPAP. Also the effect of combination therapies will be evaluated. References 1. McMahon, J. P., B. H. Foresman, and R. C. Chisholm. 2003. The influence of CPAP on the neurobehavioral performance of patients with obstructive sleep apnea hypopnea syndrome: a systematic review. WMJ. 102:36-43. 2. Marin, J. M., S. J. Carrizo, E. Vicente, and A. G. Agusti. 2005. Long-term cardiovascular outcomes in men with obstructive sleep apnoea-hypopnoea with or without treatment with continuous positive airway pressure: an observational study. Lancet 365:1046-1053. 3. Lavie, L. 2004. Sleep apnea syndrome, endothelial dysfunction, and cardiovascular morbidity. Sleep 27:1053-1055. 4. Eloot, S., Y. D'Asseler, P. De Bondt, and R. Verdonck. 2005. Combining SPECT medical imaging and computational fluid dynamics for analyzing blood and dialysate flow in hemodialyzers. Int.J Artif.Organs 28:739-749. 5. De Backer, J., O. Vanderveken, W. Vos, A. Devolder, S. Verhulst, J. Verbraecken, P. Parizel, M. Braem, P. Van de Heyning, W. De Backer. 2007. Functional imaging using computational fluid dynamics to predict treatment success of mandibular advancement devices in sleep-disordered breathing. J Biomechanics 40:16: 3708-3714.

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  • Research Project

EASI - Enhancing Activity through Sleep improvement. 01/10/2007 - 30/09/2011

Abstract

We spend approximately one third of our lives sleeping, while a synergy of psychological, physiological and physical conditions affects the quality of sleep. These conditions should not be considered apart from each other, since physical factors can influence the mental quality of sleep and vice versa. Furthermore, physiological reactions of the human body are often a response to the physical condition of the body in its environment. Due to the considerably complex and multidisciplinary character of this interaction, however, sleep is generally considered as a black box, while passing over the underlying determinants and relations. It is quite a surprise to find out that scientists have only recently (last 50 years) started to study this phenomenon, and that few communications (e.g. by media) are scientifically founded. To our knowledge, this project is the first to quantify and to gain insight into the complex and multidisciplinary character of the interaction between environmental variables and the quality of sleep. SCIENTIFIC AND TECHNOLOGICAL AIMS This project aims at opening the black box in four phases, where the first two are rather scientifically oriented, while the last two are technologically oriented:

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  • Research Project