Hyperspectral Analysis of Sweat Metabolite Biometrics for Real-Time Detection of COVID-19
Background:
The COVID-19 pandemic has challenged the health systems worldwide. Many tools have been developed in response to the pandemic, but there is no current way to quickly screen multiple people for the disease. Research has shown that people with COVID-19 have higher levels of some proteins involved in the immune response and inflammation. These proteins can be detected in sweat using a special camera. Researchers want to see if analysis of sweat from fingerprints could be used to detect COVID-19 infection in people.
Objective:
To test a new technology to detect COVID-19 infection based on an analysis of sweat from fingerprints.
Eligibility:
Adults ages 18 and older who tested positive or negative for COVID-19 within the last 7 days.
Design:
Participants will visit the NIH Clinical Center for one day within 7 days from COVID-19 testing. The visit will last for 3 to 4 hours.
Participants who show symptoms for COVID-19 with a positive test will give blood samples to correlate with the sweat markers. About 1/2 tablespoon of blood will be drawn.
For sweat markers, 10 fingers will be imaged by a camera using a touchless system. This will be repeated 3 times. It will take about 15 minutes. Participants will use the device. They will get instructions and watch a short video on how to use the device.
Study Overview
Status
Status
Conditions
Conditions
Detailed Description
Background
The Coronavirus Disease 19 (COVID19) pandemic has challenged healthcare systems worldwide. Massive testing, contact tracing and social distancing proved to be the most effective tools to fight the pandemic prior to the development of vaccines.
Despite the effort to develop rapid diagnostic testing, we still don t have an available large population screening modality. Analysis of sweat metabolites from hyperspectral images of fingertips has the potential to be a valid clinic strategy to detect Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)infected individuals.
COVID19 has shown higher levels of inflammatory proteins like IL6, LDH, CRP, and d-dimer which have been implicated with severe COVID-19 induced pneumonitis and coagulopathy. These molecules can be detected as sweat metabolites and used as a biomarker for viral infection detection.
Objective
Identify a pattern classifier to distinguish between SARS-CoV-2 positive and SARS-CoV-2 negative human subjects by analysis of sweat metabolites from hyperspectral images of fingertips.
Eligibility
Individuals must all be >=18 years old
Must have standard of care molecular testing (either antigen or PCR) for SARS-CoV-2 within 7 days from study enrollment. Those individuals who tested positive will be enrolled in cohort 1 and those who tested negative will be enrolled in cohort 2
Study Design
This is an exploratory multisite study to evaluate the use of biometric analysis of sweat metabolites from hyperspectral images of fingertips to detect SARS-CoV-2 infection. Center for Cancer research (CCR), NCI will be the coordinating center.
All adult subjects that have available testing for SARS-CoV-2 completed within 7 days from the study enrollment are eligible for this study. The study will have two cohorts, cohort 1 (SARS-CoV-2 positive), and cohort 2 (SARS-CoV-2 negative). Fifty participants will be enrolled in each cohort to have hyperspectral imaging of the fingertips.
Every participant will have the right and left index fingers imaged by the camera with a touchless system. The imaging will be repeated three times. This imaging will take about 10 minutes.
The data obtained by the digital analysis will be compared to the result of the standard SARS-CoV-2 tests in use at the enrolling sites.
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Katherine O Lee-Wisdom, R.N.
- Phone Number: (240) 858-3525
- Email: katherine.lee-wisdom@nih.gov
Study Contact Backup
- Name: James L Gulley, M.D.
- Phone Number: (301) 480-7164
- Email: gulleyj@mail.nih.gov
Study Locations
-
-
Maryland
-
Bethesda, Maryland, United States, 20892
- National Institutes of Health Clinical Center
-
-
Virginia
-
Fairfax, Virginia, United States, 22031
- Inova Fairfax Medical Campus
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
- INCLUSION CRITERIA:
Eligible subjects must meet the following inclusion criteria:
- Age >=18 years.
Eligible for one of the following cohorts:
- Cohort 1: Participants who tested positive for SARS-CoV-2 via standard of care molecular testing within 7 days of enrollment. Either antigen or PCR testing is acceptable. Results from home tests are not accepted.
- Cohort 2: Participants must have a standard of care molecular testing negative for SARS-CoV-2 done within 7 days of enrollment. Either antigen or PCR testing is acceptable for enrollment. Results from home tests are not accepted.
- Ability of subject or Legally Authorized Representative (LAR) or Durable Power of Attorney (DPA) to understand and the willingness to sign a written informed consent document
EXCLUSION CRITERIA:
Subjects with the following characteristics will be excluded from the study:
-Participants who have received remdesivir and/or dexamethasone for longer than 48 hours prior to hyperspectral imaging for the treatment of COVID19. Participants who have received up to 48 hours of treatment will be eligible.
Study Plan
How is the study designed?
Design Details
- Observational Models: Cohort
- Time Perspectives: Prospective
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
|---|
|
Cohort 1/SARS-CoV-2 positive
Participants with molecular testing positive for SARS-CoV-2
|
|
Cohort 2/SARS-CoV-2 negative
Participants with molecular testing negative for SARS-CoV-2
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Hyperspectal Analysis
Time Frame: One day
|
Identify a pattern classifier to distinguish between SARS-CoV-2 positive (cohort 1) and SARS-CoV-2 negative (cohort 2) human subjects by hyperspectral analysis of sweat metabolites.
|
One day
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: James L Gulley, M.D., National Cancer Institute (NCI)
Publications and helpful links
Helpful Links
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 10000178
- 000178-C
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
IPD Sharing Time Frame
IPD Sharing Access Criteria
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- SAP
- ICF
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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