Clinical characteristics and plasma antibody titer of patients with COVID-19 in Zhejiang, China

JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE B(2020)

引用 3|浏览8
暂无评分
摘要
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which first affected humans in China on December 31, 2019 (Shi et al., 2020). Coronaviruses generally cause mild, self-limiting upper respiratory tract infections in humans, such as the common cold, pneumonia, and gastroenteritis (To et al., 2013; Berry et al., 2015; Chan et al., 2015). According to the Report of the World Health Organization (WHO)-China Joint Mission on COVID-19 (WHO, 2020), the case fatality rate of COVID-19 increases with age, while the rate among males is higher than that among females (4.7% and 2.8%, respectively). Since an effective vaccine and specific anti-viral drugs are still under development, passive immunization using the convalescent plasma (CP) of recovered COVID-19 donors may offer a suitable therapeutic strategy for severely ill patients in the meantime. So far, several studies have shown therapeutic efficacy of CP transfusion in treating COVID-19 cases. A pilot study first reported that transfusion of CP with neutralizing antibody titers above 1:640 was well tolerated and could potentially improve clinical outcomes through neutralizing viremia in severe COVID-19 cases (Chen et al., 2020). Immunoglobulin G (IgG) and IgM are the most abundant and important antibodies in protecting the human body from viral attack (Arabi et al., 2015; Marano et al., 2016). Our study aimed to understand the aspects of plasma antibody titer levels in convalescent patients, as well as assessing the clinical characteristics of normal, severely ill, and critically ill patients, and thus provide a basis for guiding CP therapy. We also hoped to find indicators which could serve as a reference in predicting the progression of the disease.
更多
查看译文
关键词
新型冠状病毒肺炎 (COVID-19),恢复期血浆,临床特征,抗体滴度
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要