Artificial Intelligence System for Early Warning of Adverse Events in Acute Myocardial Infarction
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 1,400
- 试验地点
- 1
- 主要终点
- MACCE
研究概览
简要总结
The goal of this observational study is to learn about the effectiveness of an artificial intelligence-based early warning system for predicting adverse events in patients with acute myocardial infarction (AMI). The main question it aims to answer is:
Does an AI-based early warning system improve the assessment and prediction of adverse events across the full course of AMI care (from prevention to diagnosis, treatment, and rehabilitation)?
Participants who are receiving routine medical care for AMI in tertiary hospitals will have their multimodal medical data (clinical records, diagnostic tests, imaging, treatment pathways) collected and analyzed. Data will be integrated using innovative cross-modal representation methods and predictive models. The study will follow patients during their hospital stay and subsequent clinical follow-up to evaluate the feasibility, accuracy, and clinical value of the AI-based early warning system.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Other
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
- •Hospitalized patients who meet the diagnostic criteria for acute myocardial infarction.
- •Patients who agree to participate and sign the informed consent form.
排除标准
- •Patients with terminal malignant tumors and an expected survival time of less than 3 months.
- •Patients with complete disability and inability to communicate.
- •Patients unable to comply with follow-up.
结局指标
主要结局
MACCE
时间窗: 1-3 years
Cardiac death All-cause mortality Malignant arrhythmia Non-fatal recurrent myocardial infarction Non-fatal stroke Unplanned repeat revascularization Rehospitalization for heart failure
次要结局
未报告次要终点
研究者
Hui Chen
PHD
Beijing Friendship Hospital