Understanding hearing loss phenotypes, their progression and associations with otological and non-otological disease using hearing health big data

研究目的和背景听力丧失是人类最常见的感觉障碍，有15亿人在一生中受到这种疾病的影响。随着年龄的增长，某些类型的听力损失更加常见，因此，随着老龄化人口的增加，听力损失的负担预计会进一步上升。听力损失对生活质量、患者健康和安全具有重大影响，并对日益紧张的公共卫生服务提出了巨大的需求。为了准备和应对这场迅速加速的公共卫生危机，我们需要更好地了解不同类型的听力损失，以确定谁最有可能面临听力损失恶化的风险，以及哪些患者最有可能从新的治疗中受益。患者健康记录的数字化提供了一个令人兴奋的机会，可以使用计算机科学的最新进步方法来查看大量听力健康患者的数据并回答这些问题。该项目的另一个关键部分将查看鼓膜的临床照片。在社区中，可以评估耳膜外观的训练有素的专家的机会有限，而且转诊到耳鼻喉科专科服务往往需要很长时间。在全球范围内，这种情况在资源匮乏的国家甚至更糟。为了解决这个问题，我们建议开发一个自动程序来分析鼓膜的照片。临床图像也将被用来评估耳鼓的变化是否可以发出血管疾病和糖尿病的信号，就像眼睛进行视网膜筛查一样。耳朵是一个比眼睛更容易接近的区域，可以为筛查提供一个简单且经济高效的场所。方法我们将创建一个患者数据存储，作为标准NHS临床护理的一部分进行常规收集。这将包括人口统计细节、测试结果、测量结果和医疗条件的详细信息。一个强大的计算机程序将被用来分析这些数据，并描述不同类型的听力损失，以及这些听力损失类型如何随着时间的推移而变化。我们将进行进一步的分析，以确定这些听力损失亚型与其他疾病之间的联系，包括痴呆症、糖尿病、中风和高血压。在这项研究的第二部分，我们将使用一种新的医疗设备捕获的耳膜图片来开发和培训一个计算机程序，该程序可以识别耳鼻喉科专家评估的鼓膜的关键成分并进行分级。我们将使用这个程序结合提供的患者详细信息来探索耳鼓是否有变化可以预测糖尿病和心脏病的存在。反解放结果这项研究的关键目的是更好地了解听力损失的自然历史。确定患有严重听力损失的风险较高的患者对于资源规划、患者咨询和确定最有可能从新出现的治疗或临床试验中受益的人是重要的。找出听力损失和其他疾病之间的新联系，可以识别出那些有“风险”的患者，促使他们及早诊断，并作为一个机会，进行早期干预和促进生活方式的改变，以通过行为改变来转移或推迟这些疾病的发生。

Aims and Background to the researchHearing loss is the most common sensory disorder in humans with 1.5 billion people affected by this during their lifetime. Some types of hearing loss are more common as we get older and therefore the burden of hearing loss is predicted to rise further as our aging population increases. Hearing loss has a significant impact on quality of life, patient health and safety as well as placing a huge demand on increasingly stretched public health services.In order to prepare and respond to this rapidly accelerating public health crisis we need to better understand the different types of hearing loss to identify who is most at risk of both worsening hearing loss but also other associated medical conditions and also which patients are most likely to benefit from new treatments. The digitialisation of patient health records offers an exciting opportunity to use the latest advances in computer science methods to look at large amounts of hearing health patient data and answer these questions.Another key part of this project will look at clinical photographs of the ear drum. Access to trained specialists who can assess the appearance of ear drums is limited in the community and there are often long waits for referrals to specialty ENT services. This situation is even worse globally in resource-poor countries. To address this problem, we propose to develop an automated programme that analyse photographs of the ear drum. The clinical images will also be used to assess whether changes in the ear drum could signal the presence of vascular disease and diabetes, much like retinal screening is performed in the eye. The ear is a more readily accessible area than the eye and could provide an easy and cost-effective site for screening.MethodsWe will create a store of patient data that has been collected routinely as part of standard NHS clinical care. This will include demographic details, test results, measurements, and details of medical conditions. A powerful computer programme will be used to analyse this data and describe different types of hearing loss as well as how these hearing loss types change over time. We will perform further analysis to identify links between these hearing loss subtypes and other medical conditions including dementia, diabetes, stroke and high blood pressure.For the second part of this study, we will use pictures of ear drums captured by a new medical device to develop and train a computer programme that can identify and grade the key components of an ear drum that are assessed by ENT specialists. We will use this programme alongside supplied patient details to explore whether there are changes in the ear drum that can predict the presence of diabetes and heart disease.Anticipated OutcomesThe key aim of this research is to better understand the natural history of hearing loss. Identifying patients who are at higher risk of developing severe hearing loss is important for resource planning, patient counselling and identifying people who are most likely to benefit from emerging treatments or clinical trials. Identifying new associations between hearing loss and other conditions could identify patients who are "at risk" prompting earlier diagnosis and act as an opportunity for early intervention and the promotion of lifestyle modifications to divert or delay the onset of such conditions through behavioural change.