key: cord-0929231-g0aisrtj
authors: Newton, Sophia; Zollinger, Benjamin; Freeman, Jincong; Moran, Seamus; Helfand, Alexandra; Authelet, Kayla; McHarg, Matthew; Montano Vargas, Nataly; Shesser, Robert; Cohen, Joanna S.; Cummings, Derek A.T.; Ma, Yan; Meltzer, Andrew C.
title: Factors associated with clinical severity in emergency department patients presenting with symptomatic SARS‐CoV‐2 infection
date: 2021-06-29
journal: J Am Coll Emerg Physicians Open
DOI: 10.1002/emp2.12453
sha: e3fee233b279e85d17682bf52387e4c0210d71ef
doc_id: 929231
cord_uid: g0aisrtj

OBJECTIVE: To measure the association of race, ethnicity, comorbidities, and insurance status with need for hospitalization of symptomatic emergency department patients with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection. METHODS: This study is a cohort study of symptomatic patients presenting to a single emergency department (ED) with laboratory‐confirmed SARS‐CoV‐2 infection from March 7‐August 9, 2020. We collected patient‐level information regarding demographics, insurance status, comorbidities, level of care, and mortality using a structured chart review. We compared characteristics of patients categorized by (1) home discharge, (2) general hospital ward admission, and (3) intensive care unit (ICU) admission or death within 30 days of the index visit. Univariate and multivariable logistic regression analyses were performed to report odds ratios (OR) and 95% confidence intervals (95% CI) between hospital admission versus ED discharge home and between ICU care versus general hospital ward admission. RESULTS: In total, 994 patients who presented to the ED with symptoms were included in the analysis with 551 (55.4%) patients discharged home, 314 (31.6%) patients admitted to the general hospital ward, and 129 (13.0%) admitted to the ICU or dying. Patients requiring admission were more likely to be Black or to have public insurance (Medicaid and/or Medicare). Patients who were admitted to the ICU or dying were more likely aged ≥ 65 years or male. In multivariable logistic regression, old age, public insurance, diabetes, hypertension, obesity, heart failure, and hyperlipidemia were independent predictors of hospital admission. When comparing those who needed ICU care versus general hospital ward admission in univariate logistic regression, patients with Medicaid (OR 2.4, 95% CI 1.2–4.6), Medicare (OR 4.2, 95% CI 2.1–8.4), Medicaid and Medicare (OR 4.3, 95% CI 2.4–7.7), history of chronic obstructive pulmonary disease (OR 2.2, 95% CI 1.2–4.2), hypertension (OR 1.7, 95% CI 1.1–2.7), and heart failure (OR 2.6, 95% CI 1.4–4.7) were more likely to be admitted into the ICU or die; Black (OR 1.1, 95% CI 0.4–2.9) and Hispanic/Latino (OR 1.0, 95% CI 0.6–1.8) patients were less likely to be admitted into the ICU; however, the associations were not statistically significant. In multivariable logistic regression, old age, male sex, public insurance, and heart failure were independent predictors of ICU care/death. CONCLUSION: Comorbidities and public insurance are predictors of more severe illness for patients with SARS‐CoV‐2. This study suggests that the disparities in severity seen in COVID‐19 among Black patients may be attributable, in part, to low socioeconomic status and chronic health conditions.

insurance, diabetes, hypertension, obesity, heart failure, and hyperlipidemia were independent predictors of hospital admission. When and heart failure (OR 2.6, 95% CI 1.4-4.7) were more likely to be admitted into the ICU or die; Black (OR 1.1, 95% CI 0.4-2.9) and Hispanic/Latino (OR 1.0, 95% CI 0. 6-1.8) patients were less likely to be admitted into the ICU; however, the associations were not statistically significant. In multivariable logistic regression, old age, male sex, public insurance, and heart failure were independent predictors of ICU care/death.

Comorbidities and public insurance are predictors of more severe illness for patients with SARS-CoV-2. This study suggests that the disparities in severity seen in COVID-19 among Black patients may be attributable, in part, to low socioeconomic status and chronic health conditions.

COVID-19 disease, emergency medicine, infectious diseases, SARS-CoV-2 infection, socioeconomic factors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in the United States in January 2020. Since then, there have been 25 million cases of SARS-CoV-2 infection with over 415,000 deaths in the United States, with transmission ongoing. 1 The clinical course of coronavirus disease 2019 (COVID- 19) , the disease caused by SARS-CoV-2, ranges widely in severity from asymptomatic to life threatening. The mechanism behind this wide variation in patient outcomes is not yet well understood. Many studies thus far have documented associations between underlying patient comorbidities and more severe disease prognoses. [2] [3] [4] [5] In addition, reports suggest that Black and Hispanic/Latino populations are disproportionately affected by COVID-19 disease with increased rates of infection and severity of illness compared to White populations. 6-8

Understanding the reason for disparities among different patient populations is critical for targeting interventions aimed at mitigating the impact of disease.

The objective of this study was to evaluate race, ethnicity, comorbidities, and insurance status as predictors of illness severity in patients presenting to the emergency department (ED) with symptomatic SARS-CoV-2 infection.

This was a single-center cohort study of patients with symptomatic SARS-CoV-2 infection presenting to an urban academic ED with ≈80,000 annual visits. The Institutional Review Board at The George Washington University in Washington, DC approved the study with a waiver of consent on March 30, 2020.

Patients were included if they tested positive for SARS-CoV-2 by nasopharyngeal swab using polymerase chain reaction at the index ED 

Patients were identified via monthly electronic health record (EHR) queries for positive tests for COVID-19 in the ED from March 12, 2020 until August 9, 2020. Data abstraction were performed after the index visit to capture 30-day outcomes. Chart review was performed according to guidelines by Gilbert et al. 9 Case report forms were created by Indiana University for use in a multicenter registry. All data were entered into a REDCap database. All data abstractors were trained specifically for this study and 10% of charts were verified by a second abstractor for accuracy.

Data were analyzed to identify significant associations by 3 categories Crude odds ratio (OR) and adjusted OR (aOR) and the corresponding 95% confidence intervals (95% CI) were reported. All analyses were completed using SAS 9.4 (SAS Institute, Cary, NC).

We collected patient-level data on a total of 994 patients seen in the ED from March 7-August 9. Of these, 551 were discharged from the (Table 2) .

Of the comorbid conditions analyzed, diabetes mellitus, hypertension, obesity, hyperlipidemia, and heart failure were independent predictors of hospital admission ( The actual mechanisms behind why certain comorbidities are associated with more severe outcomes are not yet well understood.

Regarding diabetes's association, deglycation has been proposed to play a role in weakening the immune response. 4, [25] [26] [27] The mechanistic relationship between uncontrolled hypertension and worse COVID-19 prognoses is not defined but hypertension has been associated with an increase in inflammatory markers and may be related to dysregulation of the renin-angiotensin-aldosterone axis. 28 Finally, we were unable to capture the severity and treatment status of comorbid conditions from chart review and, therefore, our results may not reflect the impact of underlying health conditions on the severity of COVID-19 for individual patients.

Predictors of disease severity for ED patients who present with COVID-19 include age, Medicaid or Medicare public insurance, diabetes mellitus, hypertension, obesity, hyperlipidemia, and heart failure.

Greater understanding of the factors that contribute to clinical variability in COVID-19 severity will assist in early identification of highrisk patients and enhance the precision of public health interventions. 

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AUTHOR BIOGRAPHY

Associate Professor of the Department of Emergency Medicine and Clinical Research Director of GWU School of Medicine and Health Sciences in Washington, DC. How to cite this article