UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000042562 |
|---|---|
| Receipt number | R000048585 |
| Scientific Title | Identification of the risk factor for postoperative nausea and vomiting by artificial intelligence analysis; Retrospective study |
| Date of disclosure of the study information | 2022/02/01 |
| Last modified on | 2020/11/26 15:53:39 |
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Basic information
Public title
Identification of the risk factor for postoperative nausea and vomiting by artificial intelligence analysis; Retrospective study
Acronym
Identification of the risk factor for postoperative nausea and vomiting by artificial intelligence analysis; Retrospective study
Scientific Title
Identification of the risk factor for postoperative nausea and vomiting by artificial intelligence analysis; Retrospective study
Scientific Title:Acronym
Identification of the risk factor for postoperative nausea and vomiting by artificial intelligence analysis; Retrospective study
Region
| Japan |
Condition
Condition
Patients with postoperative nausea and vomiting
Classification by specialty
| Anesthesiology |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
We identify the risk factors for postoperative nausea and vomiting (PONV) using the machine learning of artificial intelligence.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
Surgical procedure, anesthesia time, patient information (height, weight, age, complications), amount of anesthetic drugs, intraoperative using drugs, amount of infusion
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
| 20 | years-old | <= |
Age-upper limit
| 100 | years-old | > |
Gender
Male and Female
Key inclusion criteria
Adult patients undergoing non-cardiac surgery under general anesthesia
Key exclusion criteria
Patients under 20 years old, cardiac surgery, thoratic surgery, local anesthesia
Target sample size
500000
Research contact person
Name of lead principal investigator
| 1st name | Hiroshi |
| Middle name | |
| Last name | Hoshijiam |
Organization
Tohoku University Graduate School of Dentistry
Division name
Division of Dento-oral Anesthesiology
Zip code
980-8575
Address
Seiryomachi 4-1, Aoba, Sendai, Miyagi, 980-8575, Japan
TEL
022-717-8420
hhoshi6@gmail.com
Public contact
Name of contact person
| 1st name | Hiroshi |
| Middle name | |
| Last name | Hoshijiam |
Organization
Tohoku University Graduate School of Dentistry
Division name
Division of Dento-oral Anesthesiology
Zip code
980-8575
Address
Seiryomachi 4-1, Aoba, Sendai, Miyagi, 980-8575, Japan
TEL
022-717-8420
Homepage URL
hhoshi6@gmail.com
Sponsor or person
Institute
Tohoku University Graduate School of Dentistry
Institute
Department
Personal name
Funding Source
Organization
Tohoku University Graduate School of Dentistry
Organization
Division
Category of Funding Organization
Other
Nationality of Funding Organization
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
Tohoku University Graduate School of Dentistry
Address
Seiryomachi 4-1, Aoba, Sendai, Miyagi, 980-8575, Japan
Tel
022-717-8420
hhoshi6@gmail.com
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
| 2022 | Year | 02 | 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 | 05 | Month | 01 | Day |
Date of IRB
Anticipated trial start date
| 2021 | Year | 05 | Month | 01 | Day |
Last follow-up date
| 2024 | Year | 06 | Month | 01 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
In this study, we clarify the risk factors of PONV by the self-learning function of artificial intelligence, and discover new risk factors of PONV. By grasping the risk factors of PONV and preventing PONV, it is expected to improve the QOL of postoperative patients and further reduce postoperative human and material costs.
Management information
Registered date
| 2020 | Year | 11 | Month | 26 | Day |
Last modified on
| 2020 | Year | 11 | Month | 26 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000048585
