ABSTRACT
BACKGROUND: US racial and ethnic minorities have well-established elevated rates of comorbidities, which, compounded with healthcare access inequity, often lead to worse health outcomes. In the current COVID-19 pandemic, it is important to understand existing disparities in minority groups' critical care outcomes and mechanisms behind these-topics that have yet to be well-explored. OBJECTIVE: Assess for disparities in racial and ethnic minority groups' COVID-19 critical care outcomes. DESIGN: Retrospective cohort study. PARTICIPANTS: A total of 2125 adult patients who tested positive for COVID-19 via RT-PCR between March and December 2020 and required ICU admission at the Cleveland Clinic Hospital Systems were included. MAIN MEASURES: Primary outcomes were mortality and hospital length of stay. Cohort-wide analysis and subgroup analyses by pandemic wave were performed. Multivariable logistic regression models were built to study the associations between mortality and covariates. KEY RESULTS: While crude mortality was increased in White as compared to Black patients (37.5% vs. 30.5%, respectively; p = 0.002), no significant differences were appraised after adjustment or across pandemic waves. Although median hospital length of stay was comparable between these groups, ICU stay was significantly different (4.4 vs. 3.4, p = 0.003). Mortality and median hospital and ICU length of stay did not differ significantly between Hispanic and non-Hispanic patients. Neither race nor ethnicity was associated with mortality due to COVID-19, although APACHE score, CKD, malignant neoplasms, antibiotic use, vasopressor requirement, and age were. CONCLUSIONS: We found no significant differences in mortality or hospital length of stay between different races and ethnicities. In a pandemic-influenced critical care setting that operated outside conditions of ICU strain and implemented standardized protocol enabling equitable resource distribution, disparities in outcomes often seen among racial and ethnic minority groups were successfully mitigated.
ABSTRACT
The propensity score for each individual is the predicted probability of receiving influenza vaccination from a nonparsimonious logistic regression model using the covariates listed as clinical characteristics in Table 1. Clinical characteristics and outcome of all individuals in the cohort and in the subgroup of patients tested positive for SARS-CoV-2 All tested individuals SARS-CoV-2-positive Never vaccinated Vaccinated in 2019 p Never vaccinated Vaccinated in 2019 p Clinical characteristics (n = 9082) (n = 4138) (n = 1125) (n = 309) Age – year 49.3 [34.6, 62.9] 61.5 [46.9, 72.0] <0.001 52.7 [38.6, 64.1] 63.3 [49.2, 73.4] <0.001 Race – no (%) <0.001 <0.001 White 5985 (65.9) 3050 (73.7) 686 (61.0) 203 (65.7) Black 1695 (18.7) 833 (20.1) 246 (21.9) 91 (29.4) Other 1402 (15.4) 255 (6.2) 193 (17.2) 15 (4.9) Male sex – no (%) 4050 (44.6) 1651 (39.9) <0.001 593 (52.7) 152 (49.2) 0.30 Non-Hispanic ethnicity – no (%) 7986 (87.9) 3974 (96.0) <0.001 893 (79.4) 298 (96.4) <0.001 BMI – kg/m2 28.6 [24.4, 33.6] 29.0 [24.8, 34.9] 0.002 29.7 [26.1, 34.0] 