Dataset Information

Racial Differences and In-Hospital Outcomes Among Hospitalized Patients with COVID-19.

ABSTRACT: There is a paucity of data on how race affects the clinical presentation and short-term outcome among hospitalized patients with SARS-CoV-2, the 2019 coronavirus (COVID-19). Hospitalized patients ≥ 18 years, testing positive for COVID-19 from March 13, 2020 to May 13, 2020 in a United States (U.S.) integrated healthcare system with multiple facilities in two states were evaluated. We documented racial differences in clinical presentation, disposition, and in-hospital outcomes for hospitalized patients with COIVD-19. Multivariable regression analysis was utilized to evaluate independent predictors of outcomes by race. During the study period, 3678 patients tested positive for COVID-19, among which 866 were hospitalized (55.4% self-identified as Caucasian, 29.5% as Black, 3.3% as Hispanics, and 4.7% as other racial groups). Hospitalization rates were highest for Black patients (36.6%), followed by other (28.3%), Caucasian patients (24.4%), then Hispanic patients (10.7%) (p < 0.001). Caucasian patients were older, and with more comorbidities. Absolute lymphocyte count was lowest among Caucasian patients. Multivariable regression analysis revealed that compared to Caucasians, there was no significant difference in in-hospital mortality among Black patients (adjusted odds ratio [OR] 0.53; 95% confidence interval [CI] 0.26-1.09; p = 0.08) or other races (adjusted OR 1.62; 95% CI 0.80-3.27; p = 0.18). Black and Hispanic patients were admitted less frequently to the intensive care unit (ICU), and Black patients were less likely to require pressor support or hemodialysis (HD) compared with Caucasians. This observational analysis of a large integrated healthcare system early in the pandemic revealed that patients with COVID-19 did exhibit some racial variations in clinical presentation, laboratory data, and requirements for advanced monitoring and cardiopulmonary support, but these nuances did not dramatically alter in-hospital outcomes.

SUBMITTER: Elbadawi A

PROVIDER: S-EPMC8432274 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background: The COVID-19 pandemic has exposed longstanding racial/ethnic inequities in health risks and outcomes in the U.S.. We sought to identify racial/ethnic differences in presentation and outcomes for patients hospitalized with COVID-19. Methods: The American Heart Association COVID-19 Cardiovascular Disease Registry is a retrospective observational registry capturing consecutive patients hospitalized with COVID-19. We present data on the first 7,868 patients by race/ethnicity treated at 88 hospitals across the US between 01/17/2020 and 7/22/2020. The primary outcome was in-hospital mortality; secondary outcomes included major adverse cardiovascular events (MACE: death, myocardial infarction, stroke, heart failure) and COVID-19 cardiorespiratory ordinal severity score (worst to best: death, cardiac arrest, mechanical ventilation with mechanical circulatory support, mechanical ventilation with vasopressors/inotrope support, mechanical ventilation without hemodynamic support, and hospitalization without any of the above). Multivariable logistic regression analyses were performed to assess the relationship between race/ethnicity and each outcome adjusting for differences in sociodemographic, clinical, and presentation features, and accounting for clustering by hospital. Results: Among 7,868 patients hospitalized with COVID-19, 33.0% were Hispanic, 25.5% were non-Hispanic Black, 6.3% were Asian, and 35.2% were non-Hispanic White. Hispanic and Black patients were younger than non-Hispanic White and Asian patients and were more likely to be uninsured. Black patients had the highest prevalence of obesity, hypertension, and diabetes. Black patients also had the highest rates of mechanical ventilation (23.2%) and renal replacement therapy (6.6%) but the lowest rates of remdesivir use (6.1%). Overall mortality was 18.4% with 53% of all deaths occurring in Black and Hispanic patients. The adjusted odds ratios (ORs) for mortality were 0.93 (95% confidence interval [CI] 0.76-1.14) for Black patients, 0.90 (95% CI 0.73-1.11) for Hispanic patients, and 1.31 (95% CI 0.96-1.80) for Asian patients compared with non-Hispanic White patients. The median OR across hospitals was 1.99 (95% CI 1.74-2.48). Results were similar for MACE. Asian patients had the highest COVID-19 cardiorespiratory severity at presentation (adjusted OR 1.48, 95% CI 1.16-1.90). Conclusions: Although in-hospital mortality and MACE did not differ by race/ethnicity after adjustment, Black and Hispanic patients bore a greater burden of mortality and morbidity due to their disproportionate representation among COVID-19 hospitalizations.

