A Multi-Signal Based Monitoring System for CNS Hypersomnias

June 30, 2022 updated by: Chang Gung Memorial Hospital

A Multi-Signal Based Monitoring System for CNS Hypersomnias : A 10-year Longitudinal Study

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.

Study Overview

Status

Recruiting

Conditions

Detailed Description

Excessive daytime sleepiness (EDS) is a common symptom in the general population. The prevalence ranges from 5% to 30%. And daytime drowsiness often brings negative effects, and even the daily function and the quality of life is impaired due to these hypersomnias. In some severe cases, many accidents can occur and endanger life. The current third edition of the International Classification of Sleep Disorders (ICSD 3) specifically classified "Central nervous system disorders of hypersomnolence" as Narcolepsy type 1 and type 2 ; idiopathic hypersomnia(IH), and Kleine-Levin syndrome (KLS). However, so far, except for Narcolepsy type 1, which has a relatively clear pathological mechanism that is related to the reduced secretion of hypocretin, other hypersomnia disorders such as Narcolepsy type 2, IH and KLS, that is no clear neurophysiological diagnosis standard, and the mechanism of these diseases is still not clear. Therefore, the diagnosis can only rely on the clinical symptoms and the clinical experience physicians. That is why the diagnosis of these diseases still has great difficulties and challenges. Therefore, in order to make the diagnosis more accurate, the investigators have to find out the "Biologic and neurophysiologic biomarkers" for these diseases. And let patients receive the correct treatment quickly.

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.

Research method:

This is a retrospective and prospective cohort study. There are 600 subjects (age 9-45) will be collected. These subjects will be divided into the five groups: (1) experimental group (narcolepsy Type 1, 300 subjects); (2) experimental group (narcolepsy Type 2, 100 subjects); and (3) experimental group (KLS, 100 subjects); and (4) experimental group (IH,50 subjects); and (5) healthy control group (age and gender matched healthy subjects,50 subjects). The investigators will collect all the clinical data for each subject, including clinical characteristics, sleep examination data, actigraphy, HLA typing, and brain imaging data.

Data analysis method:

Use multiple physiological signals to generate real-time quantitative algorithms and find physiological biomarkers related to hypersomnias. Use the aforementioned data were categorized and grouped through data analysis based on computer machine learning, neural network, and other algorithms. Then the investigators will build a predictive model based on the results and write a medical report and publish it.

Study Type

Observational

Enrollment (Anticipated)

600

Contacts and Locations

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

Study Contact

Study Locations

  • Taiwan
      • Taoyuan, Taiwan, 333423
        • Recruiting
        • Chang Gung memorial hospital
        • Contact:
      • Taoyuan City, Taiwan, 333423
        • Recruiting
        • Chang Gung Memorial Hospital, Linkou

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

9 years to 45 years (ADULT, CHILD)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

9-45 years old subjects with narcolepsy , Kleine-Levin syndrome or Idiopathic Hypersomnia

Description

Inclusion Criteria:

  1. Patients with narcolepsy , Kleine-Levin syndrome(KLS) or Idiopathic Hypersomnia (IH) diagnosed by a physician who meet the ICSD-3 diagnostic criteria
  2. Age: 9-45 years old
  3. Those who agree to participate in this research and can sign the consent form.

Exclusion Criteria:

  1. Patients with epilepsy, head trauma and severe organic brain disease.
  2. Patients with severe Obstructive Sleep Apnea (OSA) and severe Periodic Limb Movement Disorder (PLMD) who have not received treatment.
  3. People with narcolepsy due to other physical and brain diseases.
  4. Those who cannot cooperate with the brain imaging examination and neurocognitive function test.
  5. Exclude those who have had brain surgery for brain tumor hemangioma, or those who have cerebral blood vessel metal clips.
  6. Exclude current pacemakers.
  7. Excluded those who had implanted artificial heart metal valve.
  8. Those who underwent surgery within the last 3 months were excluded.
  9. rule out claustrophobia
  10. Those who are unwilling to participate in this research or are unwilling to fill in the consent form.

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

Cohorts and Interventions

Group / Cohort
experimental group (narcolepsy Type 1)
experimental group (narcolepsy Type 1, 300 subjects)
experimental group (narcolepsy Type 2)
experimental group (narcolepsy Type 2, 100 subjects)
experimental group (KLS)
experimental group (KLS, 100 subjects)
experimental group (IH)
experimental group (IH,50 subjects)
healthy control group
healthy control group (age and gender matched healthy subjects,50 subjects)

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Polysomnography (PSG)
Time Frame: Once a year until the study is completed (up to 3 years)
Change in sleep latency (SL, mins) based on PSG during the study.
Once a year until the study is completed (up to 3 years)
Multiple sleep latency test (MSLT)
Time Frame: Once a year until the study is completed (up to 3 years)
Change in Change in sleep latency (SL, mins) based on MSLT during the study.
Once a year until the study is completed (up to 3 years)
HLA TYPING
Time Frame: baseline
The investigators will use sequence-specific primer - polymerase chain reaction (SSP-PCR) to detect HLA-DQB1 and reverse sequence-specific oligonucleotide probes (SSOPs) to detect HLA-DQA1,and also use Sequencing Based Typing (SBT) and reverse sequence specific oligonucleotide (rSSO) to detect HLA-DRB and HLA-DQB in the lab.
baseline
Actigraphy
Time Frame: Once a year until the study is completed (up to 3 years)
Change in sleep latency (mins) based on actigraphy during the study.
Once a year until the study is completed (up to 3 years)
PET/MRI
Time Frame: through study completion, an average of 1 year
Positron Emission Tomography is a fusion of PET and MRI imaging techniques that can show the spread of diseased cells in soft tissue. The PET/MRI system can scan various parts of the patient and collect PET and MRI images separately for early diagnosis.
through study completion, an average of 1 year

