Project description:ObjectivesThe coronavirus disease 2019 (COVID-19) pandemic has highlighted inequalities in access to healthcare systems, increasing racial disparities and worsening health outcomes in these populations. This study analysed the association between sociodemographic characteristics and COVID-19 in-hospital mortality in Brazil.Study designA retrospective analysis was conducted on quantitative reverse transcription polymerase chain reaction-confirmed hospitalised adult patients with COVID-19 with a defined outcome (i.e. hospital discharge or death) in Brazil. Data were retrieved from the national surveillance system database (SIVEP-Gripe) between February 16 and August 8, 2020.MethodsClinical characteristics, sociodemographic variables, use of hospital resources and outcomes of hospitalised adult patients with COVID-19, stratified by self-reported race, were investigated. The primary outcome was in-hospital mortality. The association between self-reported race and in-hospital mortality, after adjusting for clinical characteristics and comorbidities, was evaluated using a logistic regression model.ResultsDuring the study period, Brazil had 3,018,397 confirmed COVID-19 cases and 100,648 deaths. The study population included 228,196 COVID-19-positive adult in-hospital patients with a defined outcome; the median age was 61 years, 57% were men, 35% (79,914) self-reported as Black/Brown and 35.4% (80,853) self-reported as White. The total in-hospital mortality was 37% (85,171/228,196). Black/Brown patients showed higher in-hospital mortality than White patients (42% vs 37%, respectively), were admitted less frequently to the intensive care unit (ICU) (32% vs 36%, respectively) and used more invasive mechanical ventilation (21% vs 19%, respectively), especially outside the ICU (17% vs 11%, respectively). Black/Brown race was independently associated with high in-hospital mortality after adjusting for sex, age, level of education, region of residence and comorbidities (odds ratio = 1.15; 95% confidence interval = 1.09-1.22).ConclusionsAmong hospitalised Brazilian adults with COVID-19, Black/Brown patients showed higher in-hospital mortality, less frequently used hospital resources and had potentially more severe conditions than White patients. Racial disparities in health outcomes and access to health care highlight the need to actively implement strategies to reduce inequities caused by the wider health determinants, ultimately leading to a sustainable change in the health system.

Project description:BackgroundThe ongoing Coronavirus disease of 2019 (COVID-19) pandemic has hit Brazil hard in period of different dominant variants. Different COIVD-19 variants have swept through the region, resulting that the total number of cases in Brazil is the third highest in the world. This study is aimed at investigating the regional heterogeneity of in-hospital mortality of COVID-19 in Brazil and the effects of vaccination and social inequality.MethodsWe fitted a multivariate mixed-effects Cox model to a national database of inpatient data in Brazil who were admitted for COVID-19 from February 27, 2020 to March 15, 2022. The in-hospital mortality risks of vaccinated and unvaccinated patients were compared, with adjustment for age, state, ethnicity, education and comorbidities. And the effects of variables to in-hospital mortality were also compared. Stratified analysis was conducted across different age groups and vaccine types.ResultsBy fitting the multivariate mixed-effects Cox model, we concluded that age was the most important risk factor for death. With regards to educational level, illiterate patients (hazard ratio: 1.63, 95% CI: 1.56-1.70) had a higher risk than those with a university or college degree. Some common comorbidities were more dangerous for hospitalized patients, such as liver disease (HR: 1.46, 95% CI: 1.34-1.59) and immunosuppression (HR:1.32, 95% CI: 1.26-1.40). In addition, the states involving Sergipe (HR: 1.75, 95% CI: 1.46-2.11), Roraima (HR: 1.65, 95% CI: 1.43-1.92), Maranhão (HR: 1.57, 95% CI: 1.38-1.79), Acre (HR: 1.44, 95% CI: 1.12-1.86), and Rondônia (HR: 1.26, 95% CI: 1.10-1.44) in the north and the northeast region tended to have higher hazard ratios than other area. In terms of vaccine protection, vaccination did not significantly reduce mortality among hospitalized patients. Sinovac and AstraZeneca offered different protection in different regions, and no vaccine provided high protection in all regions.ConclusionThe study revealed the regional heterogeneity of in-hospital mortality of Covid-19 in Brazil and the effects of vaccination and social inequality. We found that ethnic concentrations were consistent with higher proportion of death cases relative to population size. White Brazilians had more frequent international travel opportunities. As race revealed the intersection of social connections, we speculated that uneven interactions with residential communities partially contribute to the spread of the epidemic. Additionally, the vaccine showed different protection in different regions. In the northern and northeastern regions, AstraZeneca was much more protective than Sinovac, while Sinovac was more protective for hospitalized patients with varying numbers of comorbidities in the Central-west, Southeast and South regions.

Project description:BackgroundIllness predictive scoring systems are significant and meaningful adjuncts of patient management in the Intensive Care Unit (ICU). They assist in predicting patient outcomes, improve clinical decision making and provide insight into the effectiveness of care and management of patients while optimizing the use of hospital resources. We evaluated mortality predictive performance of Simplified Acute Physiology Score (SAPS 3) and Mortality Probability Models (MPM0-III) and compared their performance in predicting outcome as well as identifying disease pattern and factors associated with increased mortality.MethodsThis was a retrospective cohort study of adult patients admitted to the ICU of the Aga Khan Hospital, Dar- es- Salaam, Tanzania between August 2018 and April 2020. Demographics, clinical characteristics, outcomes, source of admission, primary admission category, length of stay and the support provided with the worst physiological data within the first hour of ICU admission were extracted. SAPS 3 and MPM0-III scores were calculated using an online web-based calculator. The performance of each model was assessed by discrimination and calibration. Discrimination between survivors and non-survivors was assessed by the area under the receiver operator characteristic curve (ROC) and calibration was estimated using the Hosmer-Lemeshow goodness-of-fit test.ResultsA total of 331 patients were enrolled in the study with a median age of 58 years (IQR 43-71), most of whom were male (n = 208, 62.8%), of African origin (n = 178, 53.8%) and admitted from the emergency department (n = 306, 92.4%). In- hospital mortality of critically ill patients was 16.1%. Discrimination was very good for all models, the area under the receiver-operating characteristic (ROC) curve for SAPS 3 and MPM0-III was 0.89 (95% CI [0.844-0.935]) and 0.90 (95% CI [0.864-0.944]) respectively. Calibration as calculated by Hosmer-Lemeshow goodness-of-fit test showed good calibration for SAPS 3 and MPM0-III with Chi- square values of 4.61 and 5.08 respectively and P-Value > 0.05.ConclusionBoth SAPS 3 and MPM0-III performed well in predicting mortality and outcome in our cohort of patients admitted to the intensive care unit of a private tertiary hospital. The in-hospital mortality of critically ill patients was lower compared to studies done in other intensive care units in tertiary referral hospitals within Tanzania.

Dataset Information

SAPS-3 performance for hospital mortality prediction in 30,571 patients with COVID-19 admitted to ICUs in Brazil.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure