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临床试验/NCT04637230
NCT04637230Unknown不适用

Prevention of Stroke and Sudden Cardiac Death by Recording of 1-Channel Electrocardiograms

A-Rhythmik GmbH1 个研究点 分布在 1 个国家目标入组 10,000 人开始时间: 2021年10月1日最近更新:
适应症

试验速览

阶段
不适用
入组人数
10,000
试验地点
1
主要终点
Diagnostic accuracy of AI

研究概览

简要总结

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.

详细描述

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.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 85 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Heart rhythm of interest present on ECG

排除标准

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

结局指标

主要结局

Diagnostic accuracy of AI

时间窗: 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

时间窗: Immediate

Assessment of presence ("Yes") or absence ("No") of QRS-complex fragmentation

ECG QTc interval

时间窗: Immediate

Calculation of heart rate corrected QT interval (QTc) via Bazett formula from measured QT interval

ECG T wave inversion

时间窗: Immediate

Assessment of presence ("Yes") or absence ("No") of T wave inversion

ECG R-R interval

时间窗: Immediate

30-sec mean and standard deviation of R-R intervals

ECG QRS-complex duration

时间窗: Immediate

Measurement of width/duration of QRS complex; distinction between "narrow" (\<=110ms) and "wide" (\>110ms)

次要结局

  • ECG P wave(Immediate)
  • ECG PQ interval(Immediate)
  • ECG QT interval(Immediate)

研究者

申办方类型
Other
责任方
Sponsor

研究点 (1)

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