医学
2019年冠状病毒病(COVID-19)
人口学
二元分析
肥胖
疾病
儿科
急诊医学
内科学
传染病(医学专业)
数学
统计
社会学
作者
Carla Lourenço Tavares de Andrade,Claudia Cristina de Aguiar Pereira,Mônica Martins,Sheyla Maria Lemos Lima,Margareth Crisóstomo Portela
标识
DOI:10.1101/2020.09.03.20187617
摘要
Abstract Objective To study the profile of hospitalizations due to COVID-19 in the Unified Health System (SUS) in Brazil and to identify factors associated with hospital mortality related to the disease. Methods Cross-sectional study, based on secondary data on COVID-19 hospitalizations that occurred in SUS, between the last days of February and June. Patients aged 18 years or older, with primary or secondary diagnoses indicative of COVID-19 were included. Bivariate analyses were performed and generalized linear mixed models (GLMM) were estimated with random effects intercept. The modeling followed three steps, including: attributes of the patients; elements of the care process; and characteristics of the hospital and place of hospitalization. Results 89,405 hospitalizations were observed, of which 24.4% resulted in death. COVID-19 patients hospitalized in SUS were predominantly male (56.5%), with a mean age of 58.9 years. The length of stay ranged from less than 24 hours to 114 days, with a mean of 6.9 (±6.5) days. Of the total number of hospitalizations, 22.6% reported ICU use. The chances of hospital death among men were 16.8% higher than among women and increased with age. Black individuals had a higher chance of death. The behavior of the Charlson and Elixhauser indices was consistent with the hypothesis of a higher risk of death among patients with comorbidities, and obesity had an independent effect on increasing this risk. Some states had a higher risk of hospital death from COVID-19, such as Amazonas and Rio de Janeiro. The chances of hospital death were 72.1% higher in municipalities with at least 100,000 inhabitants and being hospitalized in the municipality of residence was a protective factor. Conclusion There was wide variation in hospital COVID-19 mortality in the SUS, associated with demographic and clinical factors, social inequality and differences in the structure of services and quality of health care.
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