Studying the pathophysiology of coronavirus disease 2019: a protocol for the Berlin prospective COVID-19 patient cohort (Pa-COVID-19)
Studying the pathophysiology of coronavirus disease 2019: a protocol for the Berlin prospective COVID-19 patient cohort (Pa-COVID-19)
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DOI：
10.1007/s15010-020-01464-x
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发表时间：
2020-06-13
期刊：
影响因子：
7.5
通讯作者：
Sander, Leif Erik
中科院分区：
文献类型：
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作者：
Kurth, Florian;Roennefarth, Maria;Sander, Leif Erik
严重急性呼吸综合征冠状病毒2 （SARS-CoV-2）已在全球范围内传播，造成全球卫生紧急情况。Pa-COVID-19旨在提供有关COVID-19的临床病程、病理生理学、免疫学和转归的全面数据，以确定预后生物标志物、临床评分和治疗靶点，以改进临床管理和预防性干预措施。方法pa - covid是一项前瞻性观察队列研究，研究对象是在柏林夏里特医科大学接受治疗的确诊SARS-CoV-2感染患者。我们收集流行病学、人口学、病史、症状、临床过程、病原体检测和治疗的数据。系统的、连续的血液取样将允许深入的分子和免疫表型、转录组分析和全面的生物银行。住院期间的纵向数据和样本收集将辅以长期随访。结果测量包括第15天的WHO临床顺序量表以及出院时和随访期间的临床、功能和健康相关生活质量评估。我们开发了一个可扩展的数据集，以(i)适应国家护理标准，（ii）促进不同资源的医疗机构的综合数据收集，以及（iii）允许基于标准化研究设计和数据收集的干预性试验的快速实施。我们提出这一可扩展的方案，作为在德国统一数据收集和深度表型分析的蓝图。结论建立了统一、可扩展的COVID-19数据收集、病理生理分析和深度表型分析的基础平台，为改善医疗服务和确定候选治疗和预防策略提供了快速证据。介入试验认可的电子数据库允许候选治疗剂的快速试验实施。
Purpose Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide causing a global health emergency. Pa-COVID-19 aims to provide comprehensive data on clinical course, pathophysiology, immunology and outcome of COVID-19, to identify prognostic biomarkers, clinical scores, and therapeutic targets for improved clinical management and preventive interventions. Methods Pa-COVID-19 is a prospective observational cohort study of patients with confirmed SARS-CoV-2 infection treated at Charite - Universitatsmedizin Berlin. We collect data on epidemiology, demography, medical history, symptoms, clinical course, and pathogen testing and treatment. Systematic, serial blood sampling will allow deep molecular and immunological phenotyping, transcriptomic profiling, and comprehensive biobanking. Longitudinal data and sample collection during hospitalization will be supplemented by long-term follow-up. Results Outcome measures include the WHO clinical ordinal scale on day 15 and clinical, functional, and health-related quality-of-life assessments at discharge and during follow-up. We developed a scalable dataset to (i) suit national standards of care, (ii) facilitate comprehensive data collection in medical care facilities with varying resources, and (iii) allow for rapid implementation of interventional trials based on the standardized study design and data collection. We propose this scalable protocol as blueprint for harmonized data collection and deep phenotyping in COVID-19 in Germany. Conclusion We established a basic platform for harmonized, scalable data collection, pathophysiological analysis, and deep phenotyping of COVID-19, which enables rapid generation of evidence for improved medical care and identification of candidate therapeutic and preventive strategies. The electronic database accredited for interventional trials allows fast trial implementation for candidate therapeutic agents.