Clinical characteristics and predictors of mortality in African-Americans with COVID-19 from an inner-city community teaching hospital in New York

Abstract

There is limited data on the clinical presentation and predictors of mortality in the African-American (AA) patients hospitalized with coronavirus disease 2019 (COVID-19) despite the disproportionately higher burden and mortality. The aim of this study is to report on the clinical characteristics and the predictors of mortality in hospitalized AA patients with COVID-19 infection. In this retrospective cohort review, we included all AA patients with confirmed COVID-19 infection admitted to an inner-city teaching community hospital in New York city. Demographics, clinical presentation, baseline co-morbidities, and laboratory data were compared between survivors and non-survivors. The predictors of mortality were assessed using multivariate logistic regression analysis. Of the 408 (median age, 67 years) patients included, 276 (66.65%, median age 63 years) survived while 132 (33.35%, median age 71 years) died. The most common presenting symptoms were cough, myalgia, fever/chills, shortness of breath, and gastrointestinal symptoms (nausea, vomiting, diarrhea, and abdominal pain), with a prevalence of 62.50%, 43.87%, 53.68%, and 27.21%, respectively. Age (odds ratio [OR], 1.06; confidence interval [CI], 1.04-1.08; P < .001), body mass index (OR, 1.07; CI, 1.04-1.11; P < .001), elevated serum ferritin (OR, 1.99; CI, 1.08-3.66; P < .02), C-reactive protein (OR, 2.42; CI, 1.36-4.33; P < .01), and D-dimers (OR, 3.79; CI, 2.21-6.50; P < .001) at the time of presentation were identified as the independent predictors of mortality. Cough, shortness of breath, fever/chills, gastrointestinal symptoms, and myalgia were the predominant presentation among AAs hospitalized with COVID-19 infection. Advanced age, higher body mass index, elevated serum ferritin, C-reactive protein, and D-dimers are independent predictors of mortality among hospitalized AAs with COVID-19 infection.

Keywords: blood; coronavirus; pandemics.

Figure 1

Forest plot showing predictors of mortality. Age, body mass index, and oxygen saturations are modeled as continuous variables and odds ratio (OR) represent the odds of dying for every unit increase in respective parameter. Shortness of breath and myalgia are modeled as continuous variables. OR represent the odds of dying in those who had the respective symptom compared with those who did not. All other variables were transformed from continuous to categorical and modeled as categorical variables. OR represents odds of dying in those with values in the fourth quartile compared with those in lower quartiles (first, second, and third quartiles). CI, confidence interval