UMIN-CTR Clinical Trial

Basic information
Public title	Using machine learning to create a system for predicting blood pressure decline from thermographic images during anesthesia induction
Acronym	Using machine learning to create a system for predicting blood pressure decline from thermographic images during anesthesia induction
Scientific Title	Using machine learning to create a system for predicting blood pressure decline from thermographic images during anesthesia induction
Scientific Title:Acronym	Using machine learning to create a system for predicting blood pressure decline from thermographic images during anesthesia induction
Region	Japan

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

Objectives
Narrative objectives1	The purpose of this study is to create a classifier (system) that can discriminate cases where blood pressure drops during induction of anesthesia from thermographic images at the time of entering the operating room using an image analysis system and machine learning.
Basic objectives2	Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase

Assessment
Primary outcomes	Create a classifier (system) that can discriminate between drops in blood pressure, create 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	18 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	Cardiac surgery Patients with predicted peripheral circulatory blood flow disturbances
Target sample size	500

Research contact person
Name of lead principal investigator	1st name Misato Middle name Last name Kurota
Organization	Yamagata University Faculty of Medicine
Division name	Department of Anesthesiology
Zip code	9909585
Address	2-2-2 Iida-nishi, Yamagata city, Yamagata, Japan
TEL	023-628-5400
Email	patsykurota224@gmail.com

Public contact
Name of contact person	1st name Misato Middle name Last name Kurota
Organization	Yamagata University Faculty of Medicine
Division name	Department of Anesthesiology
Zip code	9909585
Address	2-2-2 Iida-nishi, Yamagata city, Yamagata, Japan
TEL	023-628-5400
Homepage URL
Email	patsykurota224@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	2021 Year 07 Month 02 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 06 Month 01 Day
Date of IRB	2021 Year 06 Month 28 Day
Anticipated trial start date	2021 Year 07 Month 05 Day
Last follow-up date	2025 Year 12 Month 31 Day
Date of closure to data entry
Date trial data considered complete
Date analysis concluded

Other

Other related information

An anesthesiologist will administer anesthesia as usual and record the degree of hypotension. Before entering the operating room, a frontal photograph of the patient and thermographic images of both hands are taken. Machine learning is performed and a classifier is created as supervised learning. After that, a receiver operating characteristic curve is created, and sensitivity and specificity are obtained.

Management information
Registered date	2021 Year 07 Month 01 Day
Last modified on	2021 Year 07 Month 01 Day

Link to view the page
URL(English)	https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000051084