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

Abstract

Background: Risk factors for progression of coronavirus disease 2019 (COVID-19) to severe disease or death are underexplored in U.S. cohorts.

Objective: To determine the factors on hospital admission that are predictive of severe disease or death from COVID-19.

Design: Retrospective cohort analysis.

Setting: Five hospitals in the Maryland and Washington, DC, area.

Patients: 832 consecutive COVID-19 admissions from 4 March to 24 April 2020, with follow-up through 27 June 2020.

Measurements: Patient trajectories and outcomes, categorized by using the World Health Organization COVID-19 disease severity scale. Primary outcomes were death and a composite of severe disease or death.

Results: Median patient age was 64 years (range, 1 to 108 years); 47% were women, 40% were Black, 16% were Latinx, and 21% were nursing home residents. Among all patients, 131 (16%) died and 694 (83%) were discharged (523 [63%] had mild to moderate disease and 171 [20%] had severe disease). Of deaths, 66 (50%) were nursing home residents. Of 787 patients admitted with mild to moderate disease, 302 (38%) progressed to severe disease or death: 181 (60%) by day 2 and 238 (79%) by day 4. Patients had markedly different probabilities of disease progression on the basis of age, nursing home residence, comorbid conditions, obesity, respiratory symptoms, respiratory rate, fever, absolute lymphocyte count, hypoalbuminemia, troponin level, and C-reactive protein level and the interactions among these factors. Using only factors present on admission, a model to predict in-hospital disease progression had an area under the curve of 0.85, 0.79, and 0.79 at days 2, 4, and 7, respectively.

Limitation: The study was done in a single health care system.

Conclusion: A combination of demographic and clinical variables is strongly associated with severe COVID-19 disease or death and their early onset. The COVID-19 Inpatient Risk Calculator (CIRC), using factors present on admission, can inform clinical and resource allocation decisions.

Primary funding source: Hopkins inHealth and COVID-19 Administrative Supplement for the HHS Region 3 Treatment Center from the Office of the Assistant Secretary for Preparedness and Response.

Visual Abstract.. Trajectories Among Patients Hospitalized for COVID-19

This retrospective analysis from 5 Maryland and Washington, DC, area hospitals determines factors on hospital admission predictive of severe disease or death from COVID-19 and describes patient trajectories and outcomes categorized using the WHO COVID-19 disease severity scale.

Figure.. Cumulative incidence of severe disease or death for characteristic patients.

The cumulative incidences are calculated from the model in Appendix Table 1. BMI = body mass index; CCI = Charlson Comorbidity Score; CRP = C-reactive protein. Left. Cumulative incidences at day 2, 4, and 7 after admission for 6 characteristic patients. These exemplars were chosen by selecting for key characteristics that are known to affect risk in our Cox models. Right. Cumulative incidence plots for each characteristic patient. The plots show how some patients have a higher likelihood of progression to severe disease or death and progress at a faster rate than others. For example, patient A has an 80% risk for severe disease or death by day 2, whereas patient F has only a 3% risk. The slope of the curve for patient A is also steeper than that of the others.