Differences in Inflammation, Treatment, and Outcomes Between Black and Non-Black Patients Hospitalized for COVID-19: A Prospective Cohort Study.

Clinical Significance • Compared to non-Blacks, Blacks had lower inflammatory burden after adjusting for co-morbidities, suggesting the existence of racial differences in the acute inflammatory response to COVID-19. • Blacks hospitalized for COVID-19 were less likely to receive corticosteroids and remdesivir prior to the FDA's emergency use authorization for remdesvir, and less likely to be enrolled in clinical trials. • Differences in outcomes between Blacks and non-Blacks were abrogated after adjusting for differences in therapy. Alt-text: Unlabelled box

Introduction

The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected minorities in the United States. 1 , 2 The prevalence of COVID-19 is higher in Black patients relative to other racial groups, 3 and Black patients have a higher prevalence of risk factors for severe COVID-19, including obesity, hypertension, diabetes mellitus, and kidney disease compared with non-Black patients. 4 , 5 , 6 , 7 However, reports on the association between Black race and worse COVID-19 outcomes have been discrepant. Nationwide data suggest Black patients account for a higher percentage of deaths relative to their representation in the general population. 8 However, a recent cohort study of more than 11,000 patients presenting to hospitals across the country found that there was no difference in in-hospital mortality between Black and white patients, even after accounting for age, gender, comorbidities, and markers of socioeconomic status. 9 Another recent study found that although Black and Hispanic patients were more likely to test positive for severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), rates of hospitalization were similar compared with white patients, and Black patients were less likely to die or be discharged on hospice care after adjusting for comorbidities and neighborhood characteristics. 10

Whether differences in COVID-19-related hospitalization outcomes between Black and non-Black patients relate to variations in levels of inflammatory markers or use of COVID-19-directed therapies is unclear. Most studies examining racial differences related to COVID-19 are derived from administrative databases limited by the lack of clinical detail in characterizing patients hospitalized for COVID-19. Black patients have been previously reported to receive suboptimal treatment as compared with white patients in a variety of settings, including following admission for pneumonia 11 and in-hospital cardiac arrest. 12 Minority groups have also been historically underrepresented in clinical trials, 13 , 14 , 15 an especially important consideration given the implications for the generalizability of COVID-19-directed therapeutics. 16

The main objective of this study is to understand the reasons underlying apparent racial disparities related to COVID-19, through detailed characterization of the clinical course of Black and non-Black patients hospitalized for COVID-19, including differences in comorbidities, levels of inflammatory markers, use of COVID-19-directed therapies, and participation in clinical trials. We leveraged the Michigan Medicine COVID-19 Cohort (M 2 C 2 ), a large prospective cohort in which patient hospitalized specifically for COVID-19 were identified and systematically enrolled and characterized.

Methods

Study Design

M 2 C 2 is an ongoing prospective cohort study initiated in February of 2020, which enrolls consecutive adults (≥18 years) with confirmed SARS-CoV-2 infection who were hospitalized specifically for COVID-19 at the University of Michigan. Patients with a positive test for SARS-CoV-2 hospitalized primarily for non-COVID-19 reasons were excluded. Patient eligibility for inclusion into M 2 C 2 was reviewed by 2 independent physicians at the time of admission. Manual chart review and data mining tools were used to gather details of the presentation, demographics, past medical history, home medications, laboratory studies, inpatient medical therapy, hospitalization course, and outcomes. Residual biological samples were collected for biomarker testing. All patients were followed until hospital discharge or in-hospital death. The study was approved by the University of Michigan institutional review board. The data set for this study included patients enrolled in M 2 C 2 from February 1, 2020 to March 26, 2021.

Exposures and Outcomes

The primary exposure was race as documented in the medical record; categorized as non-Hispanic Black versus non-Black patients. We collapsed non-Hispanic white (61.8%), Asian (4.7%), Hispanic (2.5%), and other races (5.3%) into a single “non-Black” category due to their limited numbers.

The outcomes examined were in-hospital death or discharge to hospice, need for mechanical ventilation, and need for renal replacement therapy during hospitalization.

Treatment for COVID-19 was defined as the receipt of any doses of the following therapies: corticosteroids, remdesivir, azithromycin, hydroxychloroquine, tocilizumab, therapeutic anticoagulation (specifically excluding anticoagulation for venous thromboembolism prophylaxis only), and convalescent serum. We also collected data on participation in COVID-19-related clinical trials.

Data on the following inflammatory markers measured within 48 hours of admission were collected: soluble urokinase plasminogen activator receptor (suPAR), C-reactive protein (CRP), interleukin-6 (IL-6), D-dimer, ferritin, lactate dehydrogenase (LDH), and procalcitonin.

