COVID-19 Outcome Prediction Algorithm

COVID-19 Clinical Trial

— COPA  

Official title:

Multi-Dimensional Outcome Prediction Algorithm for Hospitalized COVID-19 Patients

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05471011
• Other study ID #: 1R01AI159946-01A1
• Status: Recruiting
• Start date: August 8, 2022
• Est. completion date: May 31, 2026

Study information

• Verified date: May 2023
• Source: University of California, Los Angeles
• Contact: Mario C Deng, MD
• Phone: 3107532759
• Email: mdeng[@]mednet.ucla.edu
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 600
• Est. completion date: May 31, 2026
• Est. primary completion date: April 30, 2026
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

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

Related Conditions & MeSH terms

• COVID-19
• Frailty
• Frailty Syndrome
• Long COVID
• Multiple Organ Failure
• Organ Dysfunction Syndrome, Multiple
• Syndrome

Intervention

Other:
• Blood and nasal swab sampling
Blood and nasal swab sampling

Locations

Country	Name	City	State
United States	Bronx VA Medical Center	Bronx	New York
United States	Atlanta VA Medical Center	Decatur	Georgia
United States	Michael E. DeBakey VA Medical Center	Houston	Texas
United States	Ronald Reagan UCLA Medical Center	Los Angeles	California
United States	VA Greater Los Angeles Healthcare System	Los Angeles	California
United States	Olive View-UCLA Education & Research Institute	Sylmar	California
United States	Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center	Torrance	California

Sponsors (7)

Lead Sponsor	Collaborator
University of California, Los Angeles	Atlanta VA Medical Center, Bronx VA Medical Center, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Michael E. DeBakey VA Medical Center, Olive View-UCLA Education & Research Institute, VA Greater Los Angeles Healthcare System

Country where clinical trial is conducted

United States, 

References & Publications (1)

Deng MC. Multi-dimensional COVID-19 short- and long-term outcome prediction algorithm. Expert Rev Precis Med Drug Dev. 2020;5(4):239-242. doi: 10.1080/23808993.2020.1785286. Epub 2020 Jun 24. No abstract available. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	New onset or worsening frailty, single organ dysfunction, multi-organ dysfunction, and death within 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.	From hospital admission to one year
Secondary	New onset or worsening frailty, single organ dysfunction, multi-organ dysfunction, and death at 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.	From hospital admission to time of discharge