Coronary Artery Disease, Coronary Heart Disease, Ischemic Heart Disease
Conditions
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.
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
Interventions
DEVICEExplorer
ECG device which records comprehensive voltage potential data in the myocardium
Sponsors
Enverdis Corp.
Johns Hopkins University
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Accuracy of Identifying Patients With at Least One 50 Percent or Greater Coronary Artery Stenosis by CT Angiography | 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
| Measure | Time frame | Description |
|---|---|---|
| Risk of Revascularization at Follow up | 5 year after enrollment | Incidence of revascularization at follow up |
| Risk of Hospitalization | 5 years after enrollment | Incidence of hospitalization at follow up |
| Accuracy of Identifying Patients With Any Coronary Atherosclerotic Disease by CT Angiography | 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 |
| Incidence of Death at Follow up | 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. |
| Risk of Myocardial Infarction | 5 years after enrollment | Incidence of myocardial infarction at follow up |
Countries
United States
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| Study Group Single study group. All patients are planned to undergo both tests, CGM and CT angiography. | 2 |
| Total | 2 |
Withdrawals & dropouts
| Period | Reason | FG000 |
|---|---|---|
| Overall Study | Lost to Follow-up | 1 |
Baseline characteristics
| Characteristic | Study Group |
|---|---|
| Age, Categorical <=18 years | 0 Participants |
| Age, Categorical >=65 years | 1 Participants |
| Age, Categorical Between 18 and 65 years | 1 Participants |
| Age, Continuous | 56 years |
| Cardiac Risk Factors | 2 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 0 Participants |
| Race (NIH/OMB) Asian | 0 Participants |
| Race (NIH/OMB) Black or African American | 0 Participants |
| Race (NIH/OMB) More than one race | 0 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 0 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 0 Participants |
| Race (NIH/OMB) White | 2 Participants |
| Region of Enrollment United States | 2 Participants |
| Sex: Female, Male Female | 0 Participants |
| Sex: Female, Male Male | 2 Participants |
Adverse events
| Event type | EG000 affected / at risk |
|---|---|
| deaths Total, all-cause mortality | 0 / 2 |
| other Total, other adverse events | 0 / 2 |
| serious Total, serious adverse events | 0 / 2 |
Outcome results
Primary
Accuracy of Identifying Patients With at Least One 50 Percent or Greater Coronary Artery Stenosis by CT Angiography
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.
Time frame: 30 days from CGM analysis
Population: Minimum data needed for this measure was not collected and therefore could not be calculated.
Secondary
Accuracy of Identifying Patients With Any Coronary Atherosclerotic Disease by CT Angiography
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
Time frame: 30 days
Population: Insufficient enrollment for analysis for this outcome measure
Secondary
Incidence of Death at Follow up
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.
Time frame: 5 years after enrollment
Population: Insufficient enrollment for analysis of this outcome measure
Secondary
Risk of Hospitalization
Incidence of hospitalization at follow up
Time frame: 5 years after enrollment
Population: Insufficient enrollment for analysis of this outcome measure
Secondary
Risk of Myocardial Infarction
Incidence of myocardial infarction at follow up
Time frame: 5 years after enrollment
Population: Insufficient enrollment for analysis of this outcome measure
Secondary
Risk of Revascularization at Follow up
Incidence of revascularization at follow up
Time frame: 5 year after enrollment
Population: Insufficient enrollment for analysis of this outcome measure