COVID-19, the clinical presentation associated with SARS-CoV-2 infection, has already profoundly impacted healthcare systems globally. Of particular note, communities such as long-term care facilities, assisted living communities, 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-19 deaths. Early detection of COVID-19 progression in these patients is critical to improving outcomes of patients who are in an early stable condition but at risk of deteriorating, but must be balanced with efficient use of primary care resources and adequate protection of healthcare workers. An early alert to progression with a high sensitivity and an acceptable rate of false-negatives would save patient lives, reduce exposure of healthcare workers, and would also facilitate resource-shifting in the face of a surge. The time, money and effort 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 of integrating and classifying optical, electrical impedance spectroscopy and tomography data to detect change from baseline signatures of early ongoing hemorrhage with high accuracy. This proposal will (1) scale up our hardware 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. This multivariate approach that has already been demonstrated in other pre-shock models, has the potential to provide critical diagnostic and prognostic feedback in high-risk individuals.

Public Health Relevance

Our current STTR aims to develop optico-impedance sensors capable of detecting hemorrhage and results in sixty pigs (hemorrhage model) and 11 human subjects (lower-body negative pressure model) suggest excellent ability to diagnose 2-3% total blood volume loss with our early prototype device. An early alert to progression of COVID-19 should be an easier target, since an increase in extra-vascular lung water (EVLW) is one of the earliest detectable changes and these changes are more easily detected by impedance tomography than small changes in blood volume. This supplement will enable us to deploy additional Mk 1 prototype devices in COVID-positive patients to learn and test the diagnostic potential of our device.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Small Business Technology Transfer (STTR) Grants - Phase I (R41)
Project #
3R41EB029284-01S1
Application #
10188939
Study Section
Program Officer
Lash, Tiffani Bailey
Project Start
2020-07-01
Project End
2022-01-31
Budget Start
2021-02-01
Budget End
2022-01-31
Support Year
1
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Multivariate Systems, Inc.
Department
Type
DUNS #
116976322
City
Hanover
State
NH
Country
United States
Zip Code
03755