Analysis of ECGio to Predict Coronary Stenosis Against a Mixed Reference Standard
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: AI-ECG Analysis.
- Who it may be relevant to
- Registry conditions: Coronary Artery Disease (CAD). Basic parameters: 18 years — 89 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United States
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
A Study to Measure Underlying Coronary Stenosis; a Retrospective, Multi-center Study to Measure Efficacy of ECGio Against Multiple Reference Standards
Overview
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.
Interventions
- Device AI-ECG Analysis
The AI-Analysis done on the ECGs in a retrospective fashion
Primary outcome measures
- Sensitivity & Specificity [Time frame: Within 30 days of enrollment]
Secondary outcome measures (3)
- Sensitivity & Specificity [Time frame: For the first 300 patients referred to invasive angiography through study completion, an average of 90 days]
- Demographic Performance [Time frame: For patients in the 30 days following computed tomography angiography]
- Angiographic Stenosis Prediction [Time frame: For the first 300 patients referred to invasive angiography through study completion, an average of 90 days]
Eligibility criteria
Inclusion criteria
- 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.
Exclusion criteria
- 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.
- Unanalyzable invasive coronary angiogram.
- Unanalyzable Coronary Computed Tomography Angiography.
- Unanalyzable electrocardiogram signal.
- Incomplete invasive coronary angiogram (e.g., only the right coronary artery was injected and visualized).
- Patient core lab analyzed Coronary Computed Tomography Angiography showed ≥ 50% blockage in any vessel but patient was not referred to invasive coronary angiogram.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
United States · 2 centers
- Medstar Washington Hospital Center — Washington D.C.
- Cena Research Institute — Houston
Publications
- Leasure M, Jain U, Butchy A, Otten J, Covalesky VA, McCormick D, Mintz GS. Deep Learning Algorithm Predicts Angiographic Coronary Artery Disease in Stable Patients Using Only a Standard 12-Lead Electrocardiogram. Can J Cardiol. 2021 Nov;37(11):1715-1724. doi: 10.1016/j.cjca.2021.08.005. Epub 2021 Aug 20. PMID 34419615
Identifiers
NCT: NCT07375810 · HIO0004A