Laboratory Measures

Data on levels of CRP, D-dimer, ferritin, LDH, and procalcitonin measured within 48-hours of presentation were extracted from the medical record. We measured suPAR in plasma using a commercially available enzyme-linked immunosorbent assay (SuPARnostic assay by ViroGates, Birkerød) in residual samples obtained from the clinical laboratory. The lower detection limit of the assay is 100 pg/mL with minimal intra- and interassay variation (2.75% and 9.17%, respectively) per the manufacturer. We measured IL-6 with an enzyme-linked immunosorbent assay (Quantikine QuicKitTM ELISA, Human IL-6 Immunoassay). The IL-6 assays have a lower detection limit of 1.70 pg/mL and intra- and interassay variation of 2.6% and 4.5%, respectively, as reported by the assay manufacturer.

Statistical Analysis

We first compared clinical characteristics between Black and non-Black patients. Categorical variables were presented as frequencies with percentages, whereas continuous variables were presented as means with standard deviations if normally distributed or medians with interquartile ranges if non-normally distributed. χ 2 tests were used to compare categorical variables and student t -tests and Mann-Whitney U tests were used for normally and non-normally distributed continuous variables, respectively. We also report the use of COVID-19 therapies stratified by period (before and after May 1, 2020, which is date of the Emergency Use Approval (EUA) of remdesivir by the US Food and Drug Administration).

To determine whether racial differences between biomarker levels were independent of clinical characteristics, we used multivariable linear regression models where each biomarker was evaluated separately as the dependent variable and included race as an independent variable. Clinical characteristics included as covariates in each model were: age, gender, body mass index (BMI), diabetes mellitus, hypertension, coronary artery disease, heart failure, and creatinine-derived estimated glomerular filtration rate (eGFR) on admission.

To assess whether Black race was independently associated with outcomes—notably in-hospital death, need for mechanical ventilation, and need for dialysis—and assess the impact of select confounders on the association, we used binary logistic regression with stepwise modeling and each outcome as the dependent variable. Model 0 included race alone; model 1 (clinical characteristics) included race, age, gender, BMI, diabetes mellitus, hypertension, coronary artery disease, heart failure, chronic kidney disease, and eGFR on admission. Model 2 (inflammation) added CRP to model 1, and model 3 (COVID-19 therapies) added use of remdesivir and corticosteroids to the variables in Model 1.

Similarly, we used logistic regression to examine the association between race (independent variable) and the use of COVID-19 therapies; notably remdesivir and corticosteroids (dependent variables in separate models). We included the following covariates in each model: age, sex, BMI, diabetes mellitus, hypertension, coronary artery disease, heart failure, and eGFR on admission. All analyses were performed in SPSS Statistics 27 (IBM).

Results

Differences in Clinical Characteristics Between Black and Non-Black Patients

At the time of database lock for the purpose of this study (March 26, 2021), a total of 1325 patients (mean age 61 years, 57.1% male) had been hospitalized for COVID-19 at the University of Michigan Health System, comprising 341 (25.7%) Black patients and 984 (74.2%) non-Black patients. White individuals represented the majority of non-Black patients (n = 819, 83.2%), followed by Asian (n = 62, 6.3%), other/unknown race (n = 70, 7.1%), and Hispanic (n = 33, 3.4%).

