NCT05865184招募中不适用
Feasibility of Home-based, Ambient Passive Sensor Technology to Provide Early Warning of Health Decompensation by Detecting Deviations in Activities of Daily Living (ADLs) of Elderly Subjects With Diagnosed Chronic Disease
适应症
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 100
- 试验地点
- 1
- 主要终点
- Precision of AI in passive sensor system
研究概览
简要总结
Sensorum Health (Sensorum) is conducting a pilot study to determine if Sensorum's proprietary passive sensor network can be used to identify signals of early health decompensation in subjects prior to a hospitalization for chronic disease exacerbation or other ambulatory care sensitive conditions. Successful early detection would provide a window of opportunity to intervene outside of the acute setting in future interventional studies.
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
- 65 Years 至 —（Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Aged 65 years or older
- •Able to consent
- •Documented history of diagnosis of chronic obstructive pulmonary disease (COPD) and/or congestive heart failure (CHF)
- •Currently admitted to JSUMC for observation or as an inpatient with any diagnosis ≥1 prior hospital utilization events with any diagnosis (inpatient admissions, facility observation stays, or ED visits) in the past 12 months
排除标准
- •Significant cardiac valvular disease
- •End-Stage Renal Disease (ESRD)
- •End-Stage CHF
- •End-Stage COPD
结局指标
主要结局
Precision of AI in passive sensor system
时间窗: 90 days
Evaluation of AI ability to precisely predict hospital utilization event
Recall of AI in passive sensor system
时间窗: 90 days
Evaluation of AI ability to prospectively detect hospital utilization event
次要结局
- Recall of sensor data review by trained nurses(90 days)
- Precision of sensor data review by trained nurses(90 days)
研究者
研究点 (1)
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