Prevention of Stroke and Sudden Cardiac Death by Recording of 1-Channel Electrocardiograms
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Sinus Rhythm
- Sponsor
- A-Rhythmik GmbH
- Enrollment
- 10000
- Locations
- 1
- Primary Endpoint
- Diagnostic accuracy of AI
- Last Updated
- 4 years ago
Overview
Brief Summary
Single-channel electrocardiograms (lead I of 12-lead surface ECG; 30 seconds) will be collected from subjects/patients at 11 clinical centers in Germany to train an Artificial Intelligence in the automatic diagnosis of regular and irregular heart rhythms. Heart rhythms of interest are normal sinus rhythm (SR), atrial fibrillation (AF), atrial premature beats (APBs), ventricular premature beats (VPBs), and nonsustained ventricular tachycardia (VT). Per diagnosis, 20,000 ECGs are required, for a total of 100,000 ECGs to be obtained from approximately 10,000 subjects/patients.
Detailed Description
In phase 1 of a research project titled 'Prevention of stroke and sudden cardiac death by Recording of 1-Channel Electrocardiograms' (PRICE), a total of 100,000 30-sec single-channel ECGs (lead I of 12-lead surface ECG) will be collected from approximately 10,000 subjects/patients at 11 participating clinical centers in Germany. Relevant baseline clinical patient characteristics will also be recorded. The ECGs, diagnosed by an experienced electrophysiologist (diagnostic gold standard), will be fed into an Artificial Intelligence (AI) for the automatic detection of normal sinus rhythm (SR), atrial fibrillation (AF), atrial premature beats (APBs), ventricular premature beats (VPBs), and nonsustained ventricular tachycardia (VT). It is expected that the overall diagnostic accuracy of the AI against an experienced electrophysiologist will be on the order of 95%. In PRICE phase 2, ECG diagnosis by the AI will be compared with the diagnosis by 3 general cardiologists of the same ECGs. It is expected that the AI will surpass the general cardiologists in terms of diagnostic accuracy. The final clinical phase of the PRICE project will comprise a randomized controlled community trial of risk patients to establish the superiority in stroke prevention of AI detection of AF on smart-watch ECGs vs. no AF detection.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Heart rhythm of interest present on ECG
Exclusion Criteria
- •Patient incapable of or not willing to sign informed consent form
Outcomes
Primary Outcomes
Diagnostic accuracy of AI
Time Frame: 1 year
Overall diagnostic accuracy of the AI in the diagnosis of normal SR, AF, APBs, VPBs, and nonsustained VT (gold standard: diagnosis by experienced electrophysiologist)
ECG QRS-complex fragmentation
Time Frame: Immediate
Assessment of presence ("Yes") or absence ("No") of QRS-complex fragmentation
ECG QTc interval
Time Frame: Immediate
Calculation of heart rate corrected QT interval (QTc) via Bazett formula from measured QT interval
ECG T wave inversion
Time Frame: Immediate
Assessment of presence ("Yes") or absence ("No") of T wave inversion
ECG R-R interval
Time Frame: Immediate
30-sec mean and standard deviation of R-R intervals
ECG QRS-complex duration
Time Frame: Immediate
Measurement of width/duration of QRS complex; distinction between "narrow" (\<=110ms) and "wide" (\>110ms)
Secondary Outcomes
- ECG P wave(Immediate)
- ECG PQ interval(Immediate)
- ECG QT interval(Immediate)