Black patients were on average younger than non-Black patients and had higher average BMI ( Table 1 ). The prevalence of cardiovascular and COVID-19 risk factor rates was higher in Black patients compared with non-Black patients: hypertension (75.7% vs 59.0%, P < .001), diabetes mellitus (48.1% vs 35.6%, P < .001), and chronic kidney disease (22.6% vs 16.8%, P = .017) ( Table 1 ). Table 1 Demographics and Clinical Characteristics by Self-Reported Race Table 1 Variables Overall Cohort (n = 1325) Non-Black Race * (n = 984) Black Race (n = 341) P Value Age, years, mean (SD) 61 (16) 62 (16) 58 (15) .001 Male, n (%) 757 (57.1%) 578 (58.7%) 179 (52.5%) .045 BMI, kg/m 2 , mean (SD) 32 (9) 31 (8) 34 (9) <.001 History of tobacco use, n (%) 571 (43.1%) 433 (44.0%) 138 (40.5%) .26 Diabetes mellitus, n (%) 514 (38.8%) 350 (35.6%) 164 (48.1%) <.001 Hypertension, n (%) 839 (63.3%) 581 (59.0%) 258 (75.7%) <.001 Coronary artery disease, n (%) 219 (16.5%) 174 (17.7%) 45 (13.2%) .06 Congestive heart failure, n (%) 167 (12.6%) 117 (11.9%) 50 (14.7%) .18 Chronic kidney disease, n (%) 242 (18.3%) 165 (16.8%) 77 (22.6%) .017 End-stage renal disease on dialysis, n (%) 44 (3.3%) 27 (2.7%) 17 (5.0%) .047 Admission eGFR, mean (SD) 67 (32) 69 (30) 64 (37) .020 Presenting Symptoms, n (%) Fever 790 (59.6%) 577 (58.6%) 213 (62.5%) .22 Shortness of breath 990 (74.7%) 733 (74.5%) 257 (75.4%) .75 Diarrhea 383 (28.9%) 267 (27.1%) 116 (34.0%) .016 Altered mental status 146 (11.0%) 115 (11.7%) 31 (9.1%) .19 Laboratory Data, † mean (SD) Hemoglobin, g/dL 13.1 (2.2) 13.1 (2.3) 12.9 (2.0) .11 White blood cell count, k/uL 7.7 (5) 7.6 (5.3) 8 (3.9) .23 Absolute neutrophil, count, k/uL 5.9 (4.2) 5.8 (4.5) 6.1 (3.4) .29 Absolute lymphocyte count, k/uL 1.2 (3.0) 1.2 (3.4) 1.1 (1.0) .50 Aspartate aminotransferase, IU/L 59 (57) 57 (55) 66 (64) .025 Alanine aminotransferase, IU/L 46 (52) 47 (53) 44 (50) .37 Total bilirubin, mg/dL 0.73 (1.11) 0.72 (1.25) 0.73 (0.56) .98 Creatinine, mg/dL 1.8 (4.6) 1.6 (4.9) 2.4 (3.3) .007 Inflammatory Markers, median (IQR) SuPAR, ng/mL 7.77 (5.46-12.17) 7.89 (5.48-12.28) 7.54 (5.39-12.12) .45 C-reactive protein, mg/dL 8.70 (4.70-17.27) 8.30 (4.10-16.30) 10.20 (5.80-18.80) <.001 Lactate dehydrogenase, IU/L 376 (277-516) 356 (267-487) 430 (325-588) <.001 Interleukin-6, pg/mL 12.50 (12.50-95.00) 12.50 (12.50-87.93) 20.00 (12.50-105.89) .19 Procalcitonin, ng/mL 0.18 (0.10-0.48) 0.17 (0.09-0.41) 0.24 (0.11-0.70) <.001 Ferritin, ng/mL 684 (299-1368) 624 (270-1256) 844 (385-1557) <.001 D-dimer, FEU mg/L 1.00 (0.57-1.98) 0.90 (0.54-1.73) 1.34 (0.73-2.93) <.001 Outcomes, n (%) Need for mechanical ventilation 389 (29.4%) 262 (26.6%) 127 (37.2%) <.001 Need for renal replacement therapy 124 (9.4%) 70 (7.1%) 54 (15.8%) <.001 In-hospital death 191 (14.4%) 138 (14.0%) 53 (15.5%) .49 BMI = body mass index; eGFR = estimated glomerular filtration rate; IQR = interquartile range; SD = standard deviation; suPAR = soluble urokinase plasminogen activator receptor. ⁎ Includes 819 white patients, 33 Hispanics, 62 Asian patients, and 70 of unknown race or other. † First value within 48 hours of presentation.

Clinical Presentation

Frequency of respiratory symptoms on presentation of COVID-19 was similar between Black and non-Black patients, with no significant differences in cough, shortness of breath, fever, or altered mental status. Black patients were, however, more likely to have diarrhea on presentation (34.0% vs 27.1%, P = .016) ( Table 1 ).

Black patients had a higher mean CRP (2.4 mg/dL vs 1.6 mg/dL, P = .007) and aspartate aminotransferase (64 IU/L vs 57 IU/L, P = .025) on admission than non-Black patients. There were no significant differences in hemoglobin, white blood cell count, absolute neutrophil/lymphocyte count, aspartate aminotransferase, or total bilirubin ( Table 1 ).

