Cardiovascular Disease and Diabetes Cohorts Trusted Research Environment (CVDD Cohorts TRE)

心血管疾病和糖尿病队列可信研究环境 (CVDD Cohorts TRE)

基本信息

  • 批准号:
    MR/X013928/1
  • 负责人:
  • 金额:
    $ 99.78万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2022
  • 资助国家:
    英国
  • 起止时间:
    2022 至 无数据
  • 项目状态:
    已结题

项目摘要

There are many studies across the UK that collect detailed information about patients with particular diseases and aim to follow their health over many years. These studies are called cohorts. They allow researchers to study the causes of diseases, better understand how they affect patients, and develop new approaches for diagnosis and treatment. With their consent, these studies collect data directly from patients (using questionnaires and measurements) and from specialist hospital and clinic information systems, including imaging scans. They may also collect blood samples for laboratory measurements and information from mobile phone apps and monitoring devices worn by the patients taking part in the study. All of this information is collected into a database. It is particularly valuable for research analyses when combined with data about the health of the patients taking part before they developed the disease and during follow up over many years after their diagnosis. This health data can be obtained from databases collected and held by national NHS organisations, including data about hospital visits, medicines dispensed from pharmacies and death certificates. Obtaining information from these national databases is challenging, time-consuming, costly and - as a result - not always successful. It involves understanding which data are available from which NHS organisation, completing complex applications and obtaining the approval of each relevant organisation. Cohorts also need to provide a secure environment to receive and hold the data, link it together with the other study data, and provide safe, secure access to researchers to conduct their research analyses. This proposal aims to provide a single platform to overcome these challenges for UK-wide cohorts of patients with diseases of the heart and circulation (so-called 'cardiovascular diseases', such as heart attacks, heart failure and stroke) and diabetes. A dedicated, experienced team will coordinate applications and approvals for cohorts to obtain data from national NHS databases. A secure platform will be provided by a carefully selected, specialist provider to hold all the data collected by each cohort and link it with the additional data from national NHS databases. Specialist health data scientists will provide support for the cohorts in managing, checking, interpreting and analysing this additional linked NHS data. Data from each cohort will be held in a separate, secure space within the platform. Researchers approved to carry out analyses of cohort study data will not take data out of the platform but instead will access it remotely within the platform via a secure log in. To protect the privacy of the patients taking part, all information from which they could be identified (for example name, exact date of birth and NHS number) will be held securely in a separate part of the platform. This identifiable information will only be accessible for essential purposes by a very small number of named cohort study staff. Researchers will not access any of this identifiable information. The platform will also provide specialist tools for the combined analysis of the many different types of data collected by each cohort. This single platform will allow researchers to answer crucial research questions to improve the care of patients with cardiovascular diseases and diabetes much more quickly, more securely, and at lower cost than is currently the case. In the future it could be expanded to support research on cohorts of patients with a wide range of other diseases.
英国有许多研究收集了患有特定疾病的患者的详细信息,并旨在多年跟踪他们的健康状况。这些研究被称为队列研究。它们使研究人员能够研究疾病的原因,更好地了解它们如何影响患者,并开发新的诊断和治疗方法。在征得患者同意后,这些研究直接从患者(使用问卷和测量)以及专科医院和诊所信息系统(包括成像扫描)收集数据。他们还可能采集血液样本用于实验室测量,并从参与研究的患者佩戴的移动的手机应用程序和监测设备中采集信息。所有这些信息都被收集到数据库中。当与参与患者在发病前和诊断后多年随访期间的健康数据相结合时,它对于研究分析特别有价值。这些健康数据可以从国家NHS组织收集和持有的数据库中获得,包括有关医院访问,药房分发的药物和死亡证明的数据。从这些国家数据库中获取信息具有挑战性,耗时,成本高,因此并不总是成功的。它涉及了解哪些数据可从哪个NHS组织获得,完成复杂的申请并获得每个相关组织的批准。队列还需要提供一个安全的环境来接收和保存数据,将其与其他研究数据链接在一起,并为研究人员提供安全可靠的访问权限来进行研究分析。该提案旨在为英国范围内的心脏和循环疾病(所谓的“心血管疾病”,如心脏病发作,心力衰竭和中风)和糖尿病患者提供一个单一的平台来克服这些挑战。一个专门的、经验丰富的团队将协调队列的申请和批准,以从国家NHS数据库中获取数据。一个安全的平台将由一个精心挑选的专业提供商提供,以保存每个队列收集的所有数据,并将其与国家NHS数据库中的其他数据联系起来。专家健康数据科学家将为队列提供支持,管理,检查,解释和分析这些额外的相关NHS数据。来自每个队列的数据将保存在平台内的单独安全空间中。获准对队列研究数据进行分析的研究人员不会将数据从平台中取出,而是通过安全登录在平台内远程访问数据。为了保护参与研究的患者的隐私,所有可以识别他们的信息(例如姓名、确切的出生日期和NHS编号)将安全地保存在平台的单独部分。只有极少数指定的队列研究工作人员可出于基本目的访问该可识别信息。研究人员不会访问任何这些可识别的信息。该平台还将提供专业工具,用于对每个群组收集的许多不同类型的数据进行综合分析。这个单一平台将允许研究人员回答关键的研究问题,以更快,更安全,更低的成本改善心血管疾病和糖尿病患者的护理。在未来,它可以扩展到支持对患有各种其他疾病的患者队列的研究。

