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Detection of COVID-19 Decompensation (DeCODe)

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ClinicalTrials.gov Identifier: NCT04575532
Recruitment Status : Completed
First Posted : October 5, 2020
Last Update Posted : September 13, 2021
National Institute for Biomedical Imaging and Bioengineering (NIBIB)
National Cancer Institute (NCI)
University of Illinois at Chicago
Information provided by (Responsible Party):
physIQ, Inc.

Tracking Information
First Submitted Date October 1, 2020
First Posted Date October 5, 2020
Last Update Posted Date September 13, 2021
Actual Study Start Date October 5, 2020
Actual Primary Completion Date September 9, 2021   (Final data collection date for primary outcome measure)
Current Primary Outcome Measures
 (submitted: October 1, 2020)
Development of Covid Decompensation Index [ Time Frame: 4 months ]
To collect sufficient data to identify a set of predictor variables that most accurately predict a COVID-19 decompensation event aimed at developing and validating a clinically useful COVID Decompensation Index (CDI).
Original Primary Outcome Measures Same as current
Change History
Current Secondary Outcome Measures
 (submitted: October 1, 2020)
Feasibility [ Time Frame: 4 months ]
To evaluate the feasibility of using the pinpointIQ solution as a tool for healthcare professionals to identify physiologic decompensation and manage the study populations based on physIQ validated rule sets and analytics.
Original Secondary Outcome Measures Same as current
Current Other Pre-specified Outcome Measures Not Provided
Original Other Pre-specified Outcome Measures Not Provided
Descriptive Information
Brief Title Detection of COVID-19 Decompensation
Official Title Personalized Analytics and Wearable Biosensor Platform for Early Detection of COVID-19 Decompensation
Brief Summary 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 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).
Study Type Observational
Study Design Observational Model: Cohort
Time Perspective: Prospective
Target Follow-Up Duration Not Provided
Biospecimen Not Provided
Sampling Method Non-Probability Sample
Study Population Participants will be adult patients in the University of Illinois Health System (UIH). Participants will be recruited from two pools of patients at UIH: 1) patients tested in the outpatient setting who have a positive result for SAR-Co-V2 (COVID-19) and 2) patients who were admitted to the hospital with a diagnosis of COVID-19 and subsequently discharged to home convalescence. This will be a convenience sample. Phase 1 will have a sample size of 400 and Phase 2 will have a sample size of 1,200.
Condition Covid19
Intervention Device: 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.
Study Groups/Cohorts Not Provided
Publications * 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.

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
Recruitment Information
Recruitment Status Completed
Actual Enrollment
 (submitted: September 9, 2021)
Original Estimated Enrollment
 (submitted: October 1, 2020)
Actual Study Completion Date September 9, 2021
Actual Primary Completion Date September 9, 2021   (Final data collection date for primary outcome measure)
Eligibility Criteria

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

Sexes Eligible for Study: All
Ages 18 Years and older   (Adult, Older Adult)
Accepts Healthy Volunteers No
Contacts Contact information is only displayed when the study is recruiting subjects
Listed Location Countries United States
Removed Location Countries  
Administrative Information
NCT Number NCT04575532
Other Study ID Numbers CTP-004
75N91020C00040 ( Other Grant/Funding Number: NIH/NBIB/NCI )
Has Data Monitoring Committee No
U.S. FDA-regulated Product
Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: Yes
Product Manufactured in and Exported from the U.S.: No
IPD Sharing Statement
Plan to Share IPD: Yes
Plan Description: This effort is part of a hub-and-spoke technology implementation model created by the NIH, in which each supported digital health solution (the spokes) will be required to share deidentified data and other digital assets it generates with an NIH-supported central data hub. The data hub will provide global researchers a single access point to deidentified data, algorithms, and other capabilities generated by the various digital health solutions. Standards that enhance interoperability will enable unambiguous linking of digital resources among the spokes of the hub. This will enable researchers, for example, to apply the CDI developed in this project's spoke to individuals' health data that was collected by other spokes.
Supporting Materials: Analytic Code
Time Frame: January 2021
Access Criteria: NIH is gate keeper of data access through the digital hub
Current Responsible Party physIQ, Inc.
Original Responsible Party Same as current
Current Study Sponsor physIQ, Inc.
Original Study Sponsor Same as current
  • National Institute for Biomedical Imaging and Bioengineering (NIBIB)
  • National Cancer Institute (NCI)
  • University of Illinois at Chicago
Principal Investigator: Karen Larimer, PhD physIQ, Inc.
PRS Account physIQ, Inc.
Verification Date May 2021