Real-world outcomes of proliferative diabetic retinopathy

项目总结： 增殖性糖尿病视网膜病变的真实结局 糖尿病视网膜病变导致的视力丧失仍然是工薪阶层可预防失明的主要原因 美国的成年人。晚期糖尿病视网膜病变称为增殖性糖尿病。 视网膜病变(PDR)。在许多患者中，与PDR相关的失明可以通过适当的和 及时诊断和治疗。不幸的是，一些PDR高危患者没有得到足够的治疗。 眼部护理。需要更多关于真实环境中的PDR结果的知识，以及 已发表的研究结果和现实世界的有效性。电子健康记录(EHR)被用于近 90%的门诊医生办公室，并且可以成为在真实世界环境中研究PDR的强大工具。这个 这项提案的目标是开发和验证基于电子病历的方法，以改善PDR的结果。这项研究 目标是：(1)在电子病历系统中使用结合了以下内容的自动方法对患有PDR的患者进行分类 结构化数据(例如，诊断代码、药物、实验室)和非结构化数据(例如，临床记录)，(2)用于预测 应用时变预测模型预测非增殖性糖尿病视网膜病变进展为PDR 协变量，以及(3)确定在全国大眼睛中治疗PDR的真实效果 数据集。这项研究将利用加州大学旧金山分校(UCSF)的数据 临床数据仓库，一个拥有100多万名患者的未识别的EHR，可以进行眼科检查 信息，以及智能视觉研究(IRIS)注册，这是一个全国性的综合眼科数据库 这包括来自美国15,000多家眼科提供商和100多万名PDR患者的数据。这个 本研究的创新方法和工具可应用于其他眼部疾病，以促进未来的EHR- 基于眼科的临床研究。候选人凯瑟琳·孙博士是一位眼科医生，她的长期- 学期目标是通过进行基于电子病历的实用主义研究眼科的真实世界临床结果 临床试验和使用大规模的EHR数据。虽然她拥有基本技能，但她还获得了 数据分析、生物医学信息学、生物统计学和高级临床试验方面的培训和课程 设计和实施将帮助她实现目标。她的优秀导师团队的主要导师 Nisha Acharya博士和共同导师Travis Porco博士和Joshua Stein博士，以及 加州大学旧金山分校的眼科和F.I.Proctor基金会将支持孙博士的发展 变成一家由R01资助的独立调查员。

PROJECT SUMMARY: Real-world outcomes of proliferative diabetic retinopathy Vision loss from diabetic retinopathy remains the leading cause of preventable blindness in working-aged adults in the United States (US). Advanced diabetic retinopathy is referred to as proliferative diabetic retinopathy (PDR). In many patients, blindness associated with PDR can be prevented with appropriate and timely diagnosis and treatment. Unfortunately, some patients at high risk for PDR are not receiving adequate eye care. More knowledge is needed about PDR outcomes in a real-world setting, and the differences between published study outcomes and real-world effectiveness. Electronic health records (EHRs) are used in nearly 90% of outpatient physician offices and can be a powerful tool for studying PDR in a real-world setting. The goal of this proposal is to develop and validate EHR-based methods to improve outcomes in PDR. The study aims are: (1) to classify patients with PDR in the EHR system using an automated method that incorporates structured (e.g., diagnosis code, medications, labs) and unstructured data (e.g., clinical notes), (2) to predict the progression of non-proliferative diabetic retinopathy to PDR using a forecasting model with time-varying covariates, and (3) to determine the real-world effectiveness of treatments for PDR in a large nationwide eye dataset. The study will utilize data from the University of California San Francisco’s (UCSF) De-Identified Clinical Data Warehouse, a de-identified EHR with over 1 million patients that has available eye exam information, and the Intelligent Research in Sight (IRIS) registry, a nationwide comprehensive eye database that includes data from over 15,000 eye providers in the US with over 1 million patients with PDR. The innovative methods and tools from this study can be applied to other eye conditions to facilitate future EHR- based clinical studies in ophthalmology. The candidate, Dr. Catherine Sun is an ophthalmologist whose long- term goal is to study real-world clinical outcomes in ophthalmology by conducting EHR-based pragmatic clinical trials and using large-scale EHR data. While she possesses the foundational skills, additional mentored training and coursework in data analytics, biomedical informatics, biostatistics, and advanced clinical trial design and implementation will help her reach her goals. Her outstanding mentorship team of primary mentor Dr. Nisha Acharya and co-mentors Dr. Travis Porco and Dr. Joshua Stein, and the exceptional environment of the Department of Ophthalmology and the F.I. Proctor Foundation at UCSF will support Dr. Sun’s development into an R01-funded independent investigator.