Inflammatory Markers

In univariable analysis, Black patients had higher median CRP (10.2 mg/dL vs 8.3 mg/dL, P < .001), LDH (430 IU/L vs 356 IU/L, P < .001), procalcitonin (20.0 ng/mL vs 12.5 ng/mL, P < .001), ferritin (844 ng/mL vs 624 ng/mL, P < .001), and D-dimer (1.34 FEU mg/L vs 0.90 FEU mg/L, P < .001). There were no differences between Black patients and non-Black patients in suPAR or IL-6 levels ( Table 1 ). After adjusting for clinical characteristics and COVID-19 risk factors, Black race was associated with lower suPAR and CRP levels ( Table 2 ). Table 2 Biomarkers of Thrombo-Inflammation and Black Race Table 2 Biomarker, β (95%CI) SuPAR C-reactive protein Lactate dehydrogenase Interleukin-6 Procalcitonin Ferritin D-dimer Black race −1.00 (−1.93 to −0.07) −7.74 (−13.86 to −1.61) 73 (31-114) 19.93(−81.70 to 121.56) 0.75 (−4.69 to 6.18) 439 (187-691) −0.17 (−5.87 to 5.54) Age, per 1 year −0.03 (−0.06 to 0.00) −0.20 (−0.41 to 0.02) −1 (−3 to 0) −2.01 (−5.93 to 1.91) 0.03 (−0.17 to 0.22) −4 (−13 to 5) 0.09 (−0.11 to 0.29) Male gender −0.67 (−1.52 to 0.19) −5.09 (−10.54 to 0.35) −42 (−80 to −5) −78.68 (−178.31 to 20.95) −0.77 (−5.69 to 4.14) −522 (−747 to −297) −3.68 (−8.74 to 1.38) BMI, per 1 kg/m 2 0.07 (0.02-0.12) 0.05 (−0.29 to 0.39) 2 (0-5) 0.30 (−6.17 to 6.76) −0.16 (−0.46 to 0.15) 0 (−14 to 14) 0.39 (0.08-0.71) Diabetes mellitus 0.54 (−0.39 to 1.48) 6.20 (0.19-12.21) −12 (−53 to 30) 81.59 (−26.96 to 190.15) −1.62 (−7.03 to 3.80) 121 (−127 to 367) −1.47 (−7.04 to 4.09) Hypertension −0.68 (−1.69 to 0.33) −0.79 (−7.19 to 5.61) −54 (−98 to −9) −46.49 (−165.83 to 72.86) −3.51 (−9.30 to 2.27) −204 (−470 to 62) −3.53 (−9.51 to 2.45) Coronary artery disease 1.03 (−0.20 to 2.26) −8.49 (−16.49 to −0.50) −37 (−92 to 18) −33.86 (−174.29 to 106.57) −0.79 (−7.85 to 6.26) −113 (−439 to 213) −0.42 (−7.84 to 7.01) Heart failure 0.62 (−0.71 to 1.94) 0.46 (−8.23 to 9.15) 16 (−43 to 74) 34.63 (−113.93 to 183.19) −2.34 (−10.10 to 5.41) −242 (−592 to 109) −0.68 (−8.58 to 7.22) Admission eGFR −0.06 (−0.08 to −0.05) −0.10 (−0.20 to 0.01) −1 (−2 to 0) −1.00 (−2.79 to 0.79) −0.06 (−0.15 to 0.03) −8 (−12 to −3.6) 0.00 (−0.09 to 0.10) BMI = body mass index; CI = confidence interval; eGFR = estimated glomerular filtration rate.

COVID-19 Therapies

Black patients were more likely to receive hydroxychloroquine (31.7% vs 14.3%, P < .001), azithromycin (35.8% vs 23.9%, P < .001), and tocilizumab (15.8% vs 8.8%, P < .001) and less likely to receive remdesivir (23.8% vs 57.8%, P < .001), corticosteroids (44.9% vs 63.8%, P < .001), and convalescent serum (2.9% vs 9.0%, P < .001) than non-Black patients ( Figure 1 ). Black patients were also less likely to be enrolled in any COVID-19-related clinical trial than non-Black patients (15.3% vs 28.2%, P < .001) ( Figure 1 ). Figure 1 Use of COVID-19-related therapies according to race. Horizontal bar graph demonstrating the proportion of Black and non-Black patients receiving each therapy with associated P value from univariable analysis. COVID-19 = coronavirus disease 2019. Figure 1

