UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000044665 |
|---|---|
| Receipt number | R000050967 |
| Scientific Title | Creating a model to support clinical decision by predicting intraoperative vital signs using artificial Intelligence |
| Date of disclosure of the study information | 2021/07/01 |
| Last modified on | 2021/06/25 21:33:51 |
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Basic information
Public title
Development of vital signs prediction model using artificial intelligence:Supporting clinical decision.
Acronym
Development of vital signs prediction model using artificial intelligence:Supporting clinical decision.
Scientific Title
Creating a model to support clinical decision by predicting intraoperative vital signs using artificial Intelligence
Scientific Title:Acronym
Creating a model to support clinical decision by predicting intraoperative vital signs using artificial Intelligence
Region
| Japan |
Condition
Condition
Patient for operation under general anesthesia
Classification by specialty
| Anesthesiology |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
To create a simulation model to predict intraoperative vital signs, and to validate and evaluate the model.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
Intraoperative vital signs: systolic blood pressure, mean blood pressure, diastolic blood pressure, heart rate.
Key secondary outcomes
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
| 1 | days-old | <= |
Age-upper limit
| 150 | years-old | > |
Gender
Male and Female
Key inclusion criteria
Patients who underwent surgery under the anesthesiologist in the operating room of Kansai Rosai Hospital from July 2011
Key exclusion criteria
If the patient or the patient's guardian refuses to participate in the research.
Patients who are judged inappropriate by the principal investigator
Target sample size
40000
Research contact person
Name of lead principal investigator
| 1st name | Hiroshi |
| Middle name | |
| Last name | Ueyama |
Organization
Kansai Rosai Hospital
Division name
Department of Anesthesiology
Zip code
660-8511
Address
3-1-69, Inabasou,Amagasaki,Hyougo,Japan
TEL
06-6416-1221
ueyama-hiroshi@kansaih.johas.go.jp
Public contact
Name of contact person
| 1st name | Hiroshi |
| Middle name | |
| Last name | Ueyama |
Organization
Kansai Rosai Hospital
Division name
Department of Anesthesiology
Zip code
660-8511
Address
3-1-69, Inabasou,Amagasaki,Hyougo,Japan
TEL
06-6416-1221
Homepage URL
ueyama-hiroshi@kansaih.johas.go.jp
Sponsor or person
Institute
Kansai Rosai Hospital
Institute
Department
Personal name
Funding Source
Organization
Philips Japan, LTD.
Organization
Division
Category of Funding Organization
Profit organization
Nationality of Funding Organization
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
Ethics Committee, Kansai Rosai Hospital
Address
3-1-69, Inabasou,Amagasaki,Hyougo,Japan
Tel
06-6416-1221
postmaster@kansaih.johas.go.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
| 2021 | Year | 07 | Month | 01 | 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
Preinitiation
Date of protocol fixation
| 2021 | Year | 03 | Month | 05 | Day |
Date of IRB
| 2021 | Year | 03 | Month | 05 | Day |
Anticipated trial start date
| 2021 | Year | 07 | Month | 01 | Day |
Last follow-up date
| 2023 | Year | 03 | Month | 31 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
Verifying the accuracy of AI-based predictions of vital signs using validation data.
Management information
Registered date
| 2021 | Year | 06 | Month | 25 | Day |
Last modified on
| 2021 | Year | 06 | Month | 25 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000050967
