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COVID-19 Outcome Prediction Algorithm (COPA)

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ClinicalTrials.gov Identifier: NCT05471011
Recruitment Status : Recruiting
First Posted : July 22, 2022
Last Update Posted : September 29, 2022
Sponsor:
Collaborators:
Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
Olive View-UCLA Education & Research Institute
VA Greater Los Angeles Healthcare System
Michael E. DeBakey VA Medical Center
Atlanta VA Medical Center
Bronx VA Medical Center
Information provided by (Responsible Party):
Mario C. Deng, University of California, Los Angeles

Brief Summary:
Severe acute respiratory syndrome coronavirus 2-mediated coronavirus disease (COVID-19) is an evolutionarily unprecedented natural experiment that causes major changes to the host immune system. We propose to develop a test that accurately predicts short- and long-term (within one-year) outcomes in hospitalized COVID-19 patients broadly reflecting US demographics who are at increased risk of adverse outcomes from COVID-19 using both clinical and molecular data. We will enroll patients from a hospitalized civilian population in one of the country's largest metropolitan areas and a representative National Veteran's population.

Condition or disease Intervention/treatment
COVID-19 Post Acute Sequelae of COVID-19 Long COVID Organ Dysfunction Syndrome, Multiple Frailty Syndrome Other: Blood and nasal swab sampling

Detailed Description:
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-mediated coronavirus disease (COVID-19) is an evolutionarily unprecedented natural experiment that causes major changes to the host immune system. Several high risk COVID-19 populations have been identified. Older adults, males, persons of color, and those with certain underlying health conditions (e.g., diabetes mellitus, obesity, etc.) are at higher risk for severe disease from COVID-19. While it is too soon to fully understand the impact of COVID-19 on overall health and well-being, there are already several reports of significant sequelae, which appear to correlate with disease severity. There is a clear and urgent need to develop prediction tests for adverse short- and long-term outcomes, especially for high-risk COVID-19 populations. We hypothesize that complementary multi-dimensional information gathered near the time of symptom onset can be used to predict new onset or worsening frailty, organ dysfunction and death within one year after COVID-19 onset. A single parameter provides limited information and is incapable of adequately characterizing the complex biological responses in symptomatic COVID-19 to predict outcome. Since they were designed for other illnesses, it is unlikely that existing clinical tools, such as respiratory, cardiovascular, and other organ function assessment scores, will precisely assess the long-term prognosis of this novel disease. Our extensive experience in biomarker development suggests that integrating molecular and clinical data increases prediction accuracy of long-term outcomes. We have chosen to test our hypothesis in a population reflecting US-demographics that is at increased risk of adverse outcomes from COVID-19. We will enroll patients, broadly reflecting US demographics, from a hospitalized civilian population in one of the country's largest metropolitan areas and a representative National Veteran's population. We anticipate that a prediction test that performs well in this hospitalized patient group will: help guide triaging and treatment decisions and, therefore, reduce morbidity and mortality rates, enhance patient quality of life, and improve healthcare cost-effectiveness. More accurate prognostic information will also assist clinicians in framing goals of care discussions in situations of likely futility and assist patients and families in this decision-making process. Finally, it will provide a logical means for allocating resources in short supply, such as ventilators or therapeutics with limited availability.

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Study Type : Observational
Estimated Enrollment : 600 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Multi-Dimensional Outcome Prediction Algorithm for Hospitalized COVID-19 Patients
Actual Study Start Date : September 15, 2022
Estimated Primary Completion Date : March 2026
Estimated Study Completion Date : April 2026


Group/Cohort Intervention/treatment
civilian Other: Blood and nasal swab sampling
Blood and nasal swab sampling

Veteran Other: Blood and nasal swab sampling
Blood and nasal swab sampling




Primary Outcome Measures :
  1. New onset or worsening frailty, single organ dysfunction, multi-organ dysfunction, and death within one year [ Time Frame: From hospital admission to one year ]
    The primary outcome clinical composite endpoints that include new onset or worsening frailty, single organ dysfunction, multi organ dysfunction, and death within one year will include a follow-up period of time of at least 52 weeks after initial enrollment encounter. The assessment of time to event (outcome events will include various frailty measurement tools including short physical performance battery, laboratory test-based organ function assessment measures, and survival status as per publicly-accessible databases) will consist of calculating the time difference between first outcome event and baseline encounter date.