In multivariable analysis adjusting for age, gender, comorbidities, and eGFR at admission, Black race was independently associated with a lower odds of receiving remdesivir (adjusted odds ratio [aOR] 0.24 [0.18-0.32], P < .001), receiving corticosteroids (aOR 0.45 [0.35-0.58], P < .001), or being enrolled in a COVID-19 clinical trial (aOR 0.47, [0.32-0.68], P < .001). ( Table 3 ). When examining the use of COVID-19 therapies stratified by time period (prior to or after May 1, 2020, the date of EUA of remdesivir), we noted a significant increase in the use of remdesivir and corticosteroids in Black patients ( Figure 2 ), with differences in their use between Black patients and non-Black patients no longer being significant post-EUA. Table 3 Multivariable Analysis of Select COVID-19-Directed Interventions Table 3 Intervention, β (95%CI) Remdesivir Corticosteroids Clinical Trial Enrollment Black race 0.24 (0.18-0.32) 0.45 (0.35-0.58) 0.47 (0.32-0.68) Age, per 1 year 1.02 (1.01-1.03) 1.00 (0.99-1.01) 1.00 (0.99-1.02) Female sex 0.88 (0.70-1.11) 0.89 (0.71-1.12) 0.72 (0.54-0.97) BMI, per 1 kg/m 2 1.01 (0.995-1.03) 1.00 (0.99-1.02) 1.02 (1.00-1.04) Diabetes mellitus 0.91 (0.70-1.18) 0.94 (0.73-1.21) 0.88 (0.64-1.21) Hypertension 0.93 (0.71-1.23) 1.03 (0.81-1.39) 0.97 (0.69-1.35) Coronary artery disease 1.05 (0.75-1.47) 0.98 (0.70-1.36) 0.94 (0.61-1.45) Heart failure 0.81 (0.56-1.19) 0.91 (0.63-1.31) 0.43 (0.24-0.77) eGFR at admission, per 1 mL/min 1.00 (1.00-1.01) 1.00 (0.99-1.00) 1.00 (1.00-1.01) BMI = body mass index; CI = confidence interval; COVID-19 = coronavirus disease 2019; eGFR = estimated glomerular filtration rate. Figure 2 COVID-19-directed interventions in black patients prior to and after EUA approval of remdesivir. Clustered bar graph showing proportions of Black patients pre- and post-EAU of remdesivir (periods 1 and 2, respectively), in additional to the proportion of non-Black patients in period 2 receiving COVID-19 therapies. P value is derived from the comparison between Black patients and non-Black patients in their receipt of COVID-19 therapies in period 2. COVID-19 = coronavirus disease 2019; EAU = emergency use authorization. Figure 2

Outcomes

Overall mortality in the cohort was 14.4%. Although there was no statistically significant difference in mortality between Black patients and non-Black patients (15.5 vs 14.0%, P = .49), Black patients were more likely to require mechanical ventilation (37.2% vs 26.6%, P < .001) and renal replacement therapy (15.8% vs 7.1%, P < .001) ( Table 1 ).

In multivariable analysis, Black race was only associated with increased risk of death after adjustment for inflammation as measured by CRP levels, and the associations with mechanical ventilation and renal replacement therapy were strengthened ( Figure 3 ). Adjustment for the use of remdesivir and corticosteroids eliminated these associations, suggesting that the higher odds of mechanical ventilation and renal replacement therapy in Black patients may have been due to the lower rate of use of these therapies in Black patients prior to May 1, 2020. Figure 3 Odds ratios for Black race as a risk factor for COVID-19-related outcomes. Bar graphs showing the odds ratios for Black race for mortality, need for mechanical ventilation, and need for renal replacement therapy during hospitalization for COVID-19. Model 0 includes Black versus non-Black race only; model 1 includes race, sex, age, BMI, diabetes mellitus, hypertension, coronary artery disease, heart failure, chronic kidney disease, and eGFR on admission; model 2 adds CRP to model 1; and lastly, model 3 includes the use of remdesivir and corticosteroids. Error bars denote 95% confidence intervals. Dashed line denotes odds ratio of 1, with non-Black race being the reference. BMI = body mass index; COVID-19 = coronavirus disease 2019; CRP = C-reactive protein; eGFR = estimated glomerular filtration rate. Figure 3

Discussion

There has been much debate on the reasons that underlie racial disparities in COVID-19-related outcomes. We shed light on potential causes in this prospective cohort study of patients hospitalized specifically for COVID-19 who were extensively characterized and had measures of inflammation. We found that Black compared with non-Black patients had similar in-hospital death rates despite a higher prevalence of comorbidities and COVID-19 risk factors, which may be explained by the lower burden of inflammation as measured by CRP and suPAR levels. Black patients were less likely to receive remdesivir and corticosteroids or enroll in clinical trials, which our data suggest may have impacted their outcomes because the associations between Black race and the need for mechanical ventilation or renal replacement therapy were obviated after adjustment for the differential use of these therapies. To our knowledge, this is the first study analyzing the interplay among inflammation, treatment, and outcomes as it relates to racial differences in COVID-19.

Throughout the COVID-19 pandemic, racial disparities in infection rates, 17 hospitalization rates, 18 , 19 and overall mortality 17 , 20 have been described. These differences are likely closely tied to socioeconomic status because they are somewhat attenuated after adjustment for risk factors, including age, sex, comorbidities, insurance, neighborhood, and access to care. Several studies have shown no differences in in-hospital mortality. 9 , 20 , 21 A complex interplay between social determinants of health and associated comorbidity burden has been posited as the basis for the observed disparities in COVID-19 infection rate. 22 , 23 , 24 This study builds on the current body of knowledge by providing data on the impact of underlying inflammation and differing treatments to COVID-19-related outcomes.

