Leveraging real world data to characterise the long term impact of COVID-19

随着SARS-CoV-2的出现，COVID-19的表征主要集中在评估患者感染的急性效应1。已知该病毒以上皮细胞、内皮细胞和肺泡巨噬细胞为靶点，可引起肺部、消化道、肾脏、心脏、大脑和其他器官的症状。病毒在骨骼肌、平滑肌、骨和软骨等其他组织中的存在也正在研究中。患者的个体症状和疾病严重程度差异很大，一些人发展为轻度感染，另一些人则出现急性呼吸窘迫综合征（ARDS）、败血症和其他危及生命的疾病。在病人康复后，可能会有各种各样的结果。有些患者出现残留症状，而另一些患者在初次感染很久之后出现新的症状。广泛的器官系统和组织都可能受到影响。症状包括疲劳、呼吸困难、心脏异常、认知障碍、睡眠障碍、创伤后应激障碍、肌肉疼痛、头痛。这些症状持续的程度、对原有疾病的影响以及对治疗的反应尚不清楚。关于COVID-19后出现长期疾病和并发症的风险因素也缺乏证据。拟议的项目旨在描述患者的概况和现象；与COVID-19长期相关的症状模式、风险因素和并发症；心血管和血栓栓塞并发症的发生及其健康结局；并研究和描述预先存在的合并症的潜在进展，如心力衰竭、肾脏疾病和对治疗的反应。该项目将利用英国现有的健康数据源，并将其映射到观察性医疗成果伙伴关系（OMOP）共同数据模型中，并将提出一项网络队列研究。将确定从COVID-19和控制中恢复的患者，并对其进行长达3年的随访。这项研究的结果将支持更好的患者管理，并可能重新评估和开发治疗方法，以解决COVID-19疾病的长期医疗和公共卫生负担。拟议的伙伴关系将使药物流行病学研究小组（即学术伙伴）能够获得国际数据源和管理和处理此类数据的内部专门知识。候选人将受益于行业主导的计划和工作流程。拜耳（行业合作伙伴）将受益于知识交流、培训机会，以及Prieto-Alhambra教授团队中对现实世界数据分析的最先进专业知识。该项目的结果可能会为长期COVID患者的未来管理提供信息，并为未来治疗其并发症的疗法的开发提供信息。

With the emergence of SARS-CoV-2, COVID-19 characterization has primarily focused on the assessment of the acute effects of infection in patients1. It is known that the virus targets epithelial cells, endothelial cells and alveolar macrophages causing symptoms attributable to the lungs, digestive tract, kidneys, heart, brain, and other organs. Viral presence is also being investigated in other tissues such as skeletal muscle, smooth muscle, bone and cartilage2.Individual symptoms and disease severity vary widely among patients, with some developing mild infections and others experiencing acute-respiratory- distress-syndrome (ARDS), sepsis, and other life-threatening conditions3,4.Following patient recovery, a wide range of outcomes are possible. Some patients experience residual symptoms, while others develop new symptoms long after initial infection5. A wide range of organ systems and tissues can be affected. Symptoms include fatigue, dyspnea, cardiac abnormalities, cognitive impairment, sleep disturbances, post-traumatic-stress-disorder, muscle pain, headache. The extent to which these symptoms persist, the effects on pre-existing conditions and response to therapies are not well understood. There is also a lack of evidence on the risk factors for developing long term conditions and complications following COVID-19.The proposed project aims to characterize patient profiles and phenomes; symptom patterns, risk factors and complications associated with long term COVID-19; the occurrence of cardiovascular and thromboembolic complications and their health outcomes; and to study and describe the potential progression of pre-existing comorbidities such as heart failure, kidney disease, and response to treatments.The project will utilize existing health data sources in the UK and internationally mapped to the Observational Medical Outcomes Partnership (OMOP) Common Data Model and a network cohort study will be proposed. Patients recovering from COVID-19 and controls will be identified and followed up for up to 3 years.Results from this research will support better patient management and the potential re-assessment and development of therapies to address the medical and public health burden of long term of COVID-19 disease.The proposed partnership will provide the Pharmacoepidemiology Research Group (i.e. The Academic Partner) with access to international data sources and in-house expertise in the curation and processing of such data. The candidate will benefit from exposure to industry-led initiatives and working processes. Bayer (The Industry Partner) will benefit from knowledge exchange, training opportunities, and state-of-the-art expertise in the analysis of real world data existing within Prof Prieto-Alhambra's group. The project's results will likely inform the future management of long term COVID patients, as well as the development of future therapies to treat its complications.