Secondary Outcome Measures :
  1. New onset or worsening frailty, single organ dysfunction, multi-organ dysfunction, and death at time of discharge [ Time Frame: From hospital admission to time of discharge ]
    The secondary outcome clinical composite endpoints that include new onset or worsening frailty, single organ dysfunction, multi organ dysfunction, and death within the time from initial encounter to the time of discharge will include a follow-up period consisting of the time from initial enrollment encounter to the time of discharge. The assessment of time to event (outcome events will include various frailty measurement tools including short physical performance battery, laboratory test-based organ function assessment measures, and survival status as per publicly-accessible databases) will consist of calculating the time difference between first outcome event and baseline encounter date.


Biospecimen Retention:   Samples With DNA
Peripheral blood and nasal swab


Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Symptomatic COVID-19 infected civilians and symptomatic COVID-19 infected veterans
Criteria

Inclusion Criteria:

  • Symptomatic COVID-19 infection with hospital admission
  • Age 18 and above
  • Informed consent

Exclusion Criteria:

  • Absence of symptomatic COVID-19 infection with hospital admission
  • Age 17 or below
  • No informed consent

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT05471011


Contacts
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Contact: Mario C Deng, MD 3107532759 mdeng@mednet.ucla.edu
Contact: David Beenhouwer, MD 3104783711 dbeenhou@g.ucla.edu

Locations
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United States, California
VA Greater Los Angeles Healthcare System Recruiting
Los Angeles, California, United States, 90073
Contact: David Beenhouwer, MD    310-268-3936    dbeenhou@ucla.edu   
Ronald Reagan UCLA Medical Center Recruiting
Los Angeles, California, United States, 90095
Contact: Mario C Deng, MD    310-753-2759    mdeng@mednet.ucla.edu   
Contact: Irina Silacheva, BS    3109105445    isilacheva@ucla.edu   
Olive View-UCLA Education & Research Institute Recruiting
Sylmar, California, United States, 91342
Contact: Glenn Mathisen, MD    747-210-3205    gmathisen@dhs.lacounty.gov   
Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center Recruiting
Torrance, California, United States, 90502
Contact: Tim Hatlen, MD    424-201-3000 ext 7319    timothy.hatlen@lundquist.org   
United States, Georgia
Atlanta VA Medical Center Active, not recruiting
Decatur, Georgia, United States, 30033
United States, New York
Bronx VA Medical Center Active, not recruiting
Bronx, New York, United States, 10468
United States, Texas
Michael E. DeBakey VA Medical Center Active, not recruiting
Houston, Texas, United States, 77030
Sponsors and Collaborators
University of California, Los Angeles
Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
Olive View-UCLA Education & Research Institute
VA Greater Los Angeles Healthcare System
Michael E. DeBakey VA Medical Center
Atlanta VA Medical Center
Bronx VA Medical Center
  Study Documents (Full-Text)

Documents provided by Mario C. Deng, University of California, Los Angeles:
Study Protocol  [PDF] November 2, 2020

Publications:
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Responsible Party: Mario C. Deng, Professor of Medicine, University of California, Los Angeles
ClinicalTrials.gov Identifier: NCT05471011    
Other Study ID Numbers: 1R01AI159946-01A1 ( U.S. NIH Grant/Contract )
First Posted: July 22, 2022    Key Record Dates
Last Update Posted: September 29, 2022
Last Verified: September 2022
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: Yes
Plan Description: After our data is cleaned, quality checked, and analyzed, we will make the data available to the general research community. Data collected in this proposal will be submitted to the appropriate public databases (e.g. Gene Expression Omnibus), along with complete documentation to enable efficient use of the data by the general research community. Cumulative datasets will be submitted on a regular basis in a timely manner. All data made available for public use will be de-identified data, i.e., stripped of private, protected health information that could be used to deduce the identity of individual subjects, in compliance with the HIPPA Privacy Rule. The study will be registered in the database of Genotypes and Phenotypes and the following data and information will be shared through the Sequence Read Archive and Gene Expression Omnibus.
Supporting Materials: Study Protocol
Statistical Analysis Plan (SAP)
Informed Consent Form (ICF)
Clinical Study Report (CSR)
Analytic Code
Time Frame: The data will be available following the completion of the study and will be available indefinitely.
Access Criteria: COPA Study website to be determined

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Mario C. Deng, University of California, Los Angeles:
outcome prediction
systems biology
multiomics
algorithm
veterans
high-risk populations
Additional relevant MeSH terms:
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COVID-19
Syndrome
Frailty
Multiple Organ Failure
Disease
Pathologic Processes
Respiratory Tract Infections
Infections
Pneumonia, Viral
Pneumonia
Virus Diseases
Coronavirus Infections
Coronaviridae Infections
Nidovirales Infections
RNA Virus Infections
Lung Diseases
Respiratory Tract Diseases
Shock