A recent review posited that observed racial and ethnic differences in COVID-19 outcomes may arise from a differential inflammatory response between groups, driven by underlying differences in chronic inflammation from different burdens of comorbidity, socioeconomic factors, genetic factors, and psychologic stressors. 25 Differences in chronic inflammation as measured by CRP levels have been previously described, with several studies finding that Black patients have higher median CRP levels than white patients, though these differences were heavily attenuated after accounting for differences in comorbidities and psychosocial factors. 26 , 27 Similarly, after adjusting for cardiovascular and COVID-19 risk factors, Black race compared with non-Black was associated with relatively lower levels of CRP and suPAR, reflecting perhaps an attenuated inflammatory response to SARS-CoV-2 infection and leading to similar survival rates compared to non-Black patients despite their significantly higher burden of comorbidities. Studies on racial differences in acute inflammation are few. In 1 study, Black participants exhibited an attenuated inflammatory response compared to non-Blacks when exposed to endotoxin. 28 Nevertheless, these findings warrant further investigation into racial differences in the immune response and their mechanisms.

Our study found substantial treatment differences between Black and non-Black patients that persisted even after multivariable adjustment. Racial disparities in treatment in medicine are well-described in diseases as diverse as pneumonia, 29 cardiac arrest, 30 appendicitis, 31 and end-stage renal disease. 32 At the time of writing, no study has evaluated racial differences in the in-hospital management of COVID-19. These differences in the use of COVID-19-directed therapies such as remdesivir are at least partially related to the lower enrollment of Black patients in clinical trials, as we noted its rate of use dramatically increased to levels that were similar by race after its EUA by the U.S. Food and Drug Administration. Disproportionately low enrollment of Black patients in clinical trials has been demonstrated time and again, including in heart failure, 33 multiple myeloma, 13 cancer phase III trials, 34 HIV, 35 and others. Many theories have been proposed for why this disparity has been found, and much of the discussion focuses on reluctance among Black patients, a legacy of the unethical, abhorrent Tuskegee Syphilis study, 36 and investigator bias. 37 , 38 The reasons for reduced enrollment of Black patients in clinical trials in our study unfortunately could not be ascertained. However, we show that differences in management may have major consequences because differences in the incidence of mechanical ventilation and renal replacement therapy were abrogated after adjustment for the use of COVID-19-directed therapies.

Our study has major strengths, including the prospective and systematic inclusion of patients hospitalized specifically for COVID-19, rather than patients hospitalized with a positive SARS-CoV-2 test. We have complemented our assessment of conventional biomarkers of inflammation such as CRP, ferritin, D-dimer, LDH, and procalcitonin with measurements of nonconventional measurements of inflammation such as suPAR and IL-6. We used admission biomarkers levels as opposed to serial measurements to avoid confounding by therapies administered. Serial biomarker measurements may shed light on racial differences to response to therapy. The major limitations are in the observational nature of the study and the inability to capture reasons for not enrolling in clinical trials, precluding making strong conclusions on the impact of racial differences in management on COVID-19-related outcomes.

Conclusion

In conclusion, our study demonstrates significant differences in inflammation, use of COVID-19-directed therapies, and outcomes, notably the need both for mechanical ventilation and renal replacement therapy and death between Black and non-Black patients hospitalized for COVID-19. These findings should prompt additional studies on racial differences in acute inflammation, as well as scrutiny of institutional treatment protocols to reduce racial differences in treatment and clinical trial enrollment.

References

1 Yancy CW COVID-19 and African Americans JAMA 323 19 2020 1891 1892 10.1001/jama.2020.6548 32293639

2 Thebault R, Tran AB, Williams V. The coronavirus is infecting and killing black Americans at an alarmingly high rate. Washington Post . Available at: https://www.washingtonpost.com/nation/2020/04/07/coronavirus-is-infecting-killing-black-americans-an-alarmingly-high-rate-post-analysis-shows/ . Accessed April 28, 2020.

3 Garg S Kim L Whitaker M Hospitalization rates and characteristics of patients hospitalized with laboratory-confirmed Coronavirus disease 2019 — COVID-NET, 14 States, March 1–30, 2020 MMWR Morb Mortal Wkly Rep 69 2020 458 464 10.15585/mmwr.mm6915e3 32298251 PMC7755063

4 Mensah George A Mokdad Ali H Ford Earl S Greenlund Kurt J Croft Janet B State of disparities in cardiovascular health in the United States Circulation 111 10 2005 1233 1241 10.1161/01.CIR.0000158136.76824.04 15769763

5 Centers for Disease Control and Prevention (CDC). African American Health. Available at: https://www.cdc.gov/vitalsigns/aahealth/index.html . Accessed August 6, 2020.

