深度学习增强主动脉瓣狭窄检测 - DETECT-AS-Diagnostic 研究
The DETECT-AS Diagnostic Study will assess the performance of artificial intelligence (AI) risk predictions to detect aortic stenosis using results from portable electrocardiogram (ECG) and cardiac ultrasound devices.
研究概览
地位
条件
研究类型
注册 (估计的)
阶段
- 不适用
联系人和位置
学习地点
-
-
Connecticut
-
New Haven、Connecticut、美国、06519
- Yale New Haven Health System
-
-
New York
-
New York、New York、美国、10029
- Icahn School of Medicine at Mount Sinai
-
-
Texas
-
Houston、Texas、美国、77030
- The Methodist Hospital Research Institute
-
-
参与标准
资格标准
适合学习的年龄
接受健康志愿者
有资格学习的性别
描述
Inclusion Criteria:
- Age 70 years or older
- Attending a routine outpatient primary care clinic at one of the three enrollment sites
Exclusion Criteria:
- Opted out of research studies
- Non-English speaking
- Urgent or emergent visits, defined as a visit for an illness or injury that needs attention quickly or is life-threatening
- Any echocardiogram within 12 months of clinic visit
- Prior history of moderate or severe AS
- Prior history of aortic valve replacement or repair, including transcatheter and surgical AVR with either a bioprosthetic or mechanical valve
- Presence of implantable cardiac devices, including permanent cardiac pacer, implantable cardioverter-defibrillator, or left ventricular assist device
- Prior heart transplant
- History of dementia
- Documented life expectancy of <1 year or current participation in hospice services.
学习计划
研究是如何设计的？
设计细节
- 主要用途：诊断
- 分配：随机化
- 介入模型：并行分配
- 屏蔽：三倍
武器和干预
参与者组/臂 |
干预/治疗 |
|---|---|
|
实验性的：Intervention
The intervention arm will undergo sequential screening for aortic stenosis using portable 1-lead electrocardiograms (ECGs), followed by point-of-care ultrasound (POCUS), if indicated, by artificial intelligence (AI)-based risk algorithms. |
Portable 1-lead electrocardiogram (ECG) performed with the FDA-approved AliveCor KardiaMobile device. Point-of-care ultrasound performed with the FDA-approved VScan Air device. Artificial intelligence (AI) risk algorithm for aortic stenosis using a 1-lead electrocardiogram Artificial intelligence (AI) risk algorithm for aortic stenosis using cardiac ultrasound plax videos. |
|
假比较器：Control
The control arm will undergo a portable 1-lead electrocardiogram (ECG), with 10% randomly assigned to undergo point-of-care ultrasound (POCUS). |
Portable 1-lead electrocardiogram (ECG) performed with the FDA-approved AliveCor KardiaMobile device. Point-of-care ultrasound performed with the FDA-approved VScan Air device. |
研究衡量的是什么？
主要结果指标
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
|
Number of participants diagnosed with advanced aortic stenosis (AS) by transthoracic echocardiogram (TTE)
大体时间：Until 12 months from the baseline visit
|
The number of participants diagnosed with advanced AS by TTE at 12 months. Diagnosis of advanced AS is defined as diagnosis of moderate or severe AS as documented in the participant's electronic health record (EHR) at 12 months and adjudication of outcome via review of echocardiographic reports and videos performed by blinded members of the echocardiographic lab at the coordinating center. |
Until 12 months from the baseline visit
|
合作者和调查者
合作者
调查人员
- 首席研究员：Rohan Khera, MD, MS、Yale University
研究记录日期
研究主要日期
学习开始 (实际的)
初级完成 (估计的)
研究完成 (估计的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (实际的)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
与本研究相关的术语
其他研究编号
- 2000038634
- R01AG089981 (美国 NIH 拨款/合同)
计划个人参与者数据 (IPD)
计划共享个人参与者数据 (IPD)？
IPD 计划说明
A de-identified dataset will be made available following publication of primary results.
IPD 共享支持信息类型
- 研究方案
- 树液
- 国际碳纤维联合会
- 分析代码
药物和器械信息、研究文件
研究美国 FDA 监管的药品
研究美国 FDA 监管的设备产品
在美国制造并从美国出口的产品
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