UMIN-CTR Clinical Trial

Basic information
Public title	Prediction of cardiovascular events in chronic obstructive pulmonary disease using a machine learning approach
Acronym	Prediction of CV events in COPD using machine learning
Scientific Title	Prediction of cardiovascular events in chronic obstructive pulmonary disease using a machine learning approach
Scientific Title:Acronym	Prediction of CV events in COPD using machine learning
Region	Japan

Condition
Condition	Chronic obstructive pulmonary disease
Classification by specialty	Medicine in general Cardiology Pneumology Geriatrics
Classification by malignancy	Others
Genomic information	NO

Objectives
Narrative objectives1	To predict cardiovascular events (defined as the incidence of myocadiac infarction, angina, heart failure, arrhythmia, stroke and transient ischemic attack) in COPD patients by using machine learning.
Basic objectives2	Others
Basic objectives -Others	To identify predictors for CV events in COPD patients using machine learning approach.
Trial characteristics_1	Confirmatory
Trial characteristics_2	Pragmatic
Developmental phase	Not applicable

Assessment
Primary outcomes	The accuracy of machine learning algorithm to predict CV events in COPD patients.
Key secondary outcomes	Predictors of CV events identified using machine learning techniques.

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	Not applicable
Age-upper limit	Not applicable
Gender	Male and Female
Key inclusion criteria	1. Having International Classification of Disease, 10th revision [ICD-10] codes for COPD (J41-44) at least once in Sado-Himawari Network, which is the electronic health record (EHR) system in Sado city, Niigata prefecture, Japan. 2. Patients are regardless of inpatients or outpatients.
Key exclusion criteria	Patients with less than 180 days of follow-up in Sado-Himawari Network.
Target sample size	1700

Research contact person
Name of lead principal investigator	1st name Kazuto Middle name Last name Matsunaga
Organization	Yamaguchi University Hospital
Division name	Respiratory Medicine and Infectious Disease
Zip code	755-8505
Address	1-1-1 Minami-Kogushi, Ube, Yamaguchi, 755-8505, Japan
TEL	0836-85-3123
Email	kazmatsu@yamaguchi-u.ac.jp

Public contact
Name of contact person	1st name Kazuki Middle name Last name Hamada
Organization	Yamaguchi University Hospital
Division name	Department of Respiratory Medicine and Infectious Disease
Zip code	755-8505
Address	1-1-1 Minami-Kogushi, Ube, Yamaguchi, 755-8505, Japan
TEL	0836-85-3123
Homepage URL
Email	khamada@yamaguchi-u.ac.jp

Sponsor
Institute	Department of Respiratory Medicine and Infectious Disease, Yamaguchi University Hospital
Institute
Department

Funding Source
Organization	AstraZeneca PLC
Organization
Division
Category of Funding Organization	Profit organization
Nationality of Funding Organization

Other related organizations
Co-sponsor	1. The Council of Sado Regional Health Care 2. Department of Systems Bioinformatics, Graduate School of Medicine, Yamaguchi University 3. AI Systems Medicine Research and Training Center (AISMEC), Graduate School of Medicine, Yamaguchi University and Yamaguchi University Hospital 4. Department of Pulmonary and Gerontology, Graduate School of Medicine, Yamaguchi University
Name of secondary funder(s)

IRB Contact (For public release)
Organization	Center For Clinical Research, Yamaguchi Univesity Hospital
Address	1-1-1 Minami-Kogushi, Ube, Yamaguchi, 755-8505, Japan
Tel	0836-22-2428/+81-836-85-3123
Email	me223@yamaguchi-u.ac.jp

Secondary IDs
Secondary IDs	YES
Study ID_1	ESR-21-21503
Org. issuing International ID_1	AstraZeneca PLC
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 08 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	Open public recruiting
Date of protocol fixation	2022 Year 05 Month 10 Day
Date of IRB	2022 Year 06 Month 02 Day
Anticipated trial start date	2022 Year 06 Month 02 Day
Last follow-up date	2022 Year 06 Month 02 Day
Date of closure to data entry
Date trial data considered complete
Date analysis concluded

Other
Other related information	For convenience, the anticipated trial start date and last follow-up date are registered as the same date due to retrospective and observational design.

Management information
Registered date	2022 Year 08 Month 02 Day
Last modified on	2022 Year 08 Month 02 Day

Link to view the page
URL(English)	https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000054520

Research Plan
Registered date	File name

Research case data specifications
Registered date	File name

Research case data
Registered date	File name

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