课题基金 / 基金详情

Effects of donor plasma and recipient characteristics on convalescent plasma treatment outcome of COVID-19

Effects of donor plasma and recipient characteristics on convalescent plasma treatment outcome of COVID-19
供体血浆和受体特征对 COVID-19 恢复期血浆治疗结果的影响
批准号:
10225219
负责人:
Maria Laura Gennaro
金额:
$75.39万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-08-01 至 2022-07-31

项目摘要

项目成果

Maria Laura Gennaro的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
In the absence of FDA-approved pharmacological therapies, convalescent plasma infusion has rapidly emerged as a notable emergency therapy for severe cases of COVID-19. However, due to the emergency conditions under which this treatment has been practiced, little effort has been placed in characterizing the properties of the donor plasma and the clinical status of the COVID- 19 patients that can most benefit from the infusion. We have assembled a multidisciplinary team that leverages linked blood donation and blood transfusion programs at Robert Wood Johnson University Hospital and state-of-the-art resources for the study of antibody responses and plasma markers of COVID-19 severity. This team proposes to conduct a study that relates donor plasma properties (antibody titers and functions, and antigen targets) and recipient's clinical status (including peripheral blood cell immunophenotypes and various plasma markers of COVID-19 severity) to the success of convalescent plasma infusion. The new knowledge resulting from our plan will guide the development of rational clinical practice guidelines and the design of convalescent plasma clinical trials.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
COVID-19 Network of Networks Expanding Clinical and Translational approaches to Predict Severe Illness in Children (CONNECT to Predict SIck Children)
COVID-19 Network of Networks Expanding Clinical and Translational approaches to Predict Severe Illness in Children (CONNECT to Predict SIck Children)
COVID-19 Network of Networks Expanding Clinical and Translational approaches to Predict Severe Illness in Children (CONNECT to Predict SIck Children)
COVID-19 Network of Networks Expanding Clinical and Translational approaches to Predict Severe Illness in Children (CONNECT to Predict SIck Children)
海外基金