Non-invasive Biometric Monitoring for the Prevention of COVID-19 Transmission and Deaths in Nursing Homes
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 26
- 试验地点
- 1
- 主要终点
- Predictive characteristics of the algorithm for respiratory tract infection
研究概览
简要总结
Solving the problem of detecting asymptomatic carriers who can transmit infection is key to protecting vulnerable residents of nursing homes and assisted living facilities, to protecting frontline workers who care for them, and to facilitating return to work (including return of nurses and medical assistants).
The wearable biometric technology, if widely disseminated among vulnerable populations and the community-at-large, will help avoid the ravages of seasonal flu and other contagious illnesses, and the society will be better prepared for future waves of COVID-19 or other pandemics. Even if a vaccine is developed, due to immune senescence and immunocompromise, elderly people and those with chronic medical conditions may not be well protected by it. Continuous biomonitoring provides another layer of protection for them.
详细描述
- Building the algorithm for early, pre-symptomatic DETECTION OF RESPIRATORY VIRAL INFECTION and for predicting eventual DETERIORATION.
- Create an APP that AUTOMATES these algorithms and clearly REPORTS ACTIONABLE RESULTS to users, i.e., to medical professionals and citizens-at-large in near-real time. If alerted to a possible - and likely still asymptomatic - COVID-19 infection, they can self-isolate or be quarantined, get confirmatory COVID-19 testing done promptly, limit transmission to others, and stay safe knowing that if they are likely to deteriorate, the algorithm will alert the participants and their caregivers to the need to obtain medical attention promptly.
研究设计
- 研究类型
- Observational
- 观察模型
- Ecologic Or Community
- 时间视角
- Prospective
入排标准
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Residents and staff members of U.S. LTCFs where COVID-19 transmission is actively occurring. The LTCF medical director must agree to enroll the LTCF, and each participant must have the capacity to agree and sign consent.
排除标准
- •Current atrial fibrillation.
- •NB: Paroxysmal atrial fibrillation is permitted if the participant is in atrial fibrillation less than 50% of the day on most days.
- •Pacemaker in place.
- •Known active infection other than COVID-
结局指标
主要结局
Predictive characteristics of the algorithm for respiratory tract infection
时间窗: 2 months
Algorithm development, sensitivity, specificity, positive and negative predictive value at different lead times ahead of symptom onset
Proportion of quality signals obtained out of all monitoring time for each device
时间窗: 8 weeks from first enrollment
Feasibility assessment
次要结局
未报告次要终点