6 Nicholas SB Kalantar-Zadeh K Norris KC Racial disparities in kidney disease outcomes Semin Nephrol 33 5 2013 409 415 10.1016/j.semnephrol.2013.07.002 24119846 PMC3983362

7 Carethers JM Insights into disparities observed with COVID-19 J Intern Med 289 4 2021 463 473 10.1111/joim.13199 33164230 PMC9325576

8 Centers for Disease Control and Prevention (CDC). Coronavirus Disease 2019 (COVID-19) in the U.S. Available at: https://covid.cdc.gov/covid-data-tracker . Accessed September 17, 2020.

9 Yehia BR Winegar A Fogel R Association of race with mortality among patients hospitalized with coronavirus disease 2019 (COVID-19) at 92 US hospitals JAMA Netw Open 3 8 2020 e2018039 10.1001/jamanetworkopen.2020.18039 PMC7435340 32809033

10 Ogedegbe G Ravenell J Adhikari S Assessment of racial/ethnic disparities in hospitalization and mortality in patients with COVID-19 in New York City JAMA Netw Open 3 12 2020 e2026881 10.1001/jamanetworkopen.2020.26881 PMC7718605 33275153

11 Hausmann LRM Ibrahim SA Mehrotra A Racial and ethnic disparities in pneumonia treatment and mortality Med Care 47 9 2009 1009 1017 10.1097/MLR.0b013e3181a80fdc 19648832 PMC6521966

12 Chan PS Nichol G Krumholz HM Racial differences in survival after in-hospital cardiac arrest JAMA J Am Med Assoc 302 11 2009 1195 1201 10.1001/jama.2009.1340 PMC2795316 19755698

13 Duma N Azam T Riaz IB Gonzalez-Velez M Ailawadhi S Go R. Representation of minorities and elderly patients in multiple myeloma clinical trials Oncologist 23 9 2018 1076 1078 10.1634/theoncologist.2017-0592 29700207 PMC6192659

14 Zullig LL Fortune-Britt AG Rao S Tyree SD Godley PA Carpenter WR Enrollment and racial disparities in National Cancer Institute Cancer Treatment Clinical Trials in North Carolina N C Med J 77 1 2016 52 58 10.18043/ncm.77.1.52 26763244 PMC4714783

15 Kwiatkowski K Coe K Bailar JC Swanson GM Inclusion of minorities and women in cancer clinical trials, a decade later: have we improved? Cancer 119 16 2013 2956 2963 10.1002/cncr.28168 23674318

16 Carethers JM Rectifying COVID-19 disparities with treatment and vaccination JCI Insight 6 4 2021 147800 10.1172/jci.insight.147800 PMC7934932 33476304

17 Mackey K Ayers CK Kondo KK Racial and ethnic disparities in COVID-19–related infections, hospitalizations, and deaths Ann Intern Med 174 3 2020 362 373 10.7326/M20-6306 33253040 PMC7772883

18 Gu T Mack JA Salvatore M Characteristics associated with racial/ethnic disparities in COVID-19 outcomes in an Academic Health Care System JAMA Netw Open 3 10 2020 2025197 10.1001/jamanetworkopen.2020.25197 PMC7578774 33084902

19 Krishnamoorthy G Arsene C Jena N Racial disparities in COVID-19 hospitalizations do not lead to disparities in outcomes Public Health 190 2021 93 98 10.1016/j.puhe.2020.11.021 33385640 PMC7698674

20 Price-Haywood EG Burton J Fort D Seoane L Hospitalization and mortality among black patients and white patients with Covid-19 N Engl J Med 382 26 2020 2534 2543 10.1056/NEJMsa2011686 32459916 PMC7269015

21 Kabarriti R Brodin NP Maron MI Association of race and ethnicity with comorbidities and survival among patients with COVID-19 at an Urban Medical Center in New York JAMA Netw Open 3 9 2020 e2019795 10.1001/jamanetworkopen.2020.19795 PMC7519416 32975574

22 Boulware LE Race disparities in the COVID-19 pandemic-solutions lie in policy, not biology JAMA Netw Open 3 8 2020 e2018696 10.1001/jamanetworkopen.2020.18696 32809027

23 Hooper MW Nápoles AM Pérez-Stable EJ COVID-19 and racial/ethnic disparities JAMA 323 24 2020 2466 2467 10.1001/jama.2020.8598 32391864 PMC9310097

