Detection of COVID-19 Decompensation

NCT ID: NCT04575532

Last Updated: 2021-09-13

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

1000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-10-05

Study Completion Date

2021-09-09

Brief Summary

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In this study we will be monitoring for patient events (emergency department admission, hospital admission, admission to an observation unit, or death) and evaluating the feasibility and utility of using pinpointIQ in the management of patients with COVID-19. Vital sign (physiology data) is collected to build a Covid Decompensation Index and contribute data to a Covid Digital Hub supported by the National Institutes of Health.

Detailed Description

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This is a prospective, non-randomized, open-label, two-phase design. The primary focus for the study is data collection for index development. This will be done in two phases: the first phase allows for determination of predictor variables that establish the COVID-19 Decompensation Index (CDI) and the second phase establishes performance of the CDI. A participant is considered to have completed the study if he or she completes all phases of the study including the last day of monitoring (day 28).

Conditions

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Covid19

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Interventions

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Use of the pinpointIQ solution (physIQ, Inc.)

Patients are monitored for 28 days post COVID19 diagnosis or COVID19 post-hospitalization discharge using the pinpointIQ solution.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

Obtained signed and dated informed consent form Patient in the University of Illinois Health System Patient agrees to comply with all study procedures and availability for the duration of the study Male or female, aged \> 18 years of age Patient diagnosed with COVID-19 (positive SARS CoV2 test) Patient agrees to refrain from swimming or taking baths (any activity that submerges the biosensor in water for any period). Showering is okay.

Exclusion Criteria

Known allergic reactions to components of the hydrocolloid gel adhesives Subject has cognitive or physical limitations that, in the opinion of the investigator, limits the subject's ability to fully follow study procedures Cognitive ability, in the opinion of the investigator, that limits the patient's ability to use the biosensor and smartphone consistent with study requirements.

Does not speak or read English or Spanish
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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National Institute for Biomedical Imaging and Bioengineering (NIBIB)

NIH

Sponsor Role collaborator

National Cancer Institute (NCI)

NIH

Sponsor Role collaborator

University of Illinois at Chicago

OTHER

Sponsor Role collaborator

physIQ, Inc.

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Karen Larimer, PhD

Role: PRINCIPAL_INVESTIGATOR

physIQ, Inc.

Locations

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Rush University Medical Center

Chicago, Illinois, United States

Site Status

University of Illinois Hospital and Health Sciences System

Chicago, Illinois, United States

Site Status

NorthShore University HealthSystem

Evanston, Illinois, United States

Site Status

University of Texas Health

Houston, Texas, United States

Site Status

Countries

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United States

References

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Larimer K, Wegerich S, Splan J, Chestek D, Prendergast H, Vanden Hoek T. Personalized Analytics and a Wearable Biosensor Platform for Early Detection of COVID-19 Decompensation (DeCODe): Protocol for the Development of the COVID-19 Decompensation Index. JMIR Res Protoc. 2021 May 26;10(5):e27271. doi: 10.2196/27271.

Reference Type DERIVED
PMID: 33949966 (View on PubMed)

Other Identifiers

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75N91020C00040

Identifier Type: OTHER_GRANT

Identifier Source: secondary_id

CTP-004

Identifier Type: -

Identifier Source: org_study_id

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