MACE CDS Software Master Enrollment Protocol
试验速览
- 阶段
- 不适用
- 状态
- 撤回
- 入组人数
- 5,515
- 试验地点
- 3
- 主要终点
- Performance Characteristics NPV (Negative Predictive Value), Specificity and Sensitivity
研究概览
简要总结
This protocol will collect real world EHR data to support the product development life cycle activities associated with developing the Major Adverse Cardiac Events (MACE) Clinical Decision Support (CDS) software.
The data will also be utilized in subsequent clinical validation to support an FDA application and/or applications to other regulatory agencies as needed.
详细描述
The primary objective is to develop a machine learning tool which predicts risk of 30-day MACE (major adverse cardiac event) risk stratification among patients visiting ED with suspicion of ACS (Acute Coronary Syndrome).
The data will also be utilized in subsequent clinical validation. In addition to retrospective Electronic Health Record (EHR) data, Health Information Exchange (HIE) data and patient reported outcomes will be collected to capture 30-day MACE outcomes, as applicable.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 23 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •All genders, races, ethnicities
排除标准
- •≤ 18 years old presenting to the ED and for clinical validation only, adults < 22 years old
结局指标
主要结局
Performance Characteristics NPV (Negative Predictive Value), Specificity and Sensitivity
时间窗: Within 30-days from the Emergency Department Visit with suspicion of ACS (Acute Coronary Syndrome)
Clinical performance of MACE (Major Adverse Cardiac Events) CDS (Clinical Decision Support) tool to identify a patient's risk of for having a MACE (Major Adverse Cardiac Events) within 30 days, with both a single High-Sensitive Troponin and a second High-Sensitive Troponin (if applicable).
次要结局
未报告次要终点