项目成果

期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)

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Cathie Sudlow其他文献

Personal experiences of electronic measurement of medication adherence in elderly stroke survivors
  • DOI:
    10.1007/s40267-015-0200-6
  • 发表时间:
    2015-04-15
  • 期刊:
  • 影响因子:
    0.700
  • 作者:
    Julie A. Chambers;Ronan E. O’Carroll;Martin Dennis;Cathie Sudlow;Marie Johnston
  • 通讯作者:
    Marie Johnston
Prevalence and demographics of 331 rare diseases and associated COVID-19-related mortality among 58 million individuals: a nationwide retrospective observational study
5800 万人中 331 种罕见病的患病率、人口统计学特征以及相关的 COVID-19 相关死亡率:一项全国性回顾性观察研究
  • DOI:
    10.1016/s2589-7500(24)00253-x
  • 发表时间:
    2025-02-01
  • 期刊:
  • 影响因子:
    24.100
  • 作者:
    Johan H Thygesen;Huayu Zhang;Hanane Issa;Jinge Wu;Tuankasfee Hama;Ana-Caterina Phiho-Gomes;Tudor Groza;Sara Khalid;Thomas R Lumbers;Mevhibe Hocaoglu;Kamlesh Khunti;Rouven Priedon;Amitava Banerjee;Nikolas Pontikos;Chris Tomlinson;Ana Torralbo;Paul Taylor;Cathie Sudlow;Spiros Denaxas;Harry Hemingway;Honghan Wu
  • 通讯作者:
    Honghan Wu
Heart Failure Specialist Care and Long-Term Outcomes for Patients Admitted With Acute Heart Failure
急性心力衰竭住院患者的心力衰竭专科护理与长期预后
  • DOI:
    10.1016/j.jchf.2024.06.013
  • 发表时间:
    2025-03-01
  • 期刊:
  • 影响因子:
    11.800
  • 作者:
    Antonio Cannata;Mehrdad A. Mizani;Daniel I. Bromage;Susan E. Piper;Suzanna M.C. Hardman;Cathie Sudlow;Mark de Belder;Paul A. Scott;John Deanfield;Roy S. Gardner;Andrew L. Clark;John G.F. Cleland;Theresa A. McDonagh;CVD-COVID-UK/COVID-IMPACT Consortium
  • 通讯作者:
    CVD-COVID-UK/COVID-IMPACT Consortium
Developing a novel set of quality performance indicators (QPIs) for metastatic bone disease (MBD)
  • DOI:
    10.1016/j.ejso.2020.11.085
  • 发表时间:
    2021-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Samantha Downie;Alison Stillie;Matthew Moran;Cathie Sudlow;Hamish Simpson
  • 通讯作者:
    Hamish Simpson
Demographics of lipoprotein(a) and stroke: The UK biobank
  • DOI:
    10.1016/j.ajpc.2025.101055
  • 发表时间:
    2025-09-01
  • 期刊:
  • 影响因子:
    5.900
  • 作者:
    Andrew S. Kao;Jonathan Kermanshahchi;Shamim Khosrowjerdi;Alexander C. Razavi;Jacqueline Levene;Mikaila Reyes;Parveen Garg;W.T. Longstreth;Kristiina Rannikmae;Cathie Sudlow;Michael Tsai;Sotirios Tsimikas;Anum Saeed;Harpreet S. Bhatia
  • 通讯作者:
    Harpreet S. Bhatia

Cathie Sudlow的其他文献

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{{ truncateString('Cathie Sudlow', 18)}}的其他基金

Big Data for Complex Disease
复杂疾病的大数据
  • 批准号:
    HDR-23012
  • 财政年份:
    2023
  • 资助金额:
    $ 99.78万
  • 项目类别:
    Intramural

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循环硫化氢、糖尿病和糖尿病相关的心血管疾病
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    10420827
  • 财政年份:
    2022
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    $ 99.78万
  • 项目类别:
Pitt-Mozambique Training Program(Pitt-MozHRTP) in COVID-19, Cardiovascular Disease, and Diabetes in People with HIV
皮特-莫桑比克 COVID-19、心血管疾病和艾滋病毒感染者糖尿病培训计划 (Pitt-MozHRTP)
  • 批准号:
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