Atrial Fibrillation Detecting Software Gung Atrial Fibrillation Detecting Software

May 14, 2023 updated by: Chang Gung Memorial Hospital

A Study to Evaluate Accuracy and Validity of the Chang Gung Atrial Fibrillation Detecting Software

Chang Gung Atrial Fibrillation Detection Software is an artificial intelligence electrocardiogram signal analysis software that detects whether a patient has atrial fibrillation by static 12-lead ECG signals. This study is a non-inferiority test based on the control group. The main purpose is to verify whether Chang Gung atrial fibrillation detection software can correctly identify atrial fibrillation in patients with atrial fibrillation, and can be used to provide a reference for doctors to detect atrial fibrillation.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

This study is a retrospective study, and the data is from the six hospitals of Chang Gung Medical Research Database (CGRD). We collected de-identified static 12-lead electrocardiogram (ECG) data from the database during the period of January 1, 2006, to December 31, 2019.

We created a training set and a testing set of ECG data from the CGRD. Then, we stratified and sampled ECG signals from the testing set according to the actual proportion to obtain the experimental sample.

The computer first preliminarily screened and selected ECG data that met the inclusion and exclusion criteria, and then numbered them sequentially. A cardiologist confirmed that the sampled ECG data did not include exclusion criteria.

The ECG data were converted into images and interpreted for the presence or absence of atrial fibrillation by three cardiologists. Their results were used as the gold standard (reference) for this study.

After determining the experimental standards, the ECG signals were inputted into the Chang Gung Atrial Fibrillation Detection software for analysis and interpretation of each ECG data.

After the software interpretation was completed, the results were compared with the interpretations of the physicians, and the primary and secondary evaluation indicators were analyzed accordingly.

Study Type

Interventional

Enrollment (Actual)

788

Phase

  • Not Applicable

Contacts and Locations

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

Study Locations

  • Taiwan
      • Taoyuan City, Taiwan, 333
        • Chang Gung Memorial Hospital

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

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Equal or greater than twenty years old
  • Static 12-lead electrocardiogram of General Electric MUSE XML format file.
  • The data comes from the static 12-lead electrocardiogram device of General Electric (model MAC5500).
  • The electrocardiogram signal is 500 Hz.
  • The Alternating current (AC) filter of the electrocardiogram signal is 60 Hz.

Exclusion Criteria:

  • Cases used in the model development process.
  • Lacks any electrode.
  • Contain any electrode lacks a segment.
  • Misplaced leads

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

  • Primary Purpose: Diagnostic
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Software diagnosis
Software diagnosis with gold standard of 3 doctors' consensus.
Device: Chang Gung Atrial Fibrillation Detecting Software
This software is expected to be used in clinical testing to interpret the static 12-lead ECG of adults who are over 20 years old and suspected of having atrial fibrillation, detect whether there is a signal of atrial fibrillation, and output the results for clinicians Near-instant auxiliary diagnostic use.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Sensitivity
Time Frame: baseline
The rate of test results that correctly indicate the presence.
baseline

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Specificity
Time Frame: baseline
The rate of test results that correctly indicate the absence.
baseline
Accuracy
Time Frame: baseline
The rate of all test results that correctly indicate.
baseline
Area Under the receiver operating characteristic Curve
Time Frame: baseline
A graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied.
baseline
Positive predictive value
Time Frame: baseline
The proportions of positive results in statistics and diagnostic tests that are true positive results
baseline
Negative predictive value
Time Frame: baseline
The proportions of negative results in statistics and diagnostic tests that are true negative results
baseline
False positive rate
Time Frame: baseline
The rate of test result which wrongly indicates that a particular condition or attribute is present
baseline
False negative rate
Time Frame: baseline
The rate of test result which wrongly indicates that a particular condition or attribute is absent
baseline

Collaborators and Investigators

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

Sponsor

Chang Gung Memorial Hospital

Investigators

  • Study Chair: Chang-Fu Kuo, MD/Ph.D, Associate Professor and Director Division of Rheumatology

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

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 (Actual)

July 11, 2022

Primary Completion (Actual)

February 8, 2023

Study Completion (Actual)

April 10, 2023

Study Registration Dates

First Submitted

May 4, 2023

First Submitted That Met QC Criteria

May 14, 2023

First Posted (Actual)

May 24, 2023

Study Record Updates

Last Update Posted (Actual)

May 24, 2023

Last Update Submitted That Met QC Criteria

May 14, 2023

Last Verified

April 1, 2023

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 202200717A3

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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