Validation of Sleep Healthcare System

January 31, 2020 updated by: National Taiwan University Hospital

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

Unknown

Intervention / Treatment

Study Type

Interventional

Enrollment (Anticipated)

300

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

      • Taipei, Taiwan
        • Recruiting
        • Center of sleep disorders, National Taiwan University Hospital
        • Contact:
          • Peilin Lee

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

20 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Inclusion Criteria:

  1. Stage1:>=20 year-old
  2. Stage2:>=20 year-old 2-1patients with moderate-severe OSA (AHI≥15/hr)

Exclusion Criteria:

  1. Stage1:Have been diagnosed with obstructive sleep apnea
  2. 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

This section provides details of the study plan, including how the study is designed and what the study is measuring.

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
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

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

April 16, 2018

Primary Completion (Anticipated)

May 22, 2022

Study Completion (Anticipated)

May 22, 2022

Study Registration Dates

First Submitted

January 30, 2020

First Submitted That Met QC Criteria

January 31, 2020

First Posted (Actual)

February 5, 2020

Study Record Updates

Last Update Posted (Actual)

February 5, 2020

Last Update Submitted That Met QC Criteria

January 31, 2020

Last Verified

January 1, 2020

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)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

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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