30.0 [25.0, 35.5] 0.66 Smoking – no (%) <0.001 <0.001 Current smoker 1481 (16.3) 504 (12.2) 64 (5.7) 15 (4.9) Former smoker 1625 (17.9) 1684 (40.7) 178 (15.8) 123 (39.8) Nonsmoker 5976 (65.8) 1950 (47.1) 883 (78.5) 171 (55.3) Median annual income – USD 57,250.0 [42,500.9–74,812.2] 59,390.0 [41,635.0–79,201.0] 0.005 58,429.0 [45,161.0–76,719.0] 60,000.0 [43,097.0–81,953.0] 0.91 Exposure to COVID-19 – no (%) 4805 (52.9) 1923 (46.5) <0.001 825 (73.3) 203 (65.7) 0.01 Family history of COVID-19 – no (%) 4452 (49.0) 1849 (44.7) <0.001 795 (70.7) 205 (66.3) 0.16 Coexisting conditions – no (%) COPD 517 (5.7) 689 (16.7) <0.001 39 (3.5) 40 (12.9) <0.001 Asthma 1433 (15.8) 1195 (28.9) <0.001 121 (10.8) 66 (21.4) <0.001 Diabetes 1288 (14.2) 1493 (36.1) <0.001 177 (15.7) 111 (35.9) <0.001 Hypertension 2885 (31.8) 2677 (64.7) <0.001 387 (34.4) 205 (66.3) <0.001 Coronary artery disease 673 (7.4) 998 (24.1) <0.001 71 (6.3) 57 (18.4) <0.001 Congestive heart failure 551 (6.1) 880 (21.3) <0.001 49 (4.4) 61 (19.7) <0.001 Cancer 848 (9.3) 1149 (27.8) <0.001 72 (6.4) 71 (23.0) <0.001 Connective tissue disease 795 (8.8) 1003 (24.2) <0.001 69 (6.1) 46 (14.9) <0.001 Long-term medications – no (%) NSAIDs 1659 (18.3) 1459 (35.3) <0.001 189 (16.8) 108 (35.0) <0.001 Glucocorticoids 1066 (11.7) 1350 (32.6) <0.001 67 (6.0) 66 (21.4) <0.001 ACE inhibitors 512 (5.6) 565 (13.7) <0.001 74 (6.6) 52 (16.8) <0.001 ARB 374 (4.1) 439 (10.6) <0.001 70 (6.2) 41 (13.3) <0.001 Laboratory measurements Platelet count – (x 109/L) 239.0 [188.0, 298.0] 233.0 [176.0, 301.0] 0.005 198.0 [160.0, 250.0] 196.0 [157.0, 251.5] 0.66 Eosinophil count – (cells/μL) 70.0 [30.0, 170.0] 80.0 [30.0, 190.0] 0.001 30.0 [30.0, 30.0] 30.0 [30.0, 30.0] 0.55 Lymphocyte count – (109/μL) 1.4 [0.9, 2.1] 1.2 [0.8, 1.9] <0.001 1.1 [0.7, 1.5] 0.9 [0.6, 1.3] 0.011 Neutrophil count – (109/μL) 5.6 [3.7, 8.7] 5.9 [3.9, 8.9] 0.086 3.9 [2.9, 5.5] 4.1 [2.8, 6.5] 0.33 Hemoglobin – (g/dL) 13.2 [11.5, 14.6] 12.2 [10.0, 13.9] <0.001 13.6 [12.1, 14.9] 13.30 [11.7, 14.6] 0.07 Albumin – (g/dL) 4.00 [3.50, 4.35] 3.80 [3.40, 4.20] <0.001 3.80 [3.52, 4.10] 3.70 [3.40, 4.00] 0.10 Total bilirubin – (mg/dL) 0.4 [0.3, 0.7] 0.5 [0.3, 0.7] 0.277 0.4 [0.3, 0.6] 0.4 [0.3, 0.7] 0.07 ALT – (IU/L) 21.0 [14.0, 34.0] 19.0 [13.0, 30.00] <0.001 26.0 [17.0, 40.0] 22.0 [15.0, 37.8] 0.23 Creatinine – (mg/dL) 0.90 [0.73, 1.15] 0.99 [0.76, 1.41] <0.001 0.97 [0.80, 1.22] 1.09 [0.82, 1.42] 0.04 Outcome – no (%) Positive SARS-CoV-2 test 1125 (12.4) 309 (7.5) <0.001 Hospitalization 192 (17.1) 127 (41.1) <0.001 ICU admission 77 (6.8) 43 (13.9) <0.001 Hospital mortality 32 (2.8) 20 (6.5) 0.01 Continuous data are presented as median [IQR]. BMI stands for body mass index;USD for US dollar;COPD for chronic obstructive pulmonary disease;NSAIDS for nonsteroidal anti-inflammatory drugs;ACE for angiotensin-converting enzyme;ARB for angiotensin receptor blocker;and ICU for Intensive Care Unit. The effect of influenza vaccines, and adjuvanted vaccin s in particular, on Th17 immune responses in coronavirus immunopathology and on vaccine-induced immune enhancement [5] is unknown and needs to be closely monitored.