Clinical and Translational Science Award

临床和转化科学奖

• 批准号: 10183901
• 负责人: BRUCE Neil CRONSTEIN
• 金额: $ 76.85万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-18 至 2021-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10183901
• 关键词: 2019-nCoV; Affect; Area; COVID-19; COVID-19 pandemic; Categories; Cessation of life; Childhood; Clinical; Clinical Research; Clinical Sciences; Clinical Trials; Clinical and Translational Science Awards; Code; Communities; Coronavirus; Critical Care; Critical Illness; Data; Data Science; Databases; Development; Diagnosis; Disease; Electronic Health Record; Epidemic; Event; Fatal Outcome; Health; Health system; Healthcare; Hospitalization; Immune response; Individual; Infection; Inflammatory; Informatics; Institution; Ischemic Stroke; Knowledge; Laboratories; Link; Longevity; Marshal; Medical; Natural Language Processing; Nature; New York; New York City; Outcome; Patients; Pharmaceutical Preparations; Pharmacology; Phenotype; Pneumonia; Procedures; Records; Research Personnel; Resources; Respiratory Failure; Risk; Severities; Site; Subgroup; Syndrome; Testing; Text; Therapeutic; Thrombosis; Time; Tissues; Underrepresented Groups; United States; Upper respiratory tract; Venous; Viral Pneumonia; Virus; biobank; central database; cohort; coronavirus disease; data sharing; demographics; design; ethnic minority population; health data; improved; interest; medical specialties; meetings; member; pandemic disease; prevent; racial minority; response; structured data; symptomatic improvement; unstructured data; venous thromboembolism

PROJECT SUMMARY: COMBATCOVID The coronavirus (COVID-19) pandemic has affected every corner of the globe and has redefined healthcare throughout the United States. COVID-19 cases in the New York City tri-state area have reached an extraordinarily high number and have quickly become the epicenter region of the crisis in the United States. In New York State alone, there are over 372,000 confirmed cases as of June 1, 2020. NYU Langone Health (NYULH) has been particularly hard hit, with more than 8,100 COVID-19 hospitalizations to date. In response, the entire clinical research community is marshalling resources in an attempt to improve our understanding of how the virus spreads, how it infects various tissues in the body, which patients are more susceptible to infection and fatal outcomes, which therapeutics improve symptoms and survival, whether the immune response confers long-lasting protection against reinfection, and many other crucially important questions. The complexity of the development of this disease and unpredictability of progression into severity, as well as the variety of phenotypic outcomes observed during and post COVID-19, pose major challenges in understanding, predicting, preventing, managing and treating this disease and its sequelae. Answers to these challenges can only be achieved through the comprehensive analysis of a significantly high number of COVID cases. Given how recent and unknown this disease is, and its inherent epidemic nature, there is a limited number of cases at individual medical institutions. The limitation of number of cases per institution becomes even more relevant when isolating subpopulations with specific health conditions and across the lifespan. This proposed study will aim to overcome the above-mentioned challenges by supporting the formation of a consortium comprising multiple medical institutions in the U.S.: COMBATCOVID (Consortium for Multisite Biomedical Analytics and Trials on COVID-19). COMBATCOVID will bring together electronic health records (EHR) data from multiple participating institutions into a shared centralized database. As part of the COMBATCOVID effort, biorepository data of COVID-19 patients collected by some of the participating institutions will also be shared and linked to the respective EHR data. The COMBATCOVID consortium will be responsible for transferring EHR data pertaining to participating institutions interested in contributing EHR data to the N3C database.

项目概要：COMBATCOVID 新型冠状病毒（COVID-19）大流行影响了地球仪的每个角落，并重新定义了医疗保健 在整个美国。纽约市三州地区的COVID-19病例已达到 数量异常之高，并迅速成为美国危机的震中地区。在 仅纽约州，截至2020年6月1日确诊病例就超过37.2万例。NYU Langone Health （NYULH）受到的打击尤其严重，迄今已有8，100多人因COVID-19住院。 作为回应，整个临床研究界正在整合资源，试图改善我们的 了解病毒是如何传播的，它是如何感染体内的各种组织的，哪些患者更容易感染， 容易受到感染和致命后果，哪些治疗方法可以改善症状和生存，无论是 免疫反应赋予持久的保护，防止再感染，和许多其他至关重要的 问题. 这种疾病发展的复杂性和进展到严重程度的不可预测性，以及 在COVID-19期间和之后观察到的各种表型结果， 了解，预测，预防，管理和治疗这种疾病及其后遗症。回答这些 只有通过对大量新冠肺炎疫情的全面分析， 例考虑到这种疾病是最近才出现的，而且人们对它不了解，再加上它固有的流行病性质， 个别医疗机构的病例。每个机构的案件数量限制变得更加严格， 在隔离具有特定健康状况的亚群和整个生命周期时具有相关性。 这项拟议的研究旨在通过支持建立一个 由美国多家医疗机构组成的联盟：COMBATCOVID（多站点联盟 生物医学分析和COVID-19试验）。 COMBATCOVID将汇集来自多个参与机构的电子健康记录（EHR）数据 一个共享的中央数据库。作为COMBATCOVID工作的一部分，COVID-19的生物储存库数据 部分参与机构收集的病人数据亦会与有关的电子健康记录互通 数据COMBATCOVID联盟将负责传输与参与有关的EHR数据， 有兴趣向N3 C数据库提供EHR数据的机构。