UMIN-CTR Clinical Trial

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

dentistry

Classification by specialty

Anesthesiology

Dental medicine

Classification by malignancy

Others

Genomic information

NO

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

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

Study type

Observational

Basic design

Randomization

Randomization unit

Blinding

Control

Stratification

Dynamic allocation

Institution consideration

Blocking

Concealment

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

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

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

Email

ayuse@nagasaki-u.ac.jp

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

Email

ayuse@nagasaki-u.ac.jp

Institute

Nagasaki University

Institute

Department

Personal name

Organization

Nagasaki University

Organization

Division

Category of Funding Organization

Other

Nationality of Funding Organization

Co-sponsor

Name of secondary funder(s)

Organization

Nagasaki university

Address

Sakamoto Nagasaki Jpan

Tel

0958197714

Email

ayuse@nagasaki-u.ac.jp

Secondary IDs

NO

Study ID_1

Org. issuing International ID_1

Study ID_2

Org. issuing International ID_2

IND to MHLW

Institutions

長崎県

Date of disclosure of the study information

2020

Year

07

Month

29

Day

URL releasing protocol

Publication of results

Unpublished

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

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 related information

NONE

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