24 Chowkwanyun M Reed AL Racial health disparities and Covid-19 — caution and context N Engl J Med 383 3 2020 201 203 10.1056/NEJMp2012910 32374952

25 Vepa A Bae JP Ahmed F Pareek M Khunti K COVID-19 and ethnicity: a novel pathophysiological role for inflammation Diabetes Metab Syndr 14 5 2020 1043 1051 10.1016/j.dsx.2020.06.056 32640416 PMC7326443

26 Khera A McGuire DK Murphy SA Race and gender differences in C-reactive protein levels J Am Coll Cardiol 46 3 2005 464 469 10.1016/j.jacc.2005.04.051 16053959

27 Farmer HR Wray LA Xian Y Racial differences in elevated C-reactive protein among US older adults J Am Geriatr Soc 68 2 2020 362 369 10.1111/jgs.16187 31633808 PMC8211020

28 Race and gender variation in response to evoked inflammation J Transl Med . Available at: https://translational-medicine.biomedcentral.com/articles/10.1186/1479-5876-11-63 . Accessed September 1, 2021. 10.1186/1479-5876-11-63 PMC3636014 23497455

29 Hausmann LRM Ibrahim SA Mehrotra A Racial and ethnic disparities in pneumonia treatment and mortality Med Care 47 9 2009 1009 1017 10.1097/MLR.0b013e3181a80fdc 19648832 PMC6521966

30 Chan PS Nichol G Krumholz HM Racial differences in survival after in-hospital cardiac arrest JAMA J Am Med Assoc 302 11 2009 1195 1201 10.1001/jama.2009.1340 PMC2795316 19755698

31 Goyal MK Kuppermann N Cleary SD Teach SJ Chamberlain JM Racial disparities in pain management of children with appendicitis in emergency departments JAMA Pediatr 169 11 2015 996 10.1001/jamapediatrics.2015.1915 26366984 PMC4829078

32 Ku E Lee BK McCulloch CE Racial and ethnic disparities in kidney transplant access within a theoretical context of medical eligibility Transplantation 104 7 2020 1437 1444 10.1097/TP.0000000000002962 31568216 PMC7067676

33 Tahhan AS Vaduganathan M Greene SJ Enrollment of older patients, women, and racial and ethnic minorities in contemporary heart failure clinical trials: a systematic review JAMA Cardiol 3 10 2018 1011 1019 10.1001/jamacardio.2018.2559 30140928

34 Khandwala P Desai D Das DG Desai A Racial disparities in cancer clinical trials J Clin Oncol 38 29suppl 2020 97 10.1200/JCO.2020.38.29_suppl.97

35 Gifford AL Cunningham WE Heslin KC Participation in research and access to experimental treatments by HIV-infected patients N Engl J Med 346 18 2002 1373 1382 10.1056/NEJMsa011565 11986412

36 Katz RV Kegeles SS Kressin NR The Tuskegee Legacy Project: willingness of minorities to participate in biomedical research J Health Care Poor Underserved 17 4 2006 698 715 10.1353/hpu.2006.0126 17242525 PMC1780164

37 Getz K Faden L Racial disparities among clinical research investigators Am J Ther 15 1 2008 3 11 10.1097/MJT.0b013e31815fa75a 18223347

38 Niranjan SJ Martin MY Fouad MN Bias and stereotyping among research and clinical professionals: perspectives on minority recruitment for oncology clinical trials Cancer 126 9 2020 1958 1968 10.1002/cncr.32755 32147815

Acknowledgments

The authors acknowledge the University of Michigan Medical School Research Data Warehouse and DataDirect for providing data aggregation, management, and distribution services in support of the research reported in this publication. The authors are grateful to the services of the Microbiome Core supported by U2CDK110768, especially Chris Blair; the Michigan Clinical Research Unit including Wrenn Woodard and Dexter Hobdy, and the University of Michigan Medical School Central Biorepository for providing biospecimen storage, management, and distribution services in support of the research reported in the publication.

Funding: RP-B is supported by NIH/NIDDK-1-R01-DK-107956-01, NIH U01 DK119083 , and Juvenile Diabetes Research Foundation. SSH is funded by NIH 1R01HL153384, U01-DK119083, R01-DK109720. and the Frankel Cardiovascular Center COVID-19: Impact Research Ignitor (U-M G024231) award.

Conflicts of Interest: The wife of CW works at Regeneron Pharmaceuticals. SSH is a member of the scientific advisory board of Walden Biosciences. TUA, HB, EA, MP, HRS, KP, PO'H, CM, RF, EM, CL, PB, AB, RP-B, JMC report none.

Authorship: All authors had access to the data and a role in writing this manuscript.