Patient Trajectories Among Persons Hospitalized for COVID-19 : A Cohort Study

Area of Science:

• Infectious Diseases
• Public Health
• Clinical Medicine

Background:

• Risk factors for severe coronavirus disease 2019 (COVID-19) progression in U.S. patient cohorts remain underexplored.
• Identifying predictors of severe COVID-19 or death is essential for timely intervention.

Purpose of the Study:

• To identify factors present at hospital admission that predict severe COVID-19 disease or death.
• To develop a predictive model for in-hospital disease progression.

Main Methods:

• Retrospective cohort analysis of 832 COVID-19 admissions across five hospitals.
• Patient outcomes were categorized using the World Health Organization COVID-19 disease severity scale.
• Analysis included demographic and clinical variables, laboratory results, and vital signs.

Main Results:

• A significant proportion of patients admitted with mild to moderate COVID-19 progressed to severe disease or death within days.
• Factors including age, nursing home residence, comorbidities, obesity, respiratory symptoms, vital signs, and specific laboratory values (lymphocyte count, albumin, troponin, CRP) were associated with progression.
• A predictive model using admission data demonstrated strong performance (AUC 0.79-0.85) for forecasting in-hospital disease progression.

Conclusions:

• A combination of demographic and clinical factors at admission strongly predicts severe COVID-19 outcomes and early onset.
• The COVID-19 Inpatient Risk Calculator (CIRC) can inform clinical management and resource allocation decisions for hospitalized patients.