A PORTABLE MULTI-MODAL OPTICO-IMPEDANCE SYTEM FOR EARLY WARNING OF PROGRESSION IN STABLE COVID-19 PATIENTS
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 3R41EB029284-01S1
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Key facts
Disease
COVID-19Start & end year
20202022Known Financial Commitments (USD)
$155,282Funder
National Institutes of Health (NIH)Principal Investigator
Ryan Joseph HalterResearch Location
United States of AmericaLead Research Institution
Multivariate Systems IncResearch Priority Alignment
N/A
Research Category
Clinical characterisation and management
Research Subcategory
Disease pathogenesis
Special Interest Tags
Innovation
Study Type
Clinical
Clinical Trial Details
Not applicable
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Project Summary / Abstract:COVID-19, the clinical presentation associated with SARS-CoV-2 infection, has already profoundly impactedhealthcare systems globally. Of particular note, communities such as long-term care facilities, assisted livingcommunities, and prisons, are being devastated because of their high density of vulnerable individuals.Nursing home residents, which represent only 0.5% of the US population, account for 25% of COVID-19deaths. Early detection of COVID-19 progression in these patients is critical to improving outcomes of patientswho are in an early stable condition but at risk of deteriorating, but must be balanced with efficient use ofprimary care resources and adequate protection of healthcare workers. An early alert to progression with ahigh sensitivity and an acceptable rate of false-negatives would save patient lives, reduce exposure ofhealthcare workers, and would also facilitate resource-shifting in the face of a surge. The time, money andeffort saved by allowing medical resources to be applied more accurately is the essence of precision medicine.During our current STTR efforts, we have developed and evaluated an opto-impedance system capable ofintegrating and classifying optical, electrical impedance spectroscopy and tomography data to detect changefrom baseline signatures of early ongoing hemorrhage with high accuracy. This proposal will (1) scale up ourhardware inventory, (2) deploy on COVID-positive patients to collect continuous multiplex data and (3) retrain our algorithms using the data to detect associated deterioration due to progression of COVID symptoms. Thismultivariate approach that has already been demonstrated in other pre-shock models, has the potential toprovide critical diagnostic and prognostic feedback in high-risk individuals.