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Cardiogoniometry for Detecting Coronary Artery Disease by CT Angiography

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ClinicalTrials.gov Identifier: NCT02725671
Recruitment Status : Terminated (Poor enrollment due to insufficient study support.)
First Posted : April 1, 2016
Results First Posted : February 25, 2020
Last Update Posted : July 9, 2020
Sponsor:
Collaborator:
Enverdis Corp.
Information provided by (Responsible Party):
Johns Hopkins University

Brief Summary:
Cardiogoniometry is a technique to process and evaluate vectorcardiography from regular ECG acquisitions. Vectorcardiography has a long tradition in cardiology for providing comprehensive information on myocardial function and integrity. In recent years, computer assisted analysis has allowed automated interpretation of vectorcardiography with promising results in comparison to standard ECG for identifying patients with coronary heart disease. This study aims to investigate the utility of cardiogoniometry for noninvasively identifying patients who are at risk from coronary heart disease.

Condition or disease Intervention/treatment Phase
Coronary Heart Disease Coronary Artery Disease Ischemic Heart Disease Device: Explorer Not Applicable

Detailed Description:

Cardiogoniometry is a technique to process and evaluate vectorcardiography from regular ECG acquisitions. Vectorcardiography has a long tradition in cardiology for providing comprehensive information on myocardial function and integrity. Compared to standard electrocardiography, vectorcardiography has shown to be more sensitive to detect structural and ischemic heart disease. Unfortunately, the interpretation of vectorcardiography is complex which has hindered its widespread application. In recent years, computer assisted analysis has allowed automated interpretation of vectorcardiography with promising results in comparison to standard ECG for identifying patients with ischemic heart disease. However, the underlying mechanisms and threshold of altered cardiac vectors in the presence of coronary artery disease are not well understood. This research aims at exploring the relationship of computer assisted analysis of vectorcardiography with the presence, extent, severity, and location of coronary artery disease in comparison to standard ECG evaluation. Furthermore, the investigators intent to follow up enrolled patients for the occurrence of adverse cardiovascular events for correlation with test findings. These data will provide comprehensive information on the diagnostic performance of noninvasive, inexpensive evaluation of cardiac vector loops for identifying patients at risk from coronary artery disease. Specifically, the study aims to:

  1. Compare the diagnostic accuracy of cardiogoniometry with standard ECG for detecting coronary artery disease as assessed by CT angiography
  2. Investigate the relationship between abnormal cardiogoniometry findings and the extent/severity/location of coronary artery disease by CT angiography
  3. Compare the intermediate term prognosis of patients according to cardiogoniometry, standard ECG, and CT findings

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Study Type : Interventional  (Clinical Trial)
Actual Enrollment : 2 participants
Allocation: N/A
Intervention Model: Single Group Assignment
Masking: None (Open Label)
Primary Purpose: Diagnostic
Official Title: Cardiogoniometry for Detecting Coronary Artery Disease by CT Angiography
Study Start Date : April 2015
Actual Primary Completion Date : April 2019
Actual Study Completion Date : June 26, 2020

Resource links provided by the National Library of Medicine


Arm Intervention/treatment
Cardiogoniometry and ECG Assessment
The same patient will undergo both advanced ECG assessment using cardiogoniometry and standard ECG
Device: Explorer
ECG device which records comprehensive voltage potential data in the myocardium




Primary Outcome Measures :
  1. Accuracy of Identifying Patients With at Least One 50 Percent or Greater Coronary Artery Stenosis by CT Angiography [ Time Frame: 30 days from CGM analysis ]
    Area under curve (AUC) analysis is proposed to be used to determine the diagnostic accuracy of cardiogoniometry for detecting patients with coronary heart disease as defined by at least one 50% or greater stenosis on CT coronary angiography.


Secondary Outcome Measures :
  1. Accuracy of Identifying Patients With Any Coronary Atherosclerotic Disease by CT Angiography [ Time Frame: 30 days ]
    Area under the curve (AUC) analysis is proposed to be used to asses the diagnostic accuracy of CGM for identifying patients with any coronary atherosclerotic disease

  2. Incidence of Death at Follow up [ Time Frame: 5 years after enrollment ]
    Patient follow up data will be used to performance of CGM to identify patients who are at risk of suffering adverse cardiac events at follow up compared to coronary CT angiography using AUC analysis.

  3. Risk of Myocardial Infarction [ Time Frame: 5 years after enrollment ]
    Incidence of myocardial infarction at follow up

  4. Risk of Revascularization at Follow up [ Time Frame: 5 year after enrollment ]
    Incidence of revascularization at follow up

  5. Risk of Hospitalization [ Time Frame: 5 years after enrollment ]
    Incidence of hospitalization at follow up



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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

Inclusion Criteria:

  • Patients age 18 or older who are referred for elective cardiac CT examination for evaluation of coronary artery disease

Exclusion Criteria:

  • hemodynamic instability
  • history of anaphylactic contrast reaction
  • inability of following breath hold instructions

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02725671


Locations
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United States, Maryland
Johns Hopkins Hospital
Baltimore, Maryland, United States, 21287
Sponsors and Collaborators
Johns Hopkins University
Enverdis Corp.
Investigators
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Principal Investigator: Armin A Zadeh, MD PhD MPH Johns Hopkins University
  Study Documents (Full-Text)

Documents provided by Johns Hopkins University:
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Responsible Party: Johns Hopkins University
ClinicalTrials.gov Identifier: NCT02725671    
Other Study ID Numbers: IRB00033908
First Posted: April 1, 2016    Key Record Dates
Results First Posted: February 25, 2020
Last Update Posted: July 9, 2020
Last Verified: June 2020
Additional relevant MeSH terms:
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Coronary Artery Disease
Myocardial Ischemia
Coronary Disease
Heart Diseases
Cardiovascular Diseases
Arteriosclerosis
Arterial Occlusive Diseases
Vascular Diseases