UMIN-CTR Clinical Trial

Basic information
Public title	Examination of difficult intubation evaluation using face recognition system
Acronym	Examination of difficult intubation evaluation using face recognition system
Scientific Title	Examination of difficult intubation evaluation using face recognition system
Scientific Title:Acronym	Examination of difficult intubation evaluation using face recognition system
Region	Japan

Condition
Condition	Elective surgery patients
Classification by specialty	Anesthesiology
Classification by malignancy	Others
Genomic information	NO

Objectives
Narrative objectives1	The aim is to create a classifier (system) that can determine intubation difficulty using a face authentication system
Basic objectives2	Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase

Assessment
Primary outcomes	Create a classifier (system) that can determine intubation difficulties, make a Receiver operating characteristic curve, and determine sensitivity and specificity
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	Patients undergoing elective surgery at Yamagata University Hospital
Key exclusion criteria	Brain surgery Nasal surgery Dental surgery Thyroid surgery Cervical spine surgery
Target sample size	200

Research contact person
Name of lead principal investigator	1st name Tatsuya Middle name Last name Hayasaka
Organization	Yamagata University Faculty of Medicine
Division name	Department of Anesthesia
Zip code	9909585
Address	2-2-2 Iida-nishi, Yamagata city, Yamagata 990-9585, Japan
TEL	023-628-5400
Email	hayasakatatsuya1101@gmail.com

Public contact
Name of contact person	1st name Tatsuya Middle name Last name Hayasaka
Organization	Yamagata University Faculty of Medicine
Division name	Department of Anesthesia
Zip code	9909585
Address	2-2-2 Iida-nishi, Yamagata city, Yamagata 990-9585, Japan
TEL	023-628-5400
Homepage URL
Email	hayasakatatsuya1101@gmail.com

Sponsor
Institute	Yamagata University Faculty of Medicine
Institute
Department

Funding Source
Organization	Department of Anesthesiology, Yamagata University Faculty of Medicine
Organization
Division
Category of Funding Organization	Self funding
Nationality of Funding Organization

Other related organizations
Co-sponsor
Name of secondary funder(s)

IRB Contact (For public release)
Organization	The Ethical Review Committee of Yamagata University Faculty of Medicine
Address	2-2-2, Iida-nishi, yamagata-shi, Yamagata JAPAN
Tel	0236285015
Email	ikekenkyu@jm.kj.yamagata-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

Other administrative information
Date of disclosure of the study information	2020 Year 05 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	Completed
Date of protocol fixation	2020 Year 04 Month 01 Day
Date of IRB	2020 Year 01 Month 31 Day
Anticipated trial start date	2020 Year 04 Month 10 Day
Last follow-up date	2030 Year 03 Month 31 Day
Date of closure to data entry
Date trial data considered complete
Date analysis concluded

Other

Other related information

An anesthesiologist performs a tracheal intubation with a Macintosh laryngoscope as usual, and records the Cormack classification (degree of intubation difficulty) in the medical record as usual. After the operation, collect patient information on airway management while grasping the Cormack classification. In addition, a plurality of photographs such as a frontal photograph and a profile photograph of the patient are taken. Machine learning is performed, and a classifier is created as supervised learning. Then create an Receiver operating characteristic curve to determine sensitivity and specificity.

Management information
Registered date	2020 Year 04 Month 10 Day
Last modified on	2020 Year 09 Month 03 Day

Link to view the page
URL(English)	https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000045753