- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04252482
Validation of Sleep Healthcare System
Sleep quality affect working and learning performance; poor quality of sleep is one of the common problems of modern people. Traditionally, polysomnography is a recognized standard for sleep quality assessment. Subjects are put adhesive electrodes, chest and abdomen band, oximetery, and oronasal cannula and stay in certified sleep laboratory for monitoring. These sensors setup are cumbersome and be likely to induce discomfort. An alternative to assess the quality of sleep is actigraphy, which allows users to wear for more than two weeks. In recent years, many of the smart watches, which often measure wrist photoplethysmography (PPG) signal and body movement, are prevailing to make long-term sleep monitoring feasible, but its accuracy and effectiveness still need to be verified.
Obstructive sleep apnea (OSA) is a common disorder characterized by intermittent hypoxia and sleep fragmentation. OSA is associated with cardiovascular morbidity and mortality, metabolic dysregulation, and neurocognitive dysfunction, which results in the negative impact on prognosis. PSG is the gold standard for OSA diagnosis which is expensive and less accessible. Therefore, modality other than PSG is necessary to speed up diagnosis and treatment. Center of Sleep Disorder in National Taiwan University Hospital has been operated since June 2006. Up to Dec.2015, totally 8,819 patients have been referred for sleep studies (NTUH cohort) where 1,435 patients are under long-term CPAP and 396 patients are under MAD. Using data from 4,618 patients in NTUH cohort, we have already established an OSA prediction mode (apnea-hypopnea index, AHI≥5/hr) with accuracy 82.37% (sensitivity 87.03%, positive predictive value 91%). Regarding the molecular mechanism, our previous study showed that by plasma metabolomics profiling, we could identify candidate metabolites associated with OSA severity. The 11 candidate metabolites were identified by comparing profiling in 100 patients with AHI <15/hr and with AHI>=15/hr, respectively. Six identified metabolites were selected to establish an AHI prediction model which gave sensitivity 66%, specificity 72%, and AUROC 0.736. Furthermore, 15 plasma metabolites associated with excessive daytime sleepiness (EDS) or polysomnographic parameters were identified. Among those metabolites, L-Kynurenine and g-Glutamylleucine were metabolites associated with EDS which generated the AUROC to EDS prediction as 63% in study group and 76.7% in validation group. The online system (Good Sleep) for diagnosis of sleep disorder has been set up under the collaboration between, NTU, NTUH, and MediaTek. It aims on population with low probability of sleep disorder which compliments the NTUH cohort, high probability of sleep disorder. The online system provides the diagnosis and solution of sleep disorder, sleep tracking, and education via both website and App. The system is almost set and needs the input from general population to validate the accuracy.
The sleep healthcare system, which includes questionnaires, smart watches,24-hr BP and "LARGAN"ECG Holter for long-term home sleep monitoring, is proposed to allow users to detect potential subjects who have sleep disorders by filling out the questionnaire. The aims of the present project include: (1) All 300 voluntary.Stage1, Recruit 140 voluntary participants from MediaTek to validate agreement of sleep efficiency via online system, actigraph devices, smart watches and daily blood pressure for one week.Stage2, Recruit 160 voluntary participants from patients with moderate-severe OSA (AHI≥15/hr) to validate agreement of sleep efficiency via online system, actigraph devices, smart watches, ECG Holter and 24 hour blood pressure for one day. (2) All participants will take an overnight PSG test, blood sampling, basal metabolism measurement, ECG Holter, body composition and E-Prime at the sleep center to validate the performance of online system on diagnosis of OSA in low risk population. (3) Analyze the of PSG parameters in both low and high risk population (to build up the out of center devices for OSA home testing). (4) Integrate the clinical parameters and plasma metabolic profile, before and after treatment, to identify factors associated with OSA related sequels and long-term prognosis.
Study Overview
Status
Conditions
Intervention / Treatment
Study Type
Enrollment (Anticipated)
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
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Taipei, Taiwan
- Recruiting
- Center of sleep disorders, National Taiwan University Hospital
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Contact:
- Peilin Lee
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Stage1:>=20 year-old
- Stage2:>=20 year-old 2-1patients with moderate-severe OSA (AHI≥15/hr)
Exclusion Criteria:
- Stage1:Have been diagnosed with obstructive sleep apnea
- Stage2:Have been diagnosed with obstructive sleep apnea 2-1BMI≧40 kg/m2 2-2Acute disease 2-3Chronic disease 2-3Systemic inflammatory state 2-4Use anti-inflammatory drugs 2-5shift worker
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Experimental: cpap
usage cpap 3month
|
CPAP useg 3month
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No Intervention: Usual care
Usual care 3month
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Validation of sleep healthcare system
Time Frame: 24month
|
This study aims to validate effectiveness of the online questionnaires and commercial wearable devices for sleep quality assessment.
The validation results can enable future research on sleep healthcare.
|
24month
|
Collaborators and Investigators
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Anticipated)
Study Completion (Anticipated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
- 201802034RIPD
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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