UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000047113 |
|---|---|
| Receipt number | R000053622 |
| Scientific Title | A comparative study of objective measurement of sleep state using polysomnography and subjective measurement of sleep state using bed sensor in patients with psychiatric disorders complaining of insomnia |
| Date of disclosure of the study information | 2022/03/08 |
| Last modified on | 2023/11/16 09:52:05 |
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Basic information
Public title
A comparative study of objective measurement of sleep state using polysomnography and subjective measurement of sleep state using bed sensor in patients with psychiatric disorders complaining of insomnia
Acronym
A comparative study of objective measurement of sleep state using polysomnography and subjective measurement of sleep state using bed sensor in patients with psychiatric disorders complaining of insomnia
Scientific Title
A comparative study of objective measurement of sleep state using polysomnography and subjective measurement of sleep state using bed sensor in patients with psychiatric disorders complaining of insomnia
Scientific Title:Acronym
A comparative study of objective measurement of sleep state using polysomnography and subjective measurement of sleep state using bed sensor in patients with psychiatric disorders complaining of insomnia
Region
| Japan |
Condition
Condition
Psychiatric patients
Classification by specialty
| Psychiatry |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
The purpose of this study is to obtain heart rate, respiration, and body movement data using bed sensors, and subjective sleep recording using a sleep diary. The depth of sleep measured by PSG will be used as the positive value, and the correlation and relationship with the above data will be examined.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
Correlation of PSG data with heart rate, respiration, and body movement data obtained from bed sensor data
Key secondary outcomes
Association among subjective sleep recordings, PSG data, and data with heart rate, respiration, and body movement data measured by bed sensor
Base
Study type
Observational
Study design
Basic design
Randomization
Randomization unit
Blinding
Control
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment
Intervention
No. of arms
Purpose of intervention
Type of intervention
Interventions/Control_1
Interventions/Control_2
Interventions/Control_3
Interventions/Control_4
Interventions/Control_5
Interventions/Control_6
Interventions/Control_7
Interventions/Control_8
Interventions/Control_9
Interventions/Control_10
Eligibility
Age-lower limit
| 20 | years-old | <= |
Age-upper limit
| Not applicable |
Gender
Male and Female
Key inclusion criteria
Inclusion criteria:
(1) Patients who are hospitalized at Keio University Hospital for treatment or examination of any kind of psychiatric disorder
(2) Patients undergoing PSG testing for sleep disorders
(3) 20 years old or older
(4)Decisionally not impaired judged by treating physician. If judged as decisionally impaired, patients' guardians can give consent
Key exclusion criteria
Exclusion Criteria:
(1) Patients whose illness can be exacerbated by interview of the study.
(2) Patients who are not expected to be able to accurately acquire heart rate and respiration data using bed sensors. Specifically, patients with a history of severe heart disease, patients with significant limitations in physical movement such as paralysis due to stroke or spinal injury, and patients with a BMI of 25 or higher.
(3) Those who are considered to be ineligible by the PI or investigators.
Target sample size
10
Research contact person
Name of lead principal investigator
| 1st name | Taishiro |
| Middle name | |
| Last name | Kishimoto |
Organization
Keio University School of Medicine
Division name
Hills Joint Research Laboratory for Future Preventive Medicine and Wellnes
Zip code
106-0032
Address
Roppongi Hills North Tower 7F, 6-2-31 Roppongi, minato-ku, Tokyo, Japan
TEL
03-5786-0006
tkishimoto@keio.jp
Public contact
Name of contact person
| 1st name | Sayoko |
| Middle name | |
| Last name | Kawano |
Organization
Keio University School of Medicine
Division name
Department of Neuropsychiatry
Zip code
160-8582
Address
35 Shinanomachi, Shinjuku-ku, Tokyo, JAPAN
TEL
03-5363-3971
Homepage URL
sayoko.kawano@adst.keio.ac.jp
Sponsor or person
Institute
Keio University School of Medicine
Institute
Department
Personal name
Funding Source
Organization
National Institutes of Biomedical Innovation, Health and Nutrition
Organization
Division
Category of Funding Organization
Japanese Governmental office
Nationality of Funding Organization
Japan
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
The Clinical and Translational Research Center
Address
35 Shinanomachi, Shinjuku-ku, Tokyo, JAPAN
Tel
03-3353-1211
med-rinri-jimu@adst.keio.ac.jp
Secondary IDs
Secondary IDs
NO
Study ID_1
Org. issuing International ID_1
Study ID_2
Org. issuing International ID_2
IND to MHLW
Institutions
Institutions
慶應義塾大学病院（東京都）
Other administrative information
Date of disclosure of the study information
| 2022 | Year | 03 | Month | 08 | Day |
Related information
URL releasing protocol
NA
Publication of results
Unpublished
Result
URL related to results and publications
NA
Number of participants that the trial has enrolled
10
Results
Based on the approved protocol by ethics committee, 10 patients participants in the study. One of the participants was unable to acquire data due to a poor connection of the equipment, and data were collected from 9 participants.