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Conners' Continuous Performance Test (CPT)
Time Frame: Once a year until the study is completed (up to 3 years)
The Conners Continuous Performance Test is a computer administered test that is designed to assess problems with attention.Many statistics are computed including omission errors , commission errors, hit reaction time, hit reaction time standard error, detectability, response style, perseverations , hit reaction time by block, standard error by block, reaction time by ISI , and standard error by ISI. These statistics are converted to T-scores and can be interpreted in terms of various aspects of attention including inattention, impulsivity, and vigilance.Higher rates of correct detections indicate better attentional capacity.
Once a year until the study is completed (up to 3 years)
Wisconsin Card Sorting Test (WCST)
Time Frame: Once a year until the study is completed (up to 3 years)
The Wisconsin Card Sorting Test (WCST) is a neuropsychological test that is frequently used to measure such higher-level cognitive processes as attention, perseverance,working memory, abstract thinking and set shifting.
Once a year until the study is completed (up to 3 years)
Epworth Sleepoiness Scale (ESS)
Time Frame: Once a year until the study is completed (up to 3 years)
Epworth Sleepoiness Scale (ESS) assesses the responder's propensity to doze or fall asleep during 8 common daily activities, such as: sitting and reading; sitting inactive in a public place; sitting and talking to someone; sitting quietly after a lunch without alcohol; or in a car, while stopped for a few minutes in traffic. An ESS score >10 suggests excessive daytime sleepiness (EDS); ESS score ≥16 suggests a high level of EDS.
Once a year until the study is completed (up to 3 years)
Pediatric Daytime Sleepiness Scale (PDSS)
Time Frame: Once a year until the study is completed (up to 3 years)
The pediatric daytime sleepiness questionnaire is a 5 points Likert scale (0-4) for 8 questions concerning to sleepiness. Scores ranged from 0 to 32.Higher scores on PDSS were associated with reduced total sleep time, poorer school achievement, poorer anger control, and frequent illness.
Once a year until the study is completed (up to 3 years)
Short Form-36 (SF-36)
Time Frame: Once a year until the study is completed (up to 3 years)
36-Item Short-Form Health Survey (SF-36) includes 11 major questions that evaluate eight components (0-100), with higher scores indicating better outcome.These components include physical functioning, role limitations due to physical health, role limitations due to emotional problems, energy/fatigue, emotional wellbeing, social functioning, pain, and general health.
Once a year until the study is completed (up to 3 years)
Polysomnography (PSG)-SE
Time Frame: Once a year until the study is completed (up to 3 years)
Change in sleep efficiency (SE, %)based on PSG during the study.
Once a year until the study is completed (up to 3 years)
Polysomnography (PSG)-TST
Time Frame: Once a year until the study is completed (up to 3 years)
Change in total sleep time (TST, mins) based on PSG during the study.
Once a year until the study is completed (up to 3 years)
Polysomnography (PSG)-WASO
Time Frame: Once a year until the study is completed (up to 3 years)
Change in slow wave sleep (SWS, %) based on PSG during the study.
Once a year until the study is completed (up to 3 years)
Polysomnography (PSG)-REM
Time Frame: Once a year until the study is completed (up to 3 years)
Change in REM sleep (%) based on PSG during the study.
Once a year until the study is completed (up to 3 years)
Polysomnography (PSG)-SWS
Time Frame: Once a year until the study is completed (up to 3 years)
Change in slow wave sleep (SWS, %) based on PSG during the study.
Once a year until the study is completed (up to 3 years)
Actigraphy-TST
Time Frame: Once a year until the study is completed (up to 3 years)
Total sleep time (TST, mins) based on actigraphy during the study.
Once a year until the study is completed (up to 3 years)
Actigraphy-SE
Time Frame: Once a year until the study is completed (up to 3 years)
Sleep efficiency (SE, %) based on actigraphy during the study.
Once a year until the study is completed (up to 3 years)
Actigraphy-WASO
Time Frame: Once a year until the study is completed (up to 3 years)
Wake after sleep onset (WASO) based on actigraphy during the study.
Once a year until the study is completed (up to 3 years)

Collaborators and Investigators

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

Sponsor

Chang Gung Memorial Hospital

Investigators

  • Study Director: Yu-Shu Huang, PhD, Principal Investigator

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

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)

June 4, 2020

Primary Completion (ANTICIPATED)

July 31, 2023

Study Completion (ANTICIPATED)

July 31, 2023

Study Registration Dates

First Submitted

May 30, 2022

First Submitted That Met QC Criteria

June 30, 2022

First Posted (ACTUAL)

July 5, 2022

Study Record Updates

Last Update Posted (ACTUAL)

July 5, 2022

Last Update Submitted That Met QC Criteria

June 30, 2022

Last Verified

May 1, 2022

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 201902163A3

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

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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