COVID-19 hospitalizations in Brazil's Unified Health System (SUS).
COVID-19 hospitalizations in Brazil's Unified Health System (SUS).
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DOI：
10.1371/journal.pone.0243126
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发表时间：
2020
期刊：
影响因子：
3.7
通讯作者：
Portela MC
中科院分区：
文献类型：
--
作者：
de Andrade CLT;Pereira CCA;Martins M;Lima SML;Portela MC
研究巴西统一卫生系统(SUS)中因新冠肺炎而住院的情况，并确定与该病相关的住院死亡率相关因素。一项横断面研究，基于2月下旬至6月期间在南美住院治疗的次要数据。初诊或继发诊断为新冠肺炎的患者年龄在18岁或以上。进行双变量分析，随机效应截距估计广义线性混合模型(GLMM)。建模遵循三个步骤，包括：患者的属性；护理过程的要素；医院和住院地点的特征。住院89405例，死亡24.4%。在南美住院的新冠肺炎患者主要是男性(56.5%)，平均年龄58.9岁。住院时间从不到24小时到114天不等，平均6.9(±6.5)天。在住院总人数中，22.6%的人报告使用了ICU。男性住院死亡的几率比女性高16.8%，而且随着年龄的增长而增加。黑人死亡的可能性更高。Charlson和Elixhauser指数的行为与合并症患者死亡风险更高的假设是一致的，肥胖对增加这种风险具有独立影响。一些州，如亚马逊和里约热内卢，因新冠肺炎住院死亡的风险更高。在居民至少10万的城市，住院死亡的几率高出72.1%，尽管在居住城市住院是一个保护因素。新冠肺炎住院死亡率在南美存在广泛差异，与人口和临床因素、社会不平等以及服务结构和医疗质量的差异有关。
To study the profile of hospitalizations due to COVID-19 in the Unified Health System (SUS) in Brazil and to identify factors associated with in-hospital mortality related to the disease. Cross-sectional study, based on secondary data on COVID-19 hospitalizations that occurred in the SUS between late February through 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. 89,405 hospitalizations were observed, of which 24.4% resulted in death. COVID-19 patients hospitalized in the 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 odds on in-hospital death were 16.8% higher among men than among women and increased with age. Black individuals had a higher likelihood 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, such as Amazonas and Rio de Janeiro, had a higher risk of in-hospital death from COVID-19. The odds on in-hospital death were 72.1% higher in municipalities with at least 100,000 inhabitants, though being hospitalized in the municipality of residence was a protective factor. There was broad variation in COVID-19 in-hospital 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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影响因子：
2.9
作者：
Harrison C;Britt H;Miller G;Henderson J
通讯作者：
Henderson J
影响因子：
34.3
作者：
Baqui, Pedro;Bica, Ioana;van der Schaar, Mihaela
通讯作者：
van der Schaar, Mihaela
影响因子：
3
作者：
Elixhauser, A;Steiner, C;Coffey, RN
通讯作者：
Coffey, RN
影响因子：
6.3
作者：
Marmot M;Allen J
通讯作者：
Allen J
影响因子：
105.7
作者：
Docherty, Annemarie B.;Harrison, Ewen M.;Semple, Malcolm G.
通讯作者：
Semple, Malcolm G.