Racial and Ethnic Disparities in Disease Severity on Admission Chest                     Radiographs among Patients Admitted with Confirmed Coronavirus Disease 2019: A                     Retrospective Cohort Study

Joseph, Nicholos; Reid, Nicholas; Som, Avik; Li, Matthew; Hyle, Emily P; Dugdale, Caitlin M; Lang, Min; Betancourt, Joseph R.; Deng, Francis; Mendoza, Dexter P.; Little, Brent P.; Narayan, Anand K.; Flores, Efrén J.

doi:10.1148/radiol.2020202602

Cited by 65 publications

(87 citation statements)

References 29 publications

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“…The rate of delirium in this cohort is much higher than typically reported in ED studies before COVID-19, which ranged from 7% to 20%, 29 although the factors associated with risk of delirium are similar to those identified in ED and inpatient research before COVID-19. 7,30,31 Mounting evidence supports the high occurrence of delirium and other neuropsychiatric manifestations with COVID-19, with previously reported rates of 22% to 33% among hospitalized patients. 19,21 In another medical Downloaded From: https://jamanetwork.com/ on 12/01/2020…”

Section: Resultsmentioning

confidence: 61%

“…7,31 The racial and ethnic diversity of our cohort may have contributed to higher rates of delirium because non-White patients hospitalized with COVID-19 may present with higher severity of disease in the US.32 It is also possible that the patients may have presented to the ED at a later stage of COVID-19 because of family or clinicians not recognizing delirium as an important symptom, or because of delays in assessment either from fear of exposure to COVID-19 or difficulty accessing medical care. Furthermore, the data from this multicenter study strongly support an immediate revision in CDC guidance on symptom profiles for COVID-19 to include delirium as an important COVID-19-related symptom.…”

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confidence: 99%

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Delirium in Older Patients With COVID-19 Presenting to the Emergency Department

et al. 2020

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IMPORTANCE Delirium is common among older emergency department (ED) patients, is associated with high morbidity and mortality, and frequently goes unrecognized. Anecdotal evidence has described atypical presentations of coronavirus disease 2019 (COVID-19) in older adults; however, the frequency of and outcomes associated with delirium in older ED patients with COVID-19 infection have not been well described. OBJECTIVE To determine how frequently older adults with COVID-19 present to the ED with delirium and their associated hospital outcomes.

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Section: Resultsmentioning

confidence: 61%

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confidence: 99%

Delirium in Older Patients With COVID-19 Presenting to the Emergency Department

et al. 2020

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“…Furthermore, language barriers have been associated with outcomes but limited data regarding its impact in COVID-19, as it relates to racial disparities, currently exist. (4)(5)(6) Racial and ethnic disparities in health are well documented in the United States and their elimination is an important public health and societal imperative. (7,8) The etiology of health disparities is multifactorial, especially with racism's multi-level societal construct which plays a key role in the challenges we face along the path to health equity.…”

Section: Introductionmentioning

confidence: 99%

Racial/Ethnic Disparities in Hospital Admissions from COVID-19 and Determining the Impact of Neighborhood Deprivation and Primary Language