As a result, we confirmed that the bed sensor could be used to acquire heart rate, respiration, and body movement data, and the feasibility of the study was confirmed.
Results date posted
| 2023 | Year | 11 | Month | 16 | Day |
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
10 patients who were hospitalized for treatment or examination of any psychiatric disorder and who also underwent PSG testing for sleep disorders
6 males, 4 females, mean age 46.2 years
Participant flow
We obtained consent from and enrolled 10 subjects. Data were collected from 9 patients except one who could not record bed sensor data due to equipment failure.
Adverse events
None
Outcome measures
It was confirmed that heart rate, respiration and body movement data can be acquired using bed sensor data, as well as PSG data. It was also confirmed that it was possible to synchronize the timelines of both data sets and calculate the rate of agreement between the data. As this study was positioned as a feasibility study, no statistical analysis was conducted.
Plan to share IPD
IPD sharing Plan description
Progress
Recruitment status
Completed
Date of protocol fixation
| 2021 | Year | 06 | Month | 15 | Day |
Date of IRB
| 2021 | Year | 08 | Month | 10 | Day |
Anticipated trial start date
| 2022 | Year | 01 | Month | 26 | Day |
Last follow-up date
| 2022 | Year | 05 | Month | 30 | Day |
Date of closure to data entry
| 2022 | Year | 05 | Month | 30 | Day |
Date trial data considered complete
| 2022 | Year | 12 | Month | 31 | Day |
Date analysis concluded
| 2023 | Year | 07 | Month | 23 | Day |
Other
Other related information
Observation items and data collection methods
A: Collection of background factors, etc.
Collect demographical/clinical characteristics from chart, ward nursing staff and treating physician.
B: PSG (Polysomnography)
PSG (SOMNO screen BT system; Fukuda Denshi Co., Ltd.) will be performed overnight to measure electroencephalogram, electrocardiogram, electromyogram, pulse oximeter, airflow, nasal pressure, thorax and abdominal movements, snoring, and body position. Based on the measured biometric signals, the technologist classifies sleep into five stages: Wake (wakefulness), REM (rapid eye movement), Non-REM1 (shallow sleep), Non-REM2 (moderate sleep), and Non-REM3 (deep sleep) every 30 seconds.
C: Bed sensor
A sensor unit (MinebeaMitsumi Inc.) is installed at each of the four locations under the bed legs to detect load data. The analog signal of the detected load data is transmitted to the data logger. The data logger digitally processes the transmitted data, extracts the load fluctuations generated by heartbeat, respiration, and body movement data, and transmits the data to a PC connected via USB for recording.
D: Sleep diary
Participants will record subjective information about their own sleep during the study period. The following information will be recorded: time of entry into bed, time of falling asleep, time of waking up, and time of getting out of bed.
E: Sleep observation by nurses
The nurse should use the subjective sleep information of the physician in charge and the ward nurse, as in the case of a routine clinical visit.
Management information
Registered date
| 2022 | Year | 03 | Month | 08 | Day |
Last modified on
| 2023 | Year | 11 | Month | 16 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000053622
