Non-invasive Biometric Monitoring in Nursing Homes to Fight COVID-19
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|ClinicalTrials.gov Identifier: NCT04548895|
Recruitment Status : Not yet recruiting
First Posted : September 16, 2020
Last Update Posted : September 16, 2020
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.
|Condition or disease||Intervention/treatment|
|Covid19 Community-Acquired Respiratory Tract Infection||Device: Observational measurement of biometric data. No change to health care provided.|
- 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.
|Study Type :||Observational|
|Estimated Enrollment :||30 participants|
|Observational Model:||Ecologic or Community|
|Official Title:||Non-invasive Biometric Monitoring for the Prevention of COVID-19 Transmission and Deaths in Nursing Homes|
|Estimated Study Start Date :||September 2020|
|Estimated Primary Completion Date :||December 31, 2020|
|Estimated Study Completion Date :||February 26, 2021|
LTCF residents and involved health practitioners
The intervention will take place in nursing homes, assisted living facilities and long-term care facilities (LTCF) in the United States (henceforth collectively referred to as "LTCF").
Staff who work in the participating LTCF ≥ 20 hours/week and who have direct contact with the residents are also eligible to participate and to employ the biometric monitoring equipment in their private residences.
Device: Observational measurement of biometric data. No change to health care provided.
Emfit devices will be installed once after enrollment under each participant's mattress and left to record automatically without further intervention. The participants will wear their Biostrap wristbands consistently, ideally 24 hours a day, 7 days a week, for 2 months.
A virus panel will be upon enrollment (baseline) and then every two weeks (± 3 days, or on the closest convenient sampling day if the LTCF is testing all residents on the same day) for a maximum of 5 times during the two-month period. Using polymerase chain reaction or next generation sequencing, the virus panel will detect COVID-19 and 12 other common respiratory viruses that may cause similar symptoms and similar biometric signatures. These include influenza A and B, parainfluenza types 1 through 4, respiratory syncytial virus, non-COVID coronavirus, rhinovirus, adenovirus, bocavirus and metapneumovirus.
- Proportion of quality signals obtained out of all monitoring time for each device [ Time Frame: 8 weeks from first enrollment ]Feasibility assessment
- Predictive characteristics of the algorithm for respiratory tract infection [ Time Frame: 2 months ]Algorithm development, sensitivity, specificity, positive and negative predictive value at different lead times ahead of symptom onset
Biospecimen Retention: Samples With DNA
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04548895
|Contact: Martin G Frasch, MD, PhDfirstname.lastname@example.org|
|Study Chair:||Martin G Frasch||Health Stream Analytics, LLC|