COPE: Characterisation of COPD Exacerbations using Environmental Exposure Modelling

COPE：使用环境暴露模型描述 COPD 恶化的特征

• 批准号: MR/L019744/1
• 负责人: Benjamin Barratt
• 金额: $ 100.61万
• 依托单位: King's College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FL019744%2F1
• 关键词: COPE; Characterisation; COPD; Exacerbations; using

The aim of this research is to reduce the frequency of hospital and GP visits by patients with chronic obstructive pulmonary disease (COPD). This will be achieved by utilising a combination of miniature sensors that measure an individual's exposure to air pollution, mathematical models that predict air pollution at any location in a city and people's GP health records.Despite substantial evidence of the adverse health effects of air pollution, ranging from respiratory symptoms through to cancer and cardiovascular mortality, gaps and uncertainties exist in our understanding of why this happens. This has been attributed to over-simplified estimates of how much air pollution (and other environmental stress) individuals are exposed to as they go about their daily lives. This project addresses this limitation by bringing together two fields of research that have made rapid advancements in recent years - time-activity exposure models and personal pollution sensors. The research will be applied to a public health challenge requiring urgent knowledge advancement; prediction and management of COPD exacerbations. COPD patients are at risk of severe episodes of deterioration - 'exacerbations'. Exacerbations are the second commonest cause of adult emergency medical hospital admission in the UK and are associated with shortened lives and decreased quality of life. The first phase of the study will comprise the largest real time patient exposure measurement campaign yet carried out in the UK. Micro pollution, temperature and humidity sensors will be carried by 200 COPD patients for six months, with movements tracked by satellite navigation (GPS). During this period patients will keep records of symptoms relating to their condition (such as breathlessness, cough and wheeze) on diary cards and take daily exhaled breath flow tests. We will use this extensive measurement dataset to relate COPD symptoms and exacerbations to air pollution, temperature and humidity levels and activities such as travelling, cooking and exposure to tobacco smoke.The measurements will then be used to assess and improve the performance of a high resolution 'time-activity' exposure model recently developed for London. Time-activity computer models allow the calculation of an individual's exposure to pollution as they move about a city throughout the day. However, their accuracy is unproven. The pollution measurements taken during the first phase of the study will provide a means of testing the performance of the exposure model by comparing modelled and measured exposure estimates for the 200 COPD patients.Links between COPD exacerbations and environmental exposure identified in the first phase will be combined with the exposure model validated in the second phase to create a new model for predicting COPD exacerbations. The performance of this model will be evaluated by comparing modelled predictions against GP and hospital records of exacerbations between 2005 and 2011.If the predictive performance of this model is proven, it presents a means of forming a validated COPD forecasting tool for public health providers in London. The predictive algorithms used in the model will be made available for application across the UK, providing an opportunity for the development of a national COPD forecasting service with proven performance in predicting increased risk of exacerbations.The final project outcome will be the production of a patient-orientated report describing associations between environmental exposure and COPD symptoms, clearly illustrating how COPD patients can adjust their behaviour to reduce their risk of exacerbation and improve their quality of life.

本研究的目的是减少慢性阻塞性肺疾病（COPD）患者的医院和GP访问频率。这将通过使用测量个人暴露于空气污染的微型传感器、预测城市任何地点空气污染的数学模型和人们的全科医生健康记录的组合来实现。尽管有大量证据表明空气污染对健康的不利影响，从呼吸道症状到癌症和心血管死亡率，但我们对这种情况发生的原因的理解存在差距和不确定性。这是由于对个人在日常生活中暴露于空气污染（和其他环境压力）的过度简化的估计。该项目通过将近年来取得快速进展的两个研究领域-时间活动暴露模型和个人污染传感器-结合在一起来解决这一限制。该研究将应用于需要紧急知识进步的公共卫生挑战;预测和管理COPD急性加重。COPD患者有严重恶化发作的风险-“加重”。急性发作是英国成人急诊住院的第二大常见原因，与生命缩短和生活质量下降有关。该研究的第一阶段将包括迄今在英国开展的最大规模的真实的患者暴露测量活动。200名COPD患者将携带微污染、温度和湿度传感器，为期6个月，并通过卫星导航（GPS）跟踪其运动。在此期间，患者将在日记卡上记录与其病情相关的症状（如呼吸困难、咳嗽和喘息），并进行每日呼气流量测试。我们将使用这一广泛的测量数据集将COPD症状和加重与空气污染、温度和湿度水平以及旅行、烹饪和接触烟草烟雾等活动联系起来，然后将这些测量结果用于评估和改善最近为伦敦开发的高分辨率“时间-活动”暴露模型的性能。时间-活动计算机模型允许计算一个人在一天中在城市中移动时暴露于污染的程度。然而，其准确性未经证实。在研究的第一阶段进行的污染测量将通过比较200名COPD患者的模拟和测量暴露估计值来测试暴露模型的性能，第一阶段确定的COPD急性加重和环境暴露之间的联系将与第二阶段验证的暴露模型相结合，以创建预测COPD急性加重的新模型。通过比较2005年至2011年全科医生和医院急性加重记录的模型预测，评估该模型的性能。如果该模型的预测性能得到证实，它将为伦敦的公共卫生提供者提供一种有效的COPD预测工具。该模型中使用的预测算法将在英国各地应用，为开发国家COPD预测服务提供机会，该服务在预测加重风险增加方面具有经证实的性能。最终项目成果将是制作一份以患者为导向的报告，描述环境暴露与COPD症状之间的关联，清楚地说明了COPD患者如何调整他们的行为，以减少他们的恶化风险，提高他们的生活质量。

项目成果

Personal exposure to air pollution and respiratory health of COPD patients in London.

• DOI: 10.1183/13993003.03432-2020
• 发表时间: 2021-07
• 期刊: The European respiratory journal
• 作者: Evangelopoulos D;Chatzidiakou L;Walton H;Katsouyanni K;Kelly FJ;Quint JK;Jones RL;Barratt B
• 通讯作者: Barratt B

Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments

• DOI: 10.5194/amt-12-4643-2019
• 发表时间: 2019-08-30
• 期刊: ATMOSPHERIC MEASUREMENT TECHNIQUES
• 影响因子: 3.8
• 作者: Chatzidiakou, Lia;Krause, Anika;Jones, Roderic L.
• 通讯作者: Jones, Roderic L.

Effects of AIR pollution on cardiopuLmonary disEaSe in urban and peri-urban reSidents in Beijing: protocol for the AIRLESS study

• DOI: 10.5194/acp-20-15775-2020
• 发表时间: 2020-12-18
• 期刊: ATMOSPHERIC CHEMISTRY AND PHYSICS
• 影响因子: 6.3
• 作者: Han, Yiqun;Chen, Wu;Zhu, Tong
• 通讯作者: Zhu, Tong

Automated classification of time-activity-location patterns for improved estimation of personal exposure to air pollution.

• DOI: 10.1186/s12940-022-00939-8
• 发表时间: 2022-12-09
• 期刊: ENVIRONMENTAL HEALTH
• 影响因子: 6
• 作者: Chatzidiakou, Lia;Krause, Anika;Kellaway, Mike;Han, Yiqun;Li, Yilin;Martin, Elizabeth;Kelly, Frank J.;Zhu, Tong;Barratt, Benjamin;Jones, Roderic L.
• 通讯作者: Jones, Roderic L.