Project description:IntroductionCardiovascular comorbidities may predispose to adverse outcomes in hospitalized patients with coronavirus disease 2019 (COVID-19). However, across the USA, the burden of cardiovascular comorbidities varies significantly. Whether clinical outcomes of hospitalized patients with COVID-19 differ between regions has not yet been studied systematically. Here, we report differences in underlying cardiovascular comorbidities and clinical outcomes of patients hospitalized with COVID-19 in Texas and in New York state.MethodsWe established a multicenter retrospective registry including patients hospitalized with COVID-19 between March 15 and July 12, 2020. Demographic and clinical data were manually retrieved from electronic medical records. We focused on the following outcomes: mortality, need for pharmacologic circulatory support, need for mechanical ventilation, and need for hemodialysis. Univariate and multivariate logistic regression analyses were performed.ResultsPatients in the Texas cohort (n = 296) were younger (57 vs. 63 years, p value <0.001), they had a higher BMI (30.3 kg/m2 vs. 28.5 kg/m2, p = 0.015), and they had higher rates of diabetes mellitus (41 vs. 30%; p = 0.014). In contrast, patients in the New York state cohort (n = 218) had higher rates of coronary artery disease (19 vs. 10%, p = 0.005) and atrial fibrillation (11 vs. 5%, p = 0.012). Pharmacologic circulatory support, mechanical ventilation, and hemodialysis were more frequent in the Texas cohort (21 vs. 13%, p = 0.020; 30 vs. 12%, p < 0.001; and 11 vs. 5%, p = 0.009, respectively). In-hospital mortality was similar between the 2 cohorts (16 vs. 18%, p = 0.469). After adjusting for differences in underlying comorbidities, only the use of mechanical ventilation remained significantly higher in the participating Texas hospitals (odds ratios [95% CI]: 3.88 [1.23, 12.24]). Median time to pharmacologic circulatory support was 8 days (interquartile range: 2, 13.8) in the Texas cohort compared to 1 day (0, 3) in the New York state cohort, while median time to in-hospital mortality was 16 days (10, 25.5) and 7 days (4, 14), respectively (both p < 0.001). In-hospital mortality was higher in the late versus the early study phase in the New York state cohort (24 vs. 14%, p = 0.050), while it was similar between the 2 phases in the Texas cohort (16 vs. 15%, p = 0.741).ConclusionsGeographical differences, including practice pattern variations and the impact of disease burden on provision of health care, are important for the evaluation of COVID-19 outcomes. Unadjusted data may cause bias affecting future regulatory policies and proper allocation of resources.

Project description:BackgroundThe evolution of patients hospitalized with coronavirus disease 2019 (COVID-19) is still hard to predict, even after several months of dealing with the pandemic.AimsTo develop and validate a score to predict outcomes in patients hospitalized with COVID-19.MethodsAll consecutive adults hospitalized for COVID-19 from February to April 2020 were included in a nationwide observational study. Primary composite outcome was transfer to an intensive care unit from an emergency department or conventional ward, or in-hospital death. A score that estimates the risk of experiencing the primary outcome was constructed from a derivation cohort using stacked LASSO (Least Absolute Shrinkage and Selection Operator), and was tested in a validation cohort.ResultsAmong 2873 patients analysed (57.9% men; 66.6±17.0 years), the primary outcome occurred in 838 (29.2%) patients: 551 (19.2%) were transferred to an intensive care unit; and 287 (10.0%) died in-hospital without transfer to an intensive care unit. Using stacked LASSO, we identified 11 variables independently associated with the primary outcome in multivariable analysis in the derivation cohort (n=2313), including demographics (sex), triage vitals (body temperature, dyspnoea, respiratory rate, fraction of inspired oxygen, blood oxygen saturation) and biological variables (pH, platelets, C-reactive protein, aspartate aminotransferase, estimated glomerular filtration rate). The Critical COVID-19 France (CCF) risk score was then developed, and displayed accurate calibration and discrimination in the derivation cohort, with C-statistics of 0.78 (95% confidence interval 0.75-0.80). The CCF risk score performed significantly better (i.e. higher C-statistics) than the usual critical care risk scores.ConclusionsThe CCF risk score was built using data collected routinely at hospital admission to predict outcomes in patients with COVID-19. This score holds promise to improve early triage of patients and allocation of healthcare resources.

Project description:The lack of available biomarkers for diagnosing and predicting different stages of coronavirus disease 2019 (COVID-19) is currently one of the main challenges that clinicians are facing. Recent evidence indicates that the plasma levels of specific miRNAs may be significantly modified in COVID-19 patients. Large-scale deep sequencing analysis of small RNA expression was performed on plasma samples from 40 patients hospitalized for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (between March and May 2020) (median 13.50 [IQR 9–24] days since symptoms initiation) and 21 healthy noninfected individuals. Patients were categorized as hospitalized not requiring oxygen therapy (n = 6), hospitalized requiring low-flow oxygen (n = 23), and hospitalized requiring high-flow oxygen support (n = 11). A total of 1218 different micro(mi)RNAs were identified. When compared with healthy noninfected donors, SARS-CoV-2 infected patients showed significantly (fold change [FC] >1.2 and adjusted p [padj] <0.05) altered expression of 190 miRNAs. The top 10 differentially expressed (DE) miRNAs were miR-122-5p, let-7b-5p, miR-146a-5p, miR-342-3p, miR-146b-5p, miR-629-5p, miR-24-3p, miR-12136, let-7a-5p, and miR-191-5p, which displayed FC and padj values ranging from 153 to 5 and 2.51 × 10-32 to 2.21 × 10-21, respectively, which unequivocally diagnosed SARS-CoV-2 infection. No differences in blood cell counts and biochemical plasma parameters, including interleukin 6, ferritin and D-dimer, were observed between COVID-19 patients on high-flow oxygen therapy, low-flow oxygen therapy, or not requiring oxygen therapy. Notably, 31 significantly deregulated miRNAs were found when patients on high- and low-flow oxygen therapy were compared. Similarly, 6 DE miRNAs were identified between patients on high flow and those not requiring oxygen therapy. SARS-CoV-2 infection generates a specific miRNA signature in hospitalized patients. Furthermore, specific miRNA profiles are associated with COVID-19 prognosis in severe patients.

Dataset Information

Racial Differences and In-Hospital Outcomes Among Hospitalized Patients with COVID-19.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets