A Study to Evaluate Accuracy and Validity of the Chang Gung ECG Abnormality Detection Software
Trial Snapshot
- Phase
- Not Applicable
- Status
- Enrolling By Invitation
- Sponsor
- Enrollment
- 4,306
- Locations
- 1
- Primary Endpoint
- Sensitivity and Specificity
Study Overview
Brief Summary
"Chang Gung ECG Abnormality Detection Software" is a is an artificial intelligence medical signal analysis software that detect whether patients have abnormal ECG signals of 14 diseases by static 12-lead ECG. The 14 diseases were
- Long QT syndrome
- Sinus bradycardia
- Sinus Tachycardia
- Premature atrial complexes
- Premature ventricular complexes
- Atrial Flutter, Right bundle branch block
- Left bundle branch block
- Left Ventricular hypertrophy
- Anterior wall Myocardial Infarction
- Septal wall Myocardial Infarction
- Lateral wall Myocardial Infarction
- Inferior wall Myocardial Infarction
- Posterior wall Myocardial Infarction
The main purpose of this study is to verify whether "Chang Gung ECG Abnormality Detection Software" can correctly identify abnormal ECG signals among patients of 14 diseases. The interpretation standard is the consensus of 3 cardiologists. The results of the software analysis will be used to evaluate the performance of the primary and secondary evaluation indicators.
Detailed Description
Detailed procedure:
- Sample source:
This is a retrospective study, and the data comes from the Chang Gung Medical Research Database(CGRD) which was an database form 6 hospitals of Chang Gung Memorial hospital. We collected de-identified static 12-lead ECG data from the database during 2006.01.01~2019.12.31, and the length of the ECG was 10 seconds. 2. Sampling:
In this experiment, the training dataset and the test dataset ECG were separated. Afterwards, the ECG signals are stratified according to the distribution as the test sample, and all abnormal ECG signals of 14 diseases will be independently sampled from the ECG database of the test set. 3. Confirmation criteria:
The ECG data will be preliminarily screened and selected by the inclusion and exclusion criteria and compiled serial numbers. Then, a cardiologist confirms that the sampling results of the ECG data do not include the exclusion criteria again. 4. Physician interpretation:
Study Design
- Study Type
- Observational
- Observational Model
- Case Control
- Time Perspective
- Retrospective
Eligibility Criteria
- Ages
- 20 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
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.
- •The resource of original diagnosis was a cardiologist.
Exclusion Criteria
- •Cases used in the model development process.
- •Lacks any electrode.
- •Contain any electrode lacks a segment.
Arms & Interventions
Software diagnosis
Software diagnosis with gold standard of 3 cardiologists' interpretation.
Intervention: Chang Gung ECG Abnormality Detection Software (Drug)
Outcomes
Primary Outcomes
Sensitivity and Specificity
Time Frame: baseline
The rate of test results that correctly indicate the presence and absence.
Secondary Outcomes
- Area Under the receiver operating characteristic Curve(Baseline)