[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT07375810":3,"trial-entities:NCT07375810":110,"trial-summary:NCT07375810":113},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":7,"overall_status":8,"completion_date":9,"status_verified_date":10,"last_update_date":11,"start_date":12,"sponsor_name":13,"lead_sponsor_class":14,"has_dmc":15,"brief_summary":16,"detailed_description":17,"conditions":18,"keywords":20,"study_type":24,"primary_purpose":17,"phases":25,"enrollment_info":26,"interventions":29,"primary_outcomes":38,"secondary_outcomes":43,"sex":54,"minimum_age":55,"maximum_age":56,"healthy_volunteers":15,"eligibility_criteria":57,"std_ages":61,"locations":64,"central_contacts":95,"overall_officials":100,"references":104,"see_also_links":109},"NCT07375810","HIO0004A","Analysis of ECGio to Predict Coronary Stenosis Against a Mixed Reference Standard","A Study to Measure Underlying Coronary Stenosis; a Retrospective, Multi-center Study to Measure Efficacy of ECGio Against Multiple Reference Standards","NOT_YET_RECRUITING","2026-09-01","2026-03","2026-03-30","2026-04-01","Heart Input Output Inc","INDUSTRY",false,"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.",null,[19],"Coronary Artery Disease (CAD)",[21,22,23],"Artificial Intelligence","Electrocardiogram","Coronary Artery Disease","OBSERVATIONAL",[],{"count":27,"type":28},978,"ESTIMATED",[30],{"type":31,"name":32,"description":33,"armGroupLabels":34},"DEVICE","AI-ECG Analysis","The AI-Analysis done on the ECGs in a retrospective fashion",[35,36,37],"CT Angiogram","Enrollment Period 2","Invasive Angiography",[39],{"measure":40,"description":41,"timeFrame":42},"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)","Within 30 days of enrollment",[44,47,51],{"measure":40,"description":45,"timeFrame":46},"The lower 95% bound of ECGio's sensitivity and specificity in patients who underwent invasive angiography (Co-secondary endpoints) in enrollment period 2","For the first 300 patients referred to invasive angiography through study completion, an average of 90 days",{"measure":48,"description":49,"timeFrame":50},"Demographic Performance","ECGio's predictive performance across different demographic groups (e.g Race, Sex, Risk Factors)","For patients in the 30 days following computed tomography angiography",{"measure":52,"description":53,"timeFrame":46},"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)","ALL","18 Years","89 Years",{"inclusion":58,"exclusion":59,"raw_text":60},[],[],"Inclusion Criteria:\n\n1. Patients 18 years of age or older at time of data collection.\n2. Patients with medical records stored in a digitized format.\n3. 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.\n\nExclusion Criteria:\n\n1. Patients with acute coronary syndrome.\n2. Patients who previously underwent coronary artery bypass grafting.\n3. Patients whose electrocardiogram tracing has extreme noise or artifact to the extent that it would be recommended to redo the tracing.\n4. Patients with prior percutaneous coronary intervention resulting in stenting.\n5. Unanalyzable invasive coronary angiogram.\n6. Unanalyzable Coronary Computed Tomography Angiography.\n7. Unanalyzable electrocardiogram signal.\n8. Incomplete invasive coronary angiogram (e.g., only the right coronary artery was injected and visualized).\n9. Patient core lab analyzed Coronary Computed Tomography Angiography showed ≥ 50% blockage in any vessel but patient was not referred to invasive coronary angiogram.",[62,63],"ADULT","OLDER_ADULT",[65,80],{"facility":66,"city":67,"state":68,"zip":69,"country":70,"contacts":71,"geoPoint":77},"Medstar Washington Hospital Center","Washington D.C.","District of Columbia","20010","United States",[72],{"name":73,"role":74,"phone":75,"email":76},"Hector Garcia, M.D","CONTACT","(202) 877-7000","Hector.M.GarciaGarcia@medstar.net",{"lat":78,"lon":79},38.89511,-77.03637,{"facility":81,"city":82,"state":83,"zip":84,"country":70,"contacts":85,"geoPoint":92},"Cena Research Institute","Houston","Texas","77055",[86,90],{"name":87,"role":74,"phone":88,"email":89},"Asif Ali, MD","713-464-4140","drasif@hccheart.com",{"name":87,"role":91},"PRINCIPAL_INVESTIGATOR",{"lat":93,"lon":94},29.76328,-95.36327,[96],{"name":97,"role":74,"phone":98,"email":99},"Michael Leasure","6104517343","Michael.Leasure@heartio.ai",[101],{"name":102,"affiliation":103,"role":91},"Gary S Mintz","CardioVascular Research Foundation",[105],{"pmid":106,"type":107,"citation":108},"34419615","BACKGROUND","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\u002Fj.cjca.2021.08.005. Epub 2021 Aug 20.",[],{"nct_id":4,"conditions":111,"biomarkers":112},[23],[],{"nct_id":4,"found":114,"summary":115,"prompt_version":125},true,{"design":116,"status":117,"heading":118,"summary":119,"follow_up":120,"word_count":121,"commitments":122,"compensation":123,"drugs_mentioned":124},"This is an observational study, meaning researchers will analyze existing data. It aims to include 978 participants.","completed","Observational Study of ECGio for Coronary Artery Disease","This observational study is looking at how well an artificial intelligence (AI) tool called ECGio can predict if someone has significant coronary artery disease (CAD), which is a narrowing of the heart's arteries. Researchers will analyze existing electrocardiograms (ECGs) using the ECGio tool. They will compare ECGio's predictions against results from other heart imaging tests, like coronary angiography and CT angiography. The study aims to enroll 978 adults, aged 18 to 89, who are suspected of having CAD. The main goal is to see how accurate ECGio is at identifying CAD within 30 days of when the ECG was recorded. The current status of this study is unclear.","The primary endpoints (Sensitivity & Specificity) are measured within 30 days of enrollment.",108,"Not specified in the trial record.","Not stated in the trial record.",[],"v2"]