Artificial Intelligence-enabled Large-scale Electrocardiogram Feature Extraction and Exploring Association Between the Extracted Features and Mortality, Stroke or Various Health Outcome of Interest

December 22, 2023 updated by: Yonsei University
  • In this study, large-scale ECG data (Electrocardiogram data of all patients stored in the MUSE system by measuring standard 12-guided ECG at Severance Health Checkup at Severance Hospital from November 1, 2005 to October 31, 2022) are combined with electronic medical records, National Health Insurance Corporation data, and National Statistical Office death cause data, and the artificial intelligence algorithm is used to extract ECG features to analyze the association between death, stroke, and various health conditions, and to conduct external verification or transfer learning using public databases (e.g., UK Biobank data).
  • Intended to use a web-based artificial intelligence platform to distribute computational loads generated during large-scale data processing and improve analysis accuracy and efficiency.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Not yet recruiting

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Detailed Description

  • All patient IDs obtained from the main office are replaced by research IDs (de-identified IDs), so the actual ID is not exposed and other personal identification information (name, resident registration number) is not collected.

  • Research Methods:

    1. Electrocardiogram extraction based on the criteria of subjects.
    2. Combined with extracted ECG data and National Insurance Corporation data (+ National Statistical Office cause of death data).
    3. Health out of interest (HOI) definition. Includes death, stroke, etc.
    4. The defined HOI can be extracted from Yonsei Medical Center data or from National Insurance Service data or Statistics Korea's cause of death data.
    5. Artificial intelligence model training with electrocardiogram (and clinical information diagram if necessary) as input, utilizing supervised deep learning algorithms if there is a label and unsupervised learning algorithms if there is no label.
    6. Performance evaluation for supervised learning artificial intelligence models.
    7. In the case of unsupervised learning artificial intelligence models, the association/correlation between extracted features and HOI or predictability/detectability analysis.
    8. Transfer learning can be performed by adding external verification or dielectric data to the learned model using public databases.
    9. External verification can be performed using external additional data by mounting the learned model on a web-based artificial intelligence platform.
    10. Considering large-scale data, computing workloads can be distributed using web-based artificial intelligence platforms.
    11. The analysis results can be anonymized and the analysis results can be provided to researchers through a web-based artificial intelligence platform.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Estimated)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
3000000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact

The name and contact information for the person who can answer enrollment questions for a clinical study. Each location where the study is being conducted may also have a specific contact, who may be better able to answer those questions.
  • Name: Hui-Nam Pak
  • Phone Number: 82-2-2228-8459
  • Email: hnpak@yuhs.ac

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

All patients stored in the MUSE system after measuring a standard 12-guided electrocardiogram at Severance Health Checkup at Severance Hospital from November 1, 2005 to October 31, 2022

Description

Inclusion Criteria:

All patients stored in the MUSE system after measuring a standard 12-guided electrocardiogram at Severance Health Checkup at Severance Hospital from November 1, 2005 to October 31, 2022

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
Number of patients with Mortality
Time Frame: 2 years
Investigating the reproducibility of mortality prediction (number of patients who died regardless of any cause) from ECG data measured within 1 year before death using artificial intelligence algorithms
2 years
Number of patients with Stroke, Atrial Fibrillation, Dementia
Time Frame: 2 years
Investigating the correlation of certain patterns of ECG with the possibility of stroke/Atrial Fibrillation, Dementia using artificial intelligence algorithms.
2 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
Yonsei University

Investigators

Investigators

A researcher involved in a clinical study. Related terms include site principal investigator, site sub-investigator, study chair, study director, and study principal investigator.
  • Principal Investigator: Hui-Nam Pak, Yonsei University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
December 1, 2023

Primary Completion (Estimated)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
December 1, 2025

Study Completion (Estimated)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
December 1, 2025

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
November 22, 2023

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
December 21, 2023

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
December 22, 2023

Study Record Updates

Last Update Posted (Estimated)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
January 1, 2024

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
December 22, 2023

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
December 1, 2023

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • 4-2022-1506

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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