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3D ECG for Detection of Cardiomyopathy
3D ECG for Detection of Cardiomyopathy in Heart Failure
Sponsors |
Lead Sponsor: University Hospital, Essen |
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Source | University Hospital, Essen |
Brief Summary | There is existing data in the literature that suggests an additional predictive value of three dimensional ECG with respect to the presence of electrical abnormalities and for an existing cardiac disease. Especially regarding patients who suffered from a myocardial infarction in the past (post MI patients), evidence has been provided for a potential association of 3D repolarisation abnormalities and incidence of sudden cardiac death (SCD). In addition, there is some vague evidence of so called 3D ECG and prediction of coronary artery disease. This 3D ECG device is using the technology of 3D ECG vector loops and is assessing the variability of these ECG vector loops in the 3-dimensional space. Based on these data, the parameters of 3D ECG are suggested to carry certain value to predict or to identify individuals already suffering from a cardiac disease or being at risk experiencing a cardiac event in the future. In this context we performed a preliminary study with 3D-ECG device in healthy volunteers evaluating the robustness of this method with respect to reproducibility, intra- and intra-observer variability which could be confirmed. We thus postulate that the 3D ECG technology might bear the potential to serve as a sufficient screening method for diagnosing cardiomyopathy in patients with an unknown heart failure etiology. |
Overall Status | Recruiting | ||||
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Start Date | 2021-03-14 | ||||
Completion Date | 2021-10-14 | ||||
Primary Completion Date | 2021-09-14 | ||||
Study Type | Observational | ||||
Primary Outcome |
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Enrollment | 175 |
Condition | |
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Intervention |
Intervention Type: Diagnostic Test Intervention Name: 3D-ECG Description: Patient recieves 3D-ECG Assessement Arm Group Label: Patient recieving 3D-ECG-Evaluation |
Eligibility |
Sampling Method: Probability Sample
Criteria:
Inclusion Criteria: - Age >18 Years - Established diagnosis heart failure and suggested cardiomyopathy Exclusion Criteria: - Patients unable to sign informed consent - Pacemaker-stimulated ECG Gender: All Minimum Age: 18 Years Maximum Age: N/A Healthy Volunteers: No |
Overall Official |
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Overall Contact |
Last Name: Reza Wakili, Prof. Phone: 00492017234802 Email: reza.wakili@uk-essen.de |
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Location |
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Location Countries |
Germany |
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Verification Date |
2021-04-01 |
Responsible Party |
Type: Sponsor |
Has Expanded Access | No |
Condition Browse | |
Arm Group |
Label: Patient recieving 3D-ECG-Evaluation |
Patient Data | No |
Study Design Info |
Observational Model: Cohort Time Perspective: Prospective |
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