About this trial
The study objective is to evaluate the effectiveness of the ECGio algorithm in predicting clinically significant coronary artery disease . ECGio's diagnostic performance during the trial will be compared against an objective performance ¬criteria using a mixed reference standard of quantitative coronary angiography and quantitative coronary computed tomography angiography in patients a general adult population under suspicion of coronary artery disease.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Patients 18 years of age or older at time of data collection.
Patients with medical records stored in a digitized format.
Patients under suspicion of coronary artery disease (both suspicion of significant coronary artery disease as well as to rule out significant CAD) who present to the site with an electrocardiogram recorded up to 30 days prior to Coronary Computed Tomography Angiography.
Disqualifiers
Patients with acute coronary syndrome.
Patients who previously underwent coronary artery bypass grafting.
Patients whose electrocardiogram tracing has extreme noise or artifact to the extent that it would be recommended to redo the tracing.
Patients with prior percutaneous coronary intervention resulting in stenting.
Trial population
The study population will be made up of all-comers to Coronary Computed Tomography Angiography from each site taking up to the first 250, consecutive patients recruited for the analysis.
Trial design
Cohort
Retrospective
Treatments tested in this trial
AI-ECG Analysis
DeviceThe AI-Analysis done on the ECGs in a retrospective fashion
Treatment groups
Trial outcomes
Primary outcomes
Sensitivity & Specificity
The lower 95% bound of ECGio's sensitivity and specificity in patients who underwent invasive angiography or computed tomography angiography (Co-primary endpoints)
Secondary outcomes
Sensitivity & Specificity
The lower 95% bound of ECGio's sensitivity and specificity in patients who underwent invasive angiography (Co-secondary endpoints) in enrollment period 2
Demographic Performance
ECGio's predictive performance across different demographic groups (e.g Race, Sex, Risk Factors)
Angiographic Stenosis Prediction
The Root Mean Squared Error in predicting the greatest diameter stenosis per vessel (Left Main Artery, Left Anterior Descending Artery, Left Circumflex Artery, Right Coronary Artery)
Sponsors and contacts
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