Characterisation, determinants, mechanisms and consequences of the long-term effects of COVID-19: providing the evidence base for health care

COVID-19 长期影响的特征、决定因素、机制和后果：为医疗保健提供证据基础

• 批准号: MC_PC_20051
• 负责人: Nishi Chaturvedi
• 金额: $ 611.23万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Intramural
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MC_PC_20051
• 关键词: Characterisation; determinants; mechanisms; consequences; long

We will address the following patient defined questions: What is long-COVID and how is it diagnosed? Why have I got long-COVID? What effects will long-COVID have on my health, ability to work and family? What are my chances of recovery? How will this research ensure I am getting the right treatment and support for long-COVID? Physical and mental health consequences of C-19 infection, termed long-COVID, occur frequently. Our understanding of long-COVID, including how best to diagnose, risk factors, health and economic consequences, is poor, limiting efforts to help people. We will use a combination of national anonymised linked primary care electronic health records, and longitudinal studies of people of all ages across the country. We have asked participants about C-19 infections, long-COVID symptoms, and have collected health and socioeconomic information for many years before the pandemic. From these studies, we will ask people reporting long-COVID, and comparator groups, to wear a wrist band measuring exercise ability, breathing, and heart rate, and complete online questionnaires on mental health and cognitive function. They will also be invited to clinic for non-invasive imaging to look at potential damage to vital organs, such as the brain, lungs and heart. Patients, members of the public overseeing electronic health record research, and study members have been involved in shaping the research questions, and will be consulted for the duration of the project. In addition, people with long-COVID and their families, from the studies, will be involved in shaping the diagnostic tools for long-COVID, and aiding our understanding of determinants of recovery, and responses to therapy. We will share findings with bodies involved in guidelines (NICE, who are also part of this project), with government (via the publications).

我们将解决以下患者定义的问题：什么是长期COVID以及如何诊断？为什么我得了长时间的新冠肺炎？长期COVID对我的健康、工作能力和家庭有什么影响？我康复的机会有多大？这项研究将如何确保我得到正确的治疗和支持长期COVID？C-19感染的身体和精神健康后果，称为长期COVID，经常发生。我们对长期COVID的理解，包括如何最好地诊断，风险因素，健康和经济后果，都很差，限制了帮助人们的努力。我们将结合使用全国匿名链接的初级保健电子健康记录，以及对全国所有年龄段人群的纵向研究。我们询问了参与者有关C-19感染、长期COVID症状的情况，并收集了大流行前多年的健康和社会经济信息。从这些研究中，我们将要求报告长期COVID的人和对照组佩戴腕带，测量运动能力，呼吸和心率，并完成有关心理健康和认知功能的在线问卷。他们还将被邀请到诊所进行非侵入性成像，以观察对大脑，肺和心脏等重要器官的潜在损害。病人、监督电子健康记录研究的公众成员和研究成员都参与了研究问题的形成，并将在项目期间接受咨询。此外，来自研究的长期COVID患者及其家人将参与制定长期COVID的诊断工具，并帮助我们了解康复的决定因素和对治疗的反应。我们将与参与指导方针的机构（NICE，他们也是该项目的一部分）和政府（通过出版物）分享调查结果。

项目成果

Estimating the Effectiveness of First Dose of COVID-19 Vaccine Against Mortality in England: A Quasi-Experimental Study.

估计英国第一剂 COVID-19 疫苗对死亡率的有效性：一项准实验研究。

• DOI: 10.1093/aje/kwac157
• 发表时间: 2023
• 期刊: American journal of epidemiology
• 影响因子: 5
• 作者: Bermingham C

Children's behavioural and emotional wellbeing during the COVID-19 pandemic: Findings from the Born in Bradford COVID-19 mixed methods longitudinal study

COVID-19 大流行期间儿童的行为和情绪健康：出生于布拉德福德的 COVID-19 混合方法纵向研究的结果

• DOI: 10.12688/wellcomeopenres.20752.1
• 发表时间: 2024
• 期刊: Wellcome Open Research
• 作者: Badrick E

Understanding the lived experience of Long Covid: A rapid literature review

了解长期新冠疫情的生活经历：快速文献回顾

• 发表时间: 2021
• 作者: Baz. S. A.

'I don't know what to do or where to go'. Experiences of accessing healthcare support from the perspectives of people living with Long Covid and healthcare professionals: A qualitative study in Bradford, UK.

• DOI: 10.1111/hex.13687
• 发表时间: 2023-02
• 期刊: HEALTH EXPECTATIONS
• 影响因子: 3.2
• 作者: Baz, Sarah A.;Fang, Chao;Carpentieri, J. D.;Sheard, Laura
• 通讯作者: Sheard, Laura

Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration.

• DOI: 10.1186/s12911-022-02093-0
• 发表时间: 2023-01-16
• 期刊: BMC MEDICAL INFORMATICS AND DECISION MAKING
• 影响因子: 3.5
• 作者: Abbasizanjani, Hoda;Torabi, Fatemeh;Bedston, Stuart;Bolton, Thomas;Davies, Gareth;Denaxas, Spiros;Griffiths, Rowena;Herbert, Laura;Hollings, Sam;Keene, Spencer;Khunti, Kamlesh;Lowthian, Emily;Lyons, Jane;Mizani, Mehrdad A.;Nolan, John;Sudlow, Cathie;Walker, Venexia;Whiteley, William;Wood, Angela;Akbari, Ashley
• 通讯作者: Akbari, Ashley