NCT05118009已完成不适用
Artificial Intelligence Based Rapid Identification of ST-elevation Myocardial Infarction Using Electrocardiogram (ARISE)
National Defense Medical Center, Taiwan2 个研究点 分布在 1 个国家目标入组 43,176 人开始时间: 2022年5月1日最近更新:
适应症
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 43,176
- 试验地点
- 2
- 主要终点
- E2C (ECG to coronary angiography) time
研究概览
简要总结
This is a randomized controlled trial (RCT) to test a novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based supporting tool for improving the diagnosis and management of ST-elevation myocardial infarction.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Screening
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients in emergency department or inpatient department.
- •Patients recieved at least 1 ECG examination.
排除标准
- •The patients recieved ECG at the period of inactive AI-ECG system.
结局指标
主要结局
E2C (ECG to coronary angiography) time
时间窗: Within 6 hours
Time from ECG to activation of coronary angiography for STEMI patients.
次要结局
- Highest concentration of high-sensitivity cardiac troponin I(Within 3 days)
- D2C (Door to coronary angiography) time(Within 6 hours)
- Ejection fractrion(Within 3 days)
- Highest concentration of creatine kinase(Within 3 days)
- Length of hospitalization(Within 28 days)
- Number of CAG event(Within 6 hours)
- D2B (Door to Balloon Time) time(Within 6 hours)
- E2B (ECG to primary percutaneous coronary intervention) time(Within 6 hours)
研究者
Chin Lin
Associate Professor
National Defense Medical Center, Taiwan
研究点 (2)
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