NCT05802563Enrolling By Invitation不适用
Pattern Recognition in Heart Rate Variability Using Fitness Trackers in Cardiovascular Disease
适应症
试验速览
- 阶段
- 不适用
- 状态
- Enrolling By Invitation
- 入组人数
- 200
- 试验地点
- 1
- 主要终点
- Cardiovascular disease detection with an AI algorithm
研究概览
简要总结
The goal of this observational cohort study is to investigate the potential of fitness trackers in combination with machine learning algorithms to identify cardiovascular disease specific patterns.
Two hundred participants will be enrolled:
- 50 with heart failure
- 50 with atrial fibrillation
- 100 (healthy) individuals without the former two conditions
All participants are given a Fitbit device and monitored for three months. Researchers will compare differences in heart rate variability patterns between the groups and devise a machine learning algorithm to detect these patterns automatically.
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
- 是
入选标准
- •systolic heart failure (LVEF < 35%)
- •Atrial fibrillation without heart failure
- •Individuals without cardiovascular disease
排除标准
- •> 85 years old
- •Recent pulmonary venous antrum isolation procedure (<1 year)
- •(end stage) kidney failure
- •(end stage) liver failure
- •Study participants with known systemic active inflammatory disease
- •Study participants with impaired mental state
- •Inability to use a fitness tracker or mobile phone
- •Impaired cognition and inability to understand the study protocol
结局指标
主要结局
Cardiovascular disease detection with an AI algorithm
时间窗: Three months
adequate sensitivity/specificity in an algorithm to detect atrial fibrillation and heart failure
次要结局
- Detection of absence of cardiovascular disease(Three months)
研究者
Ivo van der Bilt
Principal Investigator
HagaZiekenhuis
研究点 (1)
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