跳至主要内容
临床试验/NCT05802563
NCT05802563Enrolling By Invitation不适用

Pattern Recognition in Heart Rate Variability Using Fitness Trackers in Cardiovascular Disease

HagaZiekenhuis1 个研究点 分布在 1 个国家目标入组 200 人开始时间: 2022年5月24日最近更新:
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:

  1. 50 with heart failure
  2. 50 with atrial fibrillation
  3. 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

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

申办方类型
Other
责任方
Principal Investigator
主要研究者

Ivo van der Bilt

Principal Investigator

HagaZiekenhuis

研究点 (1)

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