Clinical trial NCT04637230: Prevention of Stroke and Sudden Cardiac Death by Recording of 1-Channel Electrocardiograms
Official title: Prevention of Stroke and Sudden Cardiac Death by Recording of 1-Channel Electrocardiograms
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Sinus Rhythm
Atrial Fibrillation
Atrial Premature Complexes
Ventricular Premature Complexes
Ventricular Tachycardia, Nonsustained
Keywords: Automated ECG diagnosis
Lead sponsor: Lanserhof
Sponsor class: OTHER
First posted: 2020-11-19
Enrollment: 10000
Sex: ALL
Minimum age (years): 18
Maximum age (years): 85
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Patients from tertiary care centers

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.

Eligibility criteria: Inclusion Criteria:

* Heart rhythm of interest present on ECG

Exclusion Criteria:

* Patient incapable of or not willing to sign informed consent form

Primary outcomes:
measure: Diagnostic accuracy of AI
timeFrame: 1 year
measure: ECG R-R interval
timeFrame: Immediate
measure: ECG QRS-complex duration
timeFrame: Immediate
measure: ECG QRS-complex fragmentation
timeFrame: Immediate
measure: ECG QTc interval
timeFrame: Immediate
measure: ECG T wave inversion
timeFrame: Immediate
Secondary outcomes:
measure: ECG P wave
timeFrame: Immediate
measure: ECG PQ interval
timeFrame: Immediate
measure: ECG QT interval
timeFrame: Immediate
Other outcomes:
Locations:
city: Lübeck
country: Germany
facility: Universitäres Herzzentrum, Lübeck, Germany
Study officials:
affiliation: Universitäres Herzzentrum, Lübeck, Germany
name: Karl-Heinz Kuck, MD
role: PRINCIPAL_INVESTIGATOR
References: