Abstract
Background
Studies of COVID-19 have shown that African Americans have been affected by the virus at a higher rate compared to other races. This cohort study investigated comorbidities and clinical outcomes by race among COVID-19 patients admitted to the intensive care unit.
Methods
This is a case series of critically ill patients admitted with COVID-19 to an academic healthcare system in Atlanta, Georgia. The study included all critically ill hospitalized patients between March 6, 2020, and May 5, 2020. Clinical outcomes during hospitalization included mechanical ventilation, renal replacement therapy, and mortality stratified by race.
Results
Of 288 patients included (mean age, 63 ± 16 years; 45% female), 210 (73%) were African American. African Americans had significantly higher rates of comorbidities compared to other races, including hypertension (80% vs 59%, P = 0.001), diabetes (49% vs 34%, P = 0.026), and mean BMI (33 kg/m2 vs 28 kg/m2, P < 0.001). Despite African Americans requiring continuous renal replacement therapy during hospitalization at higher rates than other races (27% vs 13%, P = 0.011), rates of intubation, intensive care unit length of stay, and overall mortality (30% vs 24%, P = 0.307) were similar.
Conclusion
This racially diverse series of critically ill COVID-19 patients shows that despite higher rates of comorbidities at hospital admission in African Americans compared with other races, there was no significant difference in mortality.
Supplementary Information
The online version contains supplementary material available at 10.1007/s40615-021-00966-0.
Keywords: COVID-19, Mortality, Race, African American, Outcomes
Introduction
The coronavirus disease 2019 (COVID-19) has led to death tolls surpassing 2,000,000 people globally and 395,000 people in the USA [1, 2]. Studies to date have shown that COVID-19 infects African Americans (AA) at a higher rate compared with other major races in the USA; the Centers for Disease Control and Prevention (CDC) has found that AA have a 178.1/100,000 rate of COVID-19, second to only Native Americans and Native Alaskans (221.2/100,000) and significantly higher than that of white Americans (40.1/100,000) [3–6]. The racial disparity seen with COVID-19 rates has been associated with differences in household size, social distancing, community education, and ability to work from home which some communities of color do not have [7, 8]. These social issues and healthcare disparities have been apparent in the past but have been further amplified by COVID-19 [7, 9]. In addition to social factors, studies have also shown that AA have high frequencies of hypertension, diabetes, chronic kidney disease, and obesity, factors associated with poor outcomes from COVID-19 [10–13].
There are limited data assessing racial differences in clinical outcomes of critically ill COVID-19 patients. Cohort studies in Louisiana and Georgia found that race was not associated with hospital mortality after adjusting for differences in sociodemographic and clinical characteristics [6, 14]. The objective of our study was to evaluate whether racial differences impact the frequency of in-hospital complications and overall mortality of critically ill patients in a racially diverse cohort.
Methods
This observational cohort study includes data from hospitalized COVID-19 patients admitted from March 6, 2020, to May 5, 2020, who were admitted to Emory Healthcare, an academic healthcare system in Atlanta, Georgia. Patients 18 years or older that were hospitalized in the ICU were eligible for inclusion once positive COVID-19 status was confirmed based on a severe acute respiratory syndrome coronavirus 2 polymerase chain reaction assay. Other COVID-19-positive patients who did not reach ICU level of care needs were excluded. Patient data was obtained from the electronic medical record (EMR) (Cerner Millennium EMR, Kansas City, MO, USA) using proprietary data collection software internally developed on the Oracle Apex platform (Redwood City, CA, USA). Categorical and continuous data elements were automatically extracted using an internally validated technique from the Cerner Millennium EMR through the Apex platform. Data elements contained in free text were manually abstracted by members of the Emory COVID-19 Quality and Clinical Research Collaborative (QCRC) and entered into the Apex platform [15]. The variables that were investigated included data on demographics, medical comorbidities, hospitalization, and outcomes. For analysis, data from the Apex environment were merged with data directly extracted from the Millennium platform to create a comprehensive dataset of all investigated variables.
Data were collected through June 9, 2020, and analyzed using a chi-square or independent sample t tests for categorical and continuous variables, respectively, with a two-sided P value of less than 0.05 considered statistically significant. Univariate analysis and multivariate analysis were done on all categorical and continuous variables on the outcome of mortality. Significance for univariate analysis was set at a P value of less than 0.1 and for multivariate analysis significance was set at a P value of less than 0.05. All statistical analysis was SPSS version 25 (IBM Corporation, Armonk, New York). This study was approved by the Emory University Institutional Review Board.
Results
During the study period, 288 patients were admitted to the ICU with a diagnosis of COVID-19. The mean age was 63 (± 16) years, 131 (45%) were female, 209 (73%) were AA, 68 (24%) were white, 10 (3.4%) were Asian, and 1 (0.3%) was multiple race. Compared with non-AA, AAs had significantly higher rates of hypertension (80% vs 59%, P = 0.001) and diabetes (49% vs 34%, P = 0.026) and a higher mean BMI (33 vs 28, P < 0.001) (Table 1). There were no differences between races in history of coronary artery disease, stroke, chronic kidney disease, chronic obstructive pulmonary disease, asthma, obstructive sleep apnea, HIV, or other immunocompromised state.
Table 1.
Comorbidities in ICU hospitalized patients by race
| Admission characteristics | Total (n = 288) | AA (n = 209) | Other (n = 79) | P value |
|---|---|---|---|---|
| Age, SD | 63 (16) | 62 (15) | 65 (18) | 0.269 |
| Female, n (%) | 131 (45) | 95 (45) | 36 (46) | 0.986 |
| HTN, n (%) | 214 (74) | 167 (80) | 47 (59) | < 0.001 |
| DM, n (%) | 129 (45) | 102 (49) | 27 (34) | 0.026 |
| BMI (n = 285), mean (SD) | 32 (8) | 33 (9) | 28 (6) | < 0.001 |
| CAD, n (%) | 40 (14) | 25 (12) | 15 (19) | 0.124 |
| Stroke, n (%) | 39 (14) | 26 (12) | 13 (16) | 0.374 |
| CKD, n (%) | 43 (15) | 34 (16) | 9 (11) | 0.300 |
| COPD, n (%) | 19 (7) | 12 (6) | 7 (9) | 0.341 |
| Asthma, n (%) | 28 (10) | 17 (8) | 11 (14) | 0.139 |
| OSA, n (%) | 24 (8) | 18 (9) | 6 (8) | 0.780 |
| HIV, n (%) | 5 (2) | 5 (2) | 0 (0) | 0.328 |
| Other immunocompromised state, n (%) | 11 (4) | 7 (3) | 4 (5) | 0.501 |
HTN hypertension, DM diabetes mellitus, BMI body mass index, CAD coronary artery disease, CKD chronic kidney disease, COPD chronic obstructive pulmonary disease, OSA obstructive sleep apnea, HIV human immunodeficiency virus
Mean hospital length of stay was 18 (± 12) days, and ICU length of stay was 11 (± 9) days. Overall, 212 (74%) patients were intubated for a mean of 11 (± 8) days; 66 (23%) patients required continuous renal replacement therapy (CRRT) for a mean of 9 (± 6) days. There were 82 (29%) patients who died. There was no significant difference in length of stay, intubation rates, length of intubation, and deaths between AAs and non-AA patients (Table 2). CRRT was more frequently required in AA patients (27% vs 13%, P = 0.011), whereas intermittent hemodialysis rates were similar (15% vs 9%, P = 0.153).
Table 2.
Clinical outcomes in ICU patients by race
| Hospitalization data and outcome | Total (n = 288) | AA (n = 209) | Other (n = 79) | P value |
|---|---|---|---|---|
| Hospitalization duration, mean days (SD) | 18 (12) | 18 (12) | 19 (12) | 0.700 |
| ICU length, mean days (SD) | 11 (9) | 10 (8) | 11 (9) | 0.330 |
| Intubated, n (%) | 212 (74) | 155 (74) | 57 (72) | 0.730 |
| Intubation length, mean days (SD) | 11 (8) | 11 (8) | 11 (9) | 0.952 |
| CRRT, n (%) | 66 (23) | 56 (27) | 10 (13) | 0.011 |
| CRRT length, mean days (SD) | 9 (6) | 9 (6) | 9 (7) | 0.937 |
| HD, n (%) | 39 (14) | 32 (15) | 7 (9) | 0.153 |
| HD length, mean days (SD) | 7 (5) | 7 (5) | 6 (6) | 0.727 |
| SOFA, mean (SD) | 6 (4) | 6 (4) | 7 (4) | 0.215 |
| Death, n (%) | 82 (29) | 63 (30) | 19 (24) | 0.307 |
ICU intensive care unit, CRRT continuous renal replacement therapies, HD hemodialysis, SOFA sequential organ failure assessment
In univariable analysis, factors associated with in-hospital mortality included age (OR: 1.058, 95% CI: 1.036–1.080, P value: < 0.001), hypertension (OR: 1.793, 95% CI: 0.949–3.387, P value: 0.072), coronary artery disease (OR: 2.081, 95% CI: 1.046–4.140, P value: 0.037), hospital length of stay (LOS) (OR: 0.918 95% CI: 0.888–0.948, P value: < 0.001), ICU LOS (OR: 0.872, 95% CI: 0.941–1.004, P value: 0.087), intubation rate (OR: 2.091, 95% CI: 1.094–3.997, P value: 0.026), CRRT use (OR: 4.591, 95% CI: 2.563–8.226, P value: < 0.001), and BMI (OR: 0.909, 95% CI: 0.871–0.949, P value: < 0.001), but not race (Table 3). In multivariable analysis, age (OR: 1.094, 95% CI: 1.056–1.134, P value: < 0.001), hospital duration (OR: 0.760, 95% CI: 0.697–0.828, P value: < 0.001), ICU length of stay (OR: 1.148, 95% CI: 1.044–1.262, P value: 0.004), intubation rate (OR: 4.824, 95% CI: 1.545–15.062, P value: 0.007), CRRT use (OR: 20.806, 95% CI: 6.874–62.981, P value: < 0.001), and BMI (OR: 0.886, 95% CI: 0.825–0.951, P value: 0.001) were associated with in-hospital mortality (Table 4).
Table 3.
Variables associated with inpatient mortality in univariate analysis
| Variable | Odds ratio | 95% confidence interval | P value |
|---|---|---|---|
| Age | 1.058 | 1.036–1.080 | < 0.001 |
| Female | 0.914 | 0.546–1.530 | 0.733 |
| African American | 1.363 | 0.752–2.469 | 0.308 |
| HTN | 1.793 | 0.949–3.387 | 0.072 |
| DM | 1.169 | 0.700–1.953 | 0.551 |
| BMI | 0.909 | 0.871–0.949 | < 0.001 |
| CAD | 2.081 | 1.046–4.140 | 0.037 |
| Stroke | 1.491 | 0.732–3.035 | 0.271 |
| CKD | 1.607 | 0.814–3.172 | 0.171 |
| COPD | 1.509 | 0.572–3.978 | 0.406 |
| Asthma | 0.517 | 0.189–1.409 | 0.197 |
| OSA | 0.477 | 0.158–1.441 | 0.189 |
| HIV | 3.873 | 0.635–23.620 | 0.142 |
| Other immunocompromised state | 0.547 | 0.116–2.589 | 0.447 |
| Hospitalization duration | 0.918 | 0.888–0.948 | < 0.001 |
| ICU length of stay | 0.972 | 0.941–1.004 | 0.087 |
| Intubated | 2.091 | 1.094–3.997 | 0.026 |
| CRRT | 4.591 | 2.563–8.226 | < 0.001 |
| HD | 0.985 | 0.465–2.085 | 0.968 |
| SOFA | 1.042 | 0.975–1.112 | 0.224 |
Table 4.
Multivariable analysis of variables associated with in-hospital mortality
| Variable | Odds ratio | 95% confidence interval | P value |
|---|---|---|---|
| Age | 1.094 | 1.056–1.134 | < 0.001 |
| BMI | 0.886 | 0.825–0.951 | 0.001 |
| HTN | 0.859 | 0.309–2.391 | 0.771 |
| CAD | 2.486 | 0.907–6.811 | 0.077 |
| Hospital duration | 0.760 | 0.697–0.828 | < 0.001 |
| ICU length of stay | 1.148 | 1.044–1.262 | 0.004 |
| Intubation | 4.824 | 1.545–15.062 | 0.007 |
| CRRT | 20.806 | 6.874–62.981 | < 0.001 |
BMI body mass index, HTN hypertension, CAD coronary artery disease, ICU intensive care unit, CRRT continuous renal replacement therapies
Discussion
In our racially diverse cohort of critically ill COVID-19 patients including 73% AAs, we found that intubation rate and in-hospital mortality were similar between AA and non-AA patients. This was found despite AAs having higher rates of comorbidities including hypertension, diabetes, and obesity compared to non-AAs. AAs did have higher rates of CRRT than non-AAs despite having similar rates of chronic kidney disease history on admission. The prevalence of these comorbidities observed in AA vs non-AA has been reported previously and increases the complication rates in patients infected with COVID-19 [10–13, 16, 17]. These results are similar to those of a cohort study in Louisiana, which found similar in-hospital mortality rates between AAs and non-AAs despite AAs having higher rates of acute renal failure [6]. In another cohort study from Georgia which included ICU and non-ICU patients, AA patients were found to have similar rates of invasive mechanical ventilation and death compared to non-AA patients [13].
Though COVID-19 proved to be challenging to all hospital systems, Atlanta did not observe the overwhelming case numbers early in the pandemic as some other major cities [1]. Our study was limited to metropolitan Atlanta hospitals within one academic health system in Georgia and may have limited generalizability to other healthcare settings. However, our study represents a large cohort of critically ill COVID-19 patients including a large proportion of AA patients. Additionally, this study is limited by being a retrospective analysis of an ICU-specific cohort that does not compare mortality rates outside of an ICU setting. Despite these limitations, our study shows similar in-hospital mortality rates between AAs and other races despite AAs having higher rates of comorbidities at admission and higher rates of RRT in the hospital. Whether these findings are due to pre-hospital social factors [4], differences in the disease manifestation or differences in provider treatments require further study.
Conclusion
Despite critically ill AA with COVID-19 presenting with higher rates of comorbidities compared to other races, rates of intubation and mortality were similar at an academic healthcare system in Atlanta, Georgia. Our findings show that in a healthcare system that has adequate critical care capacity to provide treatment to the sickest of COVID-19 patients, we were able to limit disparities in mortality despite the social factors that contribute to AAs presenting with higher rates of comorbid illnesses on admission.
Supplementary Information
(DOCX 31 kb)
Funding
This study was supported by Grant K23 AL134182 from the National Institute of Health/National Institute of Allergy and Infectious Disease. Sara C. Auld MD, MSc.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.center JHUaMCVR. COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). 2020.
- 2.Zhang B, Zhou X, Qiu Y, Song Y, Feng F, Feng J, Song Q, Jia Q, Wang J. Clinical characteristics of 82 cases of death from COVID-19. PLoS One. 2020;15(7):e0235458. doi: 10.1371/journal.pone.0235458. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.CenterOfDiseaseControl. Racial & Ethnic Minority Groups 2020; https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/racial-ethnic-minorities.html.
- 4.Cowger TL, Davis BA, Etkins OS, Makofane K, Lawrence JA, Bassett MT, Krieger N. Comparison of weighted and unweighted population data to assess inequities in coronavirus disease 2019 deaths by race/ethnicity reported by the US Centers for Disease Control and Prevention. JAMA Netw Open. 2020;3(7):e2016933. doi: 10.1001/jamanetworkopen.2020.16933. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Millett GA, Jones AT, Benkeser D, Baral S, Mercer L, Beyrer C, Honermann B, Lankiewicz E, Mena L, Crowley JS, Sherwood J, Sullivan PS. Assessing differential impacts of COVID-19 on black communities. Ann Epidemiol. 2020;47:37–44. doi: 10.1016/j.annepidem.2020.05.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.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. 2020;382(26):2534–2543. doi: 10.1056/NEJMsa2011686. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Yancy CW. COVID-19 and African Americans. JAMA. 2020;323(19):1891–1892. doi: 10.1001/jama.2020.6548. [DOI] [PubMed] [Google Scholar]
- 8.Duffin E. Race and ethnicity of U.S. households in 2015, by size. Statista. 2020.
- 9.Gold JAW, Rossen LM, Ahmad FB, Sutton P, Li Z, Salvatore PP, Coyle JP, DeCuir J, Baack BN, Durant TM, Dominguez KL, Henley SJ, Annor FB, Fuld J, Dee DL, Bhattarai A, Jackson BR. Race, ethnicity, and age trends in persons who died from COVID-19 - United States, may-august 2020. MMWR Morb Mortal Wkly Rep. 2020;69(42):1517–1521. doi: 10.15585/mmwr.mm6942e1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.CenterOfDiseaseControl. African American Health 2017.
- 11.Cooper RS. Genetic factors in ethnic disparities in health. National Research Council (US) Panel on Race, Ethnicity, and Health in Later Life. 2004;8.
- 12.Health NIo. Why are some genetic conditions more common in particular ethnic groups? . Genetic Home refrence.
- 13.Palmer ND, McDonough CW, Hicks PJ, Roh BH, Wing MR, An SS, Hester JM, Cooke JN, Bostrom MA, Rudock ME, Talbert ME, Lewis JP, DIAGRAM Consortium. MAGIC Investigators. Ferrara A, Lu L, Ziegler JT, Sale MM, Divers J, Shriner D, Adeyemo A, Rotimi CN, Ng MC, Langefeld CD, Freedman BI, Bowden DW, Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP, Zeggini E, Huth C, Aulchenko YS, Thorleifsson G, McCulloch L, Ferreira T, Grallert H, Amin N, Wu G, Willer CJ, Raychaudhuri S, McCarroll S, Langenberg C, Hofmann OM, Dupuis J, Qi L, Segrè AV, van Hoek M, Navarro P, Ardlie K, Balkau B, Benediktsson R, Bennett AJ, Blagieva R, Boerwinkle E, Bonnycastle LL, Boström KB, Bravenboer B, Bumpstead S, Burtt NP, Charpentier G, Chines PS, Cornelis M, Couper DJ, Crawford G, Doney AS, Elliott KS, Elliott AL, Erdos MR, Fox CS, Franklin CS, Ganser M, Gieger C, Grarup N, Green T, Griffin S, Groves CJ, Guiducci C, Hadjadj S, Hassanali N, Herder C, Isomaa B, Jackson AU, Johnson PR, Jørgensen T, Kao WH, Klopp N, Kong A, Kraft P, Kuusisto J, Lauritzen T, Li M, Lieverse A, Lindgren CM, Lyssenko V, Marre M, Meitinger T, Midthjell K, Morken MA, Narisu N, Nilsson P, Owen KR, Payne F, Perry JR, Petersen AK, Platou C, Proença C, Prokopenko I, Rathmann W, Rayner NW, Robertson NR, Rocheleau G, Roden M, Sampson MJ, Saxena R, Shields BM, Shrader P, Sigurdsson G, Sparsø T, Strassburger K, Stringham HM, Sun Q, Swift AJ, Thorand B, Tichet J, Tuomi T, van Dam R, van Haeften T, van Herpt T, van Vliet-Ostaptchouk J, Walters GB, Weedon MN, Wijmenga C, Witteman J, Bergman RN, Cauchi S, Collins FS, Gloyn AL, Gyllensten U, Hansen T, Hide WA, Hitman GA, Hofman A, Hunter DJ, Hveem K, Laakso M, Mohlke KL, Morris AD, Palmer CN, Pramstaller PP, Rudan I, Sijbrands E, Stein LD, Tuomilehto J, Uitterlinden A, Walker M, Wareham NJ, Watanabe RM, Abecasis GR, Boehm BO, Campbell H, Daly MJ, Hattersley AT, Hu FB, Meigs JB, Pankow JS, Pedersen O, Wichmann HE, Barroso I, Florez JC, Frayling TM, Groop L, Sladek R, Thorsteinsdottir U, Wilson JF, Illig T, Froguel P, van Duijn C, Stefansson K, Altshuler D, Boehnke M, McCarthy M, Soranzo N, Wheeler E, Glazer NL, Bouatia-Naji N, Mägi R, Randall J, Johnson T, Elliott P, Rybin D, Henneman P, Dehghan A, Hottenga JJ, Song K, Goel A, Egan JM, Lajunen T, Doney A, Kanoni S, Cavalcanti-Proença C, Kumari M, Timpson NJ, Zabena C, Ingelsson E, An P, O'Connell J, Luan J, Elliott A, McCarroll S, Roccasecca RM, Pattou F, Sethupathy P, Ariyurek Y, Barter P, Beilby JP, Ben-Shlomo Y, Bergmann S, Bochud M, Bonnefond A, Borch-Johnsen K, Böttcher Y, Brunner E, Bumpstead SJ, Chen YD, Chines P, Clarke R, Coin LJ, Cooper MN, Crisponi L, Day IN, de Geus EJ, Delplanque J, Fedson AC, Fischer-Rosinsky A, Forouhi NG, Frants R, Franzosi MG, Galan P, Goodarzi MO, Graessler J, Grundy S, Gwilliam R, Hallmans G, Hammond N, Han X, Hartikainen AL, Hayward C, Heath SC, Hercberg S, Hicks AA, Hillman DR, Hingorani AD, Hui J, Hung J, Jula A, Kaakinen M, Kaprio J, Kesaniemi YA, Kivimaki M, Knight B, Koskinen S, Kovacs P, Kyvik KO, Lathrop GM, Lawlor DA, le Bacquer O, Lecoeur C, Li Y, Mahley R, Mangino M, Manning AK, Martínez-Larrad MT, McAteer J, McPherson R, Meisinger C, Melzer D, Meyre D, Mitchell BD, Mukherjee S, Naitza S, Neville MJ, Oostra BA, Orrù M, Pakyz R, Paolisso G, Pattaro C, Pearson D, Peden JF, Pedersen NL, Perola M, Pfeiffer AF, Pichler I, Polasek O, Posthuma D, Potter SC, Pouta A, Province MA, Psaty BM, Rayner NW, Rice K, Ripatti S, Rivadeneira F, Rolandsson O, Sandbaek A, Sandhu M, Sanna S, Sayer AA, Scheet P, Seedorf U, Sharp SJ, Shields B, Sijbrands EJ, Silveira A, Simpson L, Singleton A, Smith NL, Sovio U, Swift A, Syddall H, Syvänen AC, Tanaka T, Tönjes A, Uitterlinden AG, van Dijk K, Varma D, Visvikis-Siest S, Vitart V, Vogelzangs N, Waeber G, Wagner PJ, Walley A, Ward KL, Watkins H, Wild SH, Willemsen G, Witteman JC, Yarnell JW, Zelenika D, Zethelius B, Zhai G, Zhao JH, Zillikens MC, Borecki IB, Loos RJ, Meneton P, Magnusson PK, Nathan DM, Williams GH, Silander K, Salomaa V, Smith GD, Bornstein SR, Schwarz P, Spranger J, Karpe F, Shuldiner AR, Cooper C, Dedoussis GV, Serrano-Ríos M, Lind L, Palmer LJ, Franks PW, Ebrahim S, Marmot M, Kao WH, Pramstaller PP, Wright AF, Stumvoll M, Hamsten A, Buchanan TA, Valle TT, Rotter JI, Siscovick DS, Penninx BW, Boomsma DI, Deloukas P, Spector TD, Ferrucci L, Cao A, Scuteri A, Schlessinger D, Uda M, Ruokonen A, Jarvelin MR, Waterworth DM, Vollenweider P, Peltonen L, Mooser V, Sladek R. A genome-wide association search for type 2 diabetes genes in African Americans. PLoS One. 2012;7(1):e29202. doi: 10.1371/journal.pone.0029202. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Gold JAW, Wong KK, Szablewski CM, Patel PR, Rossow J, da Silva J, Natarajan P, Morris SB, Fanfair RN, Rogers-Brown J, Bruce BB, Browning SD, Hernandez-Romieu AC, Furukawa NW, Kang M, Evans ME, Oosmanally N, Tobin-D’Angelo M, Drenzek C, Murphy DJ, Hollberg J, Blum JM, Jansen R, Wright DW, Sewell WM, III, Owens JD, Lefkove B, Brown FW, Burton DC, Uyeki TM, Bialek SR, Jackson BR. Characteristics and clinical outcomes of adult patients hospitalized with COVID-19 - Georgia, march 2020. MMWR Morb Mortal Wkly Rep. 2020;69(18):545–550. doi: 10.15585/mmwr.mm6918e1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Auld S, Caridi-Scheible M, Blum JM, et al. ICU and ventilator mortality among critically ill adults with COVID-19. Society of Critical Care Medicine. 2020.
- 16.Guan WJ, Liang WH, Zhao Y, et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J. 2020;55(5). [DOI] [PMC free article] [PubMed]
- 17.Sanyaolu A, Okorie C, Marinkovic A, et al. Comorbidity and its impact on patients with COVID-19. SN Compr Clin Med. 2020:1–8. [DOI] [PMC free article] [PubMed]
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Supplementary Materials
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