View clinical trials related to Hypersomnia.
Filter by:The platform protocol is designed to be flexible so that it is suitable for a range of study settings and intervention types. Therefore, the platform protocol provides a general protocol structure that can be shared by multiple interventions and allows comparative analysis across the interventions. For example, objectives, measures, and endpoints are generalized in the platform protocol, but intervention-specific features are detailed in separate appendices. This platform protocol is a prospective, multi-center, multi-arm, randomized controlled platform trial evaluating potential interventions for PASC-mediated sleep disturbances. The hypothesis is that symptoms of sleep and circadian disorders that emerge in patients with PASC can be improved by phenotype-targeted interventions. Specific sleep and circadian disorders addressed in this protocol include sleep-related daytime impairment (referred to as hypersomnia) and complex PASC-related sleep disturbance (reflecting symptoms of insomnia and sleep-wake rhythm disturbance).
The platform protocol is designed to be flexible so that it is suitable for a range of study settings and intervention types. Therefore, the platform protocol provides a general protocol structure that can be shared by multiple interventions and allows comparative analysis across the interventions. For example, objectives, measures, and endpoints are generalized in the platform protocol, but intervention-specific features are detailed in separate appendices. This platform protocol is a prospective, multi-center, multi-arm, randomized controlled platform trial evaluating potential interventions for PASC-mediated sleep disturbances. The hypothesis is that symptoms of sleep and circadian disorders that emerge in patients with PASC can be improved by phenotype-targeted interventions. Specific sleep and circadian disorders addressed in this protocol include sleep-related daytime impairment (referred to as hypersomnia) and complex PASC-related sleep disturbance (reflecting symptoms of insomnia and sleep-wake rhythm disturbance).
The goal of this pilot observational study is to assess the ability of continuous 'home' EEG to accurately diagnose Narcolepsy in children and young people with hypersomnia. The main question[s]it aims to answer are: - can ambulatory home monitoring using a Dreem headband with a 'life as usual' unrestricted protocol allow accurate diagnosis of Narcolepsy, compared to gold standard in-patient PSG and MSLT - which EEG derived sleep parameters and study duration yield most diagnostic accuracy Participants undergoing investigation for hypersomnia will additionally be asked to wear a Dream Headband at night for weeknights, then continuously for 48 hours over the weekend. The data from the headband will then be analysed to see if it can predict the results of the polysomnography and MSLT that form routine clinical care.
Individuals who have disorders of hypersomnolence (excessive sleepiness) often report symptoms of depression. The goal of this study is to further understand of the relationship between depression and hypersomnia by examining mood-relevant domains of slow wave sleep and reward function.
The central hypothesis is that home EEG monitoring (Dream 3 wearable) can be feasibly utilized for data capture of continuous sleep and wake measurements for the diagnostic evaluation and treatment monitoring of hypersomnia.
This is a retrospective and prospective cohort study. There are 600 subjects (age 9-45) will be collected.The purposes of this study are as follows:(1) The main purpose is to use Multi-Signal Based Monitoring System to link with brain image data and perform cross-comparison to find out possible pathological mechanisms of these CNS hypersomnias.(2) Use the Multi-Signal Based Monitoring System to link with brain image data and perform cross-comparison to further screen out these clinically significant biomarkers for CNS hypersomnias, and to find ideal and accurate physiological biomarkers that can monitor the course of the disease.(3) Utilize these precisely monitored biomarkers to track changes in the biomarkers and the long-term course of these CNS hypersomnias, and evaluate the treatment effect and prognosis.(4) Use computer machine learning and other algorithms to analyze and construct a variety of faster and more accurate prediction models for these CNS hypersomnias, thereby achieving the goal of preventive medicine.
This randomized controlled study will directly evaluate whether unattended polysomnography (level 2 sleep study) in individuals referred for sleep apnea or hypersomnia, including those with comorbidities of insomnia and sleep-related movement disorders, provides similar patient outcomes when compared to level 1 sleep studies.
Excessive diurnal sleepiness is characterized by an incapacity to stay awake, in favour of sleep occurrence. This sleepiness might be secondary to a sleep disorder; when it is not the case, it is primary hypersomnia (including narcolepsy and idiopathic hypersomnia). To date, objective measures of sleepiness can only be achieved in laboratory. Subjective techniques as scales and questionnaires are highly sensitive to inter-individual differences and cannot constitute a reliable diagnosis tool of sleepiness. Recent studies suggested that some salivary biomarkers are sensitive to sleep characteristics and thus, may allow the objective and easy evaluation of sleepiness. The objective of the study is to explore the usability of salivary biomarkers (a-amylase and oxalate) as a new non-invasive technique to evaluate sleepiness and to diagnose primary hypersomnia in children. The hypothesis of this study is that there will be a modification of salivary biomarkers concentrations with the variations of diurnal sleepiness.
The goal of the study is to test the role of telemedicine combined with humidification to check CPAP treatment during the first month to improve adherence and reduce unsolved side effects of therapy.
Decades of research have shown that sleep disturbances are common among patients with a wide range of psychiatric disorders. Such reported sleep disturbances include disrupted sleep efficiency and continuity, sleep quality complaints, insomnia, and nightmares. While traditional models suggest that certain sleep alterations are specific for certain mental disorders, newer models assume a transdiagnostic or dimensional view of sleep disturbances in mental disorders. Findings of a recent meta-analysis support the transdiagnostic or dimensional association between sleep disorders and psychiatric conditions. Additionally, the period just prior to sleep has recently received increased clinical and research interest, with studies investigating cognitive activity and rumination prior to sleep. However, only few studies compare sleep in different psychiatric diagnoses and the characteristics of sleep in different mental disorders are still not understood well enough for concrete implications for clinical practice. This is especially true for the population of psychiatric inpatients. In this study, the outcome measures and study variables will be measured with standardised and validated questionnaires, structured clinical interview, and a commercially available Fitbit Charge 2 tracker. Participants will be recruited from the inpatient units of the Psychiatric University Hospital Zurich (PUK). Screening will be conducted by the applicant and master's students enrolled in the project, using electronic patient files at the hospital. The patients will be invited to the study by their treating physician or psychologist. Assessments will consist of one interview and filling out of questionnaires (with a 30- to 45-minute duration respectively). A sub-sample will wear fill out a sleep diary for seven consecutive nights as well as wear a Fitbit Charge 2 tracker, which they will return a week later. Each patient will receive participant reimbursement of 30 Swiss francs (CHF) for their participation in the study.