Ingraham

Purcell

Karam

et al. 2020

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Importance Despite past and ongoing efforts to achieve health equity in the United States, persistent disparities in socioeconomic status along with multilevel racism maintain disparate outcomes and appear to be amplified by COVID-19. Objective Measure socioeconomic factors and primary language effects on the risk of COVID-19 severity across and within racial/ethnic groups. Design Retrospective cohort study. Setting Health records of 12 Midwest hospitals and 60 clinics in the U.S. between March 4, 2020 to August 19, 2020. Participants PCR+ COVID-19 patients. Patients missing race or ethnicity data or those diagnosed with COVID-19 during a hospitalization were excluded. Exposures Main exposures included race/ethnicity, area deprivation index (ADI), and primary language. Main Outcomes and Measures The primary outcome was COVID-19 severity using hospitalization within 45 days of diagnosis. Logistic and competing-risk regression models (censored at 45 days and accounting for the competing risk of death prior to hospitalization) assessed the effects of neighborhood-level deprivation (using the ADI) and primary language. Within race effects of ADI and primary language were measured using logistic regression. Results 5,577 COVID-19 patients were included, 866 (n=15.5%) were hospitalized within 45 days of diagnosis. Hospitalized patients were older (60.9 years, IQR: 45.7-75.9 vs. 40.4 years, IQR: 25.6-58.3, p<0.001) and more likely to be male (n=425 [49.1%] vs. 2,049 [43.5%], p=0.002). Of those requiring hospitalization, 43.9% (n=381), 19.9% (n=172), 18.6% (n=161), and 11.8% (n=102) were White, Black, Asian, and Hispanic, respectively. Independent of ADI, minority race/ethnicity was associated with COVID-19 severity; Hispanic patients (OR 3.8, 95% CI 2.72-5.30), Asians (OR 2.39, 95% CI 1.74-3.29), and Blacks (OR 1.50, 95% CI 1.15-1.94). Surprisingly ADI was not associated with hospitalization; however, consistent trends within racial/ethnic groups were observed. Furthermore, non-English speaking (OR 1.91, 95% CI 1.51-2.43) significantly increased odds of hospital admission across and within minority groups. Conclusions Minority populations have increased odds of severe COVID-19 independent of neighborhood deprivation, a commonly suspected driver of disparate outcomes during the pandemic. Non-English speaking also accounts for between and within minority populations. These results support continued concern that racism contributes to disparities during COVID-19 while also highlighting the underappreciated role primary language plays in COVID-19 severity across and within minority groups.

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“…Although recently published comprehensive studies from China address disease progression, our study is unique as it focuses on the United States. We note that work in other urban areas of the United States (i.e., New York and Los Angeles) has found strong differences in severe illness onset and outcomes across racial and ethnic groups [13][14][15][16][17][18][19][20][21][22]. In that context, our research focuses specifically on the population of Chicago, Illinois, which has a diverse and unique urban patient population.…”

Section: Studies Have Been Published Of the Clinical Characteristicsmentioning

confidence: 99%

A Retrospective Longitudinal Study of COVID-19 as Seen by a Large Urban Hospital in Chicago

Chen

Varatharajah

Ramirez

et al. 2020

Preprint

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The rapid spread of the novel coronavirus disease 2019 (COVID-19) has created a high demand for medical resources, including personnel, intensive care unit beds, and ventilators. As thousands of patients are hospitalized, the disease has shown remarkable diversity in its manifestation; many patients with mild to no symptoms recover from the disease requiring minimal care, but some patients with severe disease progression require mechanical ventilation support in intensive care units (ICU) with an increased risk of death. Studying the characteristics of patients in these various strata can help us understand the varied progression of this disease, enable earlier interventions for at-risk patients, and help manage medical resources more efficiently. This paper presents a retrospective analysis of 10,123 COVID-19 patients treated at the Rush University Medical Center in Chicago, including their demographics, symptoms, comorbidities, laboratory values, vital signs, and clinical history. Specifically, we present a staging scheme based on discrete clinical events (i.e., admission to the hospital, admission to the ICU, mechanical ventilation, and death), and investigate the temporal trend of clinical variables and the effect of comorbidities in each of those stages. We then developed a prognostic model to predict ventilation demands at an individual patient level by analyzing baseline clinical variables, which entails (1) a least absolute shrinkage and selection operator (LASSO) regression and a decision tree model to identify predictors for mechanical ventilation; and (2) a logistic regression model based on these risk factors to predict which patients will eventually need ventilatory support. Our results indicate that the prognostic model achieves an AUC of 0.823 (95% CI: 0.765-0.880) in identifying patients who will eventually require mechanical ventilation.

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Racial and Ethnic Disparities in Disease Severity on Admission Chest Radiographs among Patients Admitted with Confirmed Coronavirus Disease 2019: A Retrospective Cohort Study

Abstract: Sources of funding: No sources of funding were obtained for the preparation of this manuscript.

Cited by 65 publications

References 29 publications

Delirium in Older Patients With COVID-19 Presenting to the Emergency Department

Delirium in Older Patients With COVID-19 Presenting to the Emergency Department

Racial/Ethnic Disparities in Hospital Admissions from COVID-19 and Determining the Impact of Neighborhood Deprivation and Primary Language

A Retrospective Longitudinal Study of COVID-19 as Seen by a Large Urban Hospital in Chicago

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