Assessment and Modeling of COVID-19 Outcomes in a Longitudinal Cohort of Hospitalized Adults

Abstract

ABSTRACTBackgroundWhile several demographic and clinical correlates of Coronavirus Disease 2019 (COVID-19) outcome have been identified, they remain imprecise tools for clinical management of disease. Furthermore, there are limited data on how these factors are associated with virological and immunological parameters over time.Methods and FindingsNasopharyngeal swabs and blood samples were longitudinally collected from a cohort of 58 hospitalized adults with COVID-19 in Chicago, Illinois between March 27 and June 9, 2020. Samples were assessed for SARS-CoV-2 viral load, viral genotype, viral diversity, and antibody titer. Demographic and clinical information, including patient blood tests and several composite measures of disease severity, were extracted from electronic health records. All parameters were assessed for association with three patient outcome groups: discharge without intensive care unit (ICU) admission (n = 23), discharge with ICU admission (n = 29), and COVID-19 related death (n = 6). Higher age, male sex, and higher body mass index (BMI) were significantly associated with ICU admission. At hospital admission, higher 4C Mortality scores and lactate dehydrogenase (LDH) levels were likewise associated with ICU admission. Longitudinal trends in Deterioration Index (DI) score, Modified Early Warning Score (MEWS), and serum neutrophil count were also associated with ICU admission, though only the retrospectively calculated median DI score was predictive of death. While viral load and genotype were not significantly associated with outcome in this study, viral load did correlate positively with C-reactive protein levels and negatively with D-dimer, lymphocyte count, and antibody titer. Intra-host viral genetic diversity resulted in changes in viral genotype in some participants over time, though intra-host evolution was not associated with outcome. A stepwise-generated multivariable model including BMI, lymphocyte count at admission, and neutrophil count at admission was sufficient to predict outcome with a 0.82 accuracy rate in this cohort.ConclusionsThese studies suggest that COVID-19 disease severity and poor outcomes among hospitalized patients are likely driven by dysfunctional host responses to infection and underlying co-morbid conditions rather than SARS-CoV-2 viral loads. Several parameters, including 4C mortality score, LDH levels, and DI score, were ultimately predictive of participant outcome and warrant further exploration in larger cohort studies for use in clinical management and risk assessment. Finally, the prevalence of intra-host diversity and viral evolution in hospitalized patients suggests a mechanism for population-level change, further emphasizing the need for effective antivirals to suppress viral replication and to avoid the emergence of new variants.