Non-invasive Biometric Monitoring in Nursing Homes to Fight COVID-19

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.

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Key information

Conditions

Covid19 COVID-19 Community-Acquired Respiratory Tract Infection Coronaviridae Infections Coronavirus Infections Infections Lung Diseases Nidovirales Infections Pneumonia Pneumonia, Viral RNA Virus Infections Respiratory Tract Diseases Respiratory Tract Infections Virus Diseases

Sex eligibility

All sexes

Study type

Observational

Primary location

Avalon Health & Rehabilitation Center

Pasco, Washington, 99301, United States

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

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.

Exclusion criteria

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-19.
Dementia

Treatment and study plan

Observational measurement of biometric data. No change to health care provided.

Device

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.

Primary outcomes

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

Sponsors and collaborators

Lead sponsor

Health Stream Analytics, LLC

Industry

Registry information

Official study title

Non-invasive Biometric Monitoring for the Prevention of COVID-19 Transmission and Deaths in Nursing Homes

Important dates

Study start: 2020
Primary completion: 2021
Study completion: 2021
First posted: Sep 16, 2020
Registry last updated: Jun 11, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Completed