UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000041243 |
|---|---|
| Receipt number | R000047095 |
| Scientific Title | Development of anesthesia management robot that deeply learns signs of upper airway obstruction and diagnosis/procedure data of anesthesiologist |
| Date of disclosure of the study information | 2020/07/29 |
| Last modified on | 2021/01/28 09:19:59 |
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Basic information
Public title
Development of anesthesia management robot that deeply learns signs of upper airway obstruction and diagnosis/procedure data of anesthesiologist
Acronym
Development of anesthesia management robot
Scientific Title
Development of anesthesia management robot that deeply learns signs of upper airway obstruction and diagnosis/procedure data of anesthesiologist
Scientific Title:Acronym
Development of anesthesia management robot
Region
| Japan |
Condition
Condition
dentistry
Classification by specialty
| Anesthesiology | Dental medicine |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
The main purpose of this study is to digitize quantifiable items from various physiological functions that regulate the respiratory function during sedation into large-scale data, and use AI (artificial intelligence) to determine the severity of anesthesiologist illness. It is to develop an anesthesia management robot equipped with a new AI respiration monitor by performing deep learning using the judgment of the degree and the treatment of airway maintenance as teacher data.
Basic objectives2
Others
Basic objectives -Others
Sedation and non-intubation intravenous anesthesia have been applied in cases such as minor surgical operations/procedures, examinations, and dental treatments, but because they are managed under spontaneous breathing, there is always a risk of upper airway obstruction. is there. During sedation, respiratory management is performed by performing continuous measurements such as transcutaneous oxygen saturation, but the current condition is that no early signs of upper airway obstruction can be detected, and oxygen saturation is below 90%. After it began to decline, hypoxemia worsened suddenly, and in cases where the anesthesiologist was not involved in systemic management, it became a clinically extremely dangerous condition, such as delays in the airway maintenance of medical personnel. Could be. Therefore, it is necessary to detect the signs of upper airway obstruction early and generalize the diagnosis and treatment by anesthesiologists.
Trial characteristics_1
Others
Trial characteristics_2
Others
Developmental phase
Not applicable
Assessment
Primary outcomes
Item 1: Waveform data of airflow limitation during inspiration and expiration obtained with a nasal mask
Item 2: Carbon dioxide data by capnograph with nasal cannula
Item 3: Movement data of forehead, temporal region, chin, chest, and abdomen using an acceleration sensor
Item 4: Percutaneous arterial oxygen saturation data
Item 5: Depth of anesthesia data by BIS monitor and EMG activity
Item 6 (Teacher data): Anesthesiologist's determination of upper airway obstruction during sedation and treatment data are created in advance by selective formation, and comments and correspondence are leveled.
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
| Not applicable |
Gender
Male and Female
Key inclusion criteria
Twenty adult healthy volunteers (volunteers) who agreed with the explanation of the content of the research plan are targeted.
Key exclusion criteria
1)Patients with serious respiratory illness
2) Patients with serious cardiovascular disease
3)Diabetes patients with poor control
4)Severe renal disorder patient
5)Severe liver disorder patient
6)Patients who have hypersensitivity (allergy) to the drug to be used
7)Patients who are judged to be unsuitable by the research supervisor or the co-workers
Target sample size
20
Research contact person
Name of lead principal investigator
| 1st name | Takao |
| Middle name | |
| Last name | Ayuse |
Organization
Nagasaki University
Division name
Dental Anesthesiology
Zip code
8528588
Address
Sakamoto Nagasaki Jpan
TEL
81958197713
ayuse@nagasaki-u.ac.jp
Public contact
Name of contact person
| 1st name | Takao |
| Middle name | |
| Last name | Ayuse |
Organization
Nagasaki University Hospital
Division name
Dental Anesthesiology
Zip code
81958197713
Address
Sakamoto Nagasaki Jpan
TEL
81958197713
Homepage URL
ayuse@nagasaki-u.ac.jp
Sponsor or person
Institute
Nagasaki University
Institute
Department
Personal name
Funding Source
Organization
Nagasaki University
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
Nagasaki university
Address
Sakamoto Nagasaki Jpan
Tel
0958197714
ayuse@nagasaki-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
長崎県
Other administrative information
Date of disclosure of the study information
| 2020 | Year | 07 | Month | 29 | 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
| 2020 | Year | 06 | Month | 16 | Day |
Date of IRB
| 2020 | Year | 07 | Month | 29 | Day |
Anticipated trial start date
| 2020 | Year | 08 | 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
NONE
Management information
Registered date
| 2020 | Year | 07 | Month | 29 | Day |
Last modified on
| 2021 | Year | 01 | Month | 28 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047095
