UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000041289 |
|---|---|
| Receipt number | R000047155 |
| Scientific Title | Development of an AI-based system for predicting falls and fall-related injuries in hospitals |
| Date of disclosure of the study information | 2020/08/03 |
| Last modified on | 2022/08/05 16:59:44 |
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Basic information
Public title
Development of an AI-based system for predicting falls and fall-related injuries in hospitals
Acronym
Development of an AI-based system for predicting falls and fall-related injuries in hospitals
Scientific Title
Development of an AI-based system for predicting falls and fall-related injuries in hospitals
Scientific Title:Acronym
Development of an AI-based system for predicting falls and fall-related injuries in hospitals
Region
| Japan |
Condition
Condition
None (All patients admitted during the study period)
Classification by specialty
| Not applicable |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
Development and validation of a system for predicting falls and fall-related injuries in hospital with large data sets.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
Falls and fall-related injuries obtained from incident reports
Key secondary outcomes
Scores of fall risk assessment tool
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
| Not applicable |
Age-upper limit
| Not applicable |
Gender
Male and Female
Key inclusion criteria
The patients who had been hospitalized in Fujita Health University Hospital from April 2012 to March 2020 and those who had been hospitalized in Fujita Health University Nanakuri Memorial Hospital from April 2016 to March 2020.
Key exclusion criteria
A person who has asked to be excluded from the study to the researcher listed in the disclosure document on the website.
Target sample size
300000
Research contact person
Name of lead principal investigator
| 1st name | Yohei |
| Middle name | |
| Last name | Otaka |
Organization
Fujita Health University
Division name
Department of Rehabilitation Medicine I, School of Medicine
Zip code
470-1192
Address
1-98 Dengakugakubo, Kutsukake, Toyoake, Aichi
TEL
0562-93-2167
yootaka@fujita-hu.ac.jp
Public contact
Name of contact person
| 1st name | Shin |
| Middle name | |
| Last name | Kitamura |
Organization
Fujita Health University
Division name
Faculty of Rehabilitation, School of Health Sciences
Zip code
470-1192
Address
1-98 Dengakugakubo, Kutsukake, Toyoake, Aichi
TEL
0562-93-9000
Homepage URL
shin.kitamura@fujita-hu.ac.jp
Sponsor or person
Institute
Fujita Health University
Institute
Department
Personal name
Funding Source
Organization
None
Organization
Division
Category of Funding Organization
Self funding
Nationality of Funding Organization
Other related organizations
Co-sponsor
FRONTEO, Inc.
Name of secondary funder(s)
IRB Contact (For public release)
Organization
Fujita Health University
Address
1-98 Dengakugakubo, Kutsukake, Toyoake, Aichi
Tel
0562-93-2865
f-irb@fujita-hu.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
藤田医科大学（愛知県）
Other administrative information
Date of disclosure of the study information
| 2020 | Year | 08 | Month | 03 | 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
69291
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
No longer recruiting
Date of protocol fixation
| 2020 | Year | 05 | Month | 25 | Day |
Date of IRB
| 2020 | Year | 07 | Month | 27 | Day |
Anticipated trial start date
| 2020 | Year | 08 | Month | 03 | Day |
Last follow-up date
| 2025 | Year | 03 | Month | 31 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
We will retrospectively analyze the medical records of patients who had been hospitalized in the two hospitals. The data will be divided into two parts. Using one of the data sets, we will develop an AI-based prediction system for the risks for falls and fall-related injuries for each patient. Then, we will validate the system against the actual incidents and the scores of the fall risk assessed tools using the other data sets.
Management information
Registered date
| 2020 | Year | 08 | Month | 03 | Day |
Last modified on
| 2022 | Year | 08 | Month | 05 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047155
