UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000052154 |
|---|---|
| Receipt number | R000059347 |
| Scientific Title | Establishment of a quantitative evaluation method using sensor based measurements of gait and physical activity in the elderly and development of a predictive model for falls |
| Date of disclosure of the study information | 2023/09/08 |
| Last modified on | 2023/09/08 18:49:42 |
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Basic information
Public title
Establishment of sensor-based measurement of gait and physical activity in the elderly and development of a fall risk prediction model
Acronym
Establishment of sensor-based measurement of gait and physical activity in the elderly and development of a fall risk prediction model
Scientific Title
Establishment of a quantitative evaluation method using sensor based measurements of gait and physical activity in the elderly and development of a predictive model for falls
Scientific Title:Acronym
Establishment of a quantitative evaluation method using sensor based measurements of gait and physical activity in the elderly and development of a predictive model for falls
Region
| Japan |
Condition
Condition
gait and fall
Classification by specialty
| Not applicable | Adult |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
To establish a method to stably measure the biomechanics of gait in the elderly with reduced physical function using sensor technology and establish a model to predict the risk of falling based on the biomechanical data of gait.
Basic objectives2
Others
Basic objectives -Others
To identify barriers to measuring gait mechanics using acceleration sensors in the elderly and establish a method that allows to collect data in fast, easy, and safe ways. Furthermore, we aim to find a new reliable fall risk prediction model by multimodal machine learning and other methods.
Trial characteristics_1
Exploratory
Trial characteristics_2
Others
Developmental phase
Not applicable
Assessment
Primary outcomes
Association between falls or history of falls and measures of gait performance
Key secondary outcomes
Whether experienced nurses' predictions of falls correlate with actual falls and sensor data.
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
Patients with written consent, aged 50 years or older, who are inpatients or outpatients of Osaka University Hospital or Yokohama City University Medical Center.
Consenting adults over the age of 20 gathered through public solicitation via the Internet, posters, and other notifications.
Key exclusion criteria
Those with orthopedic problems or neurologic diseases that affect gait, and others deemed unsuitable by the investigators.
Target sample size
1000
Research contact person
Name of lead principal investigator
| 1st name | Kazue |
| Middle name | |
| Last name | Nakajima |
Organization
Osaka University
Division name
Osaka University Hospital
Zip code
565-0871
Address
2-15 Yamadaoka, Suita, Osaka, Japan
TEL
06-6879-5111
kazuen@hp-cqm.med.osaka-u.ac.jp
Public contact
Name of contact person
| 1st name | Hitoshi |
| Middle name | |
| Last name | Sato |
Organization
Osaka University
Division name
Osaka University Hospital
Zip code
565-0871
Address
2-15 Yamadaoka, Suita, Osaka, Japan
TEL
06-6879-5111
Homepage URL
sjinkun@yokohama-cu.ac.jp
Sponsor or person
Institute
Osaka University
Institute
Department
Personal name
Funding Source
Organization
Osaka University
Organization
Division
Category of Funding Organization
Other
Nationality of Funding Organization
Other related organizations
Co-sponsor
Yokohama City University Medical Center
Name of secondary funder(s)
ASICS Corporation
IRB Contact (For public release)
Organization
Ethic Review Board Osaka University Hospital
Address
2-2 Yamadaoka, Suita, Osaka, Japan Advanced Medical Innovation Center Building 4F
Tel
06-6210-8270
rinri@hp-crc.med.osaka-u.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
Other administrative information
Date of disclosure of the study information
| 2023 | Year | 09 | Month | 08 | Day |
Related information
URL releasing protocol
Publication of results
Unpublished
Result
URL related to results and publications
Number of participants that the trial has enrolled
Results
Results date posted
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
Participant flow
Adverse events
Outcome measures
Plan to share IPD
IPD sharing Plan description
Progress
Recruitment status
Enrolling by invitation
Date of protocol fixation
| 2023 | Year | 04 | Month | 17 | Day |
Date of IRB
| 2023 | Year | 04 | Month | 17 | Day |
Anticipated trial start date
| 2023 | Year | 08 | Month | 28 | Day |
Last follow-up date
| 2028 | Year | 08 | Month | 28 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
(Participants)
Patients written consent, aged 50 years or older who are inpatients or outpatients of Osaka University Hospital or Yokohama City University Medical Center.
Consenting adults over the age of 20 gathered through public solicitation via the Internet, posters, and other notifications.
(Primary Outcome)
Association between falls or history of falls and measures of gait performance
(Secondary Outcome)
Whether experienced nurses' predictions of falls correlate with actual falls and sensor data.
(Measurements)
Demographic data
Past history
Medication
Physical ability
History of fall
Occurrence of falls per year after measurement
Perceptions of falls by the individual and family
Data obtained from acceleration sensors
Data obtained from motion capture
Information about daily life
Management information
Registered date
| 2023 | Year | 09 | Month | 08 | Day |
Last modified on
| 2023 | Year | 09 | Month | 08 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000059347
