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影响1。已知该病毒靶向上皮细胞、内皮细胞和肺泡巨噬细胞，引起归因于肺、消化道、肾、心脏、脑和其它器官的症状。其他组织如骨骼肌、平滑肌、骨和软骨中的病毒存在也在研究中2。患者的个体症状和疾病严重程度差异很大，一些患者出现轻度感染，另一些患者出现急性呼吸窘迫综合征（ARDS）、脓毒症和其他危及生命的疾病3，4。患者康复后，可能会出现多种结局。一些患者会出现残留症状，而另一些患者在初次感染后很久才出现新症状5。广泛的器官系统和组织可能受到影响。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、对既存疾病的影响以及对治疗的反应尚不清楚。此外，亦缺乏证据显示COVID-19后出现长期病症及并发症的风险因素。建议的项目旨在描述病人的特征及表现;与长期COVID-19相关的症状模式、风险因素及并发症;心血管及血栓栓塞并发症的发生及其健康结果;并研究和描述既存合并症的潜在进展，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，并在国际上映射到观察性医学成果伙伴关系（OMOP）通用数据模型和网络队列研究。将对从COVID-19中康复的患者和控制患者进行识别和随访长达3年。这项研究的结果将支持更好的患者管理以及潜在的重新评估和治疗方法的开发，以解决COVID-19疾病的长期医疗和公共卫生负担。拟议的合作伙伴关系将提供药物流行病学研究小组（即学术合作伙伴）可以访问国际数据源以及管理和处理此类数据的内部专业知识。候选人将受益于行业主导的举措和工作流程。拜耳（行业合作伙伴）将受益于Prieto-Alhambra教授团队中现有的知识交流、培训机会和真实的世界数据分析方面的最先进专业知识。该项目的结果可能会为长期COVID患者的未来管理以及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.