Fecho Karamarie, Ahalt Stanley C, Knowles Michael, Krishnamurthy Ashok, Leigh Margaret, Morton Kenneth, Pfaff Emily, Wang Max, Yi Hong
Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Front Artif Intell. 2022 Jun 28;5:918888. doi: 10.3389/frai.2022.918888. eCollection 2022.
Research on rare diseases has received increasing attention, in part due to the realized profitability of orphan drugs. Biomedical informatics holds promise in accelerating translational research on rare disease, yet challenges remain, including the lack of diagnostic codes for rare diseases and privacy concerns that prevent research access to electronic health records when few patients exist. The Integrated Clinical and Environmental Exposures Service (ICEES) provides regulatory-compliant open access to electronic health record data that have been integrated with environmental exposures data, as well as analytic tools to explore the integrated data. We describe a proof-of-concept application of ICEES to examine demographics, clinical characteristics, environmental exposures, and health outcomes among a cohort of patients enriched for phenotypes associated with cystic fibrosis (CF), idiopathic bronchiectasis (IB), and primary ciliary dyskinesia (PCD). We then focus on a subset of patients with CF, leveraging the availability of a diagnostic code for CF and serving as a benchmark for our development work. We use ICEES to examine select demographics, co-diagnoses, and environmental exposures that may contribute to poor health outcomes among patients with CF, defined as emergency department or inpatient visits for respiratory issues. We replicate current understanding of the pathogenesis and clinical manifestations of CF by identifying co-diagnoses of asthma, chronic nasal congestion, cough, middle ear disease, and pneumonia as factors that differentiate patients with poor health outcomes from those with better health outcomes. We conclude by discussing our preliminary findings in relation to other published work, the strengths and limitations of our approach, and our future directions.
对罕见病的研究日益受到关注,部分原因是孤儿药已实现盈利。生物医学信息学有望加速罕见病的转化研究,但挑战依然存在,包括缺乏罕见病的诊断编码以及隐私问题,这使得在患者数量稀少时难以获取电子健康记录进行研究。综合临床与环境暴露服务(ICEES)提供符合法规的开放访问权限,可获取已与环境暴露数据整合的电子健康记录数据,以及用于探索整合后数据的分析工具。我们描述了ICEES的一个概念验证应用,以研究一组因与囊性纤维化(CF)、特发性支气管扩张(IB)和原发性纤毛运动障碍(PCD)相关的表型而富集的患者的人口统计学特征、临床特征、环境暴露和健康结局。然后,我们聚焦于CF患者子集,利用CF诊断编码的可用性,并将其作为我们开发工作的基准。我们使用ICEES来研究可能导致CF患者健康结局不佳(定义为因呼吸问题到急诊科就诊或住院)的特定人口统计学特征、合并诊断和环境暴露。我们通过确定哮喘、慢性鼻充血、咳嗽、中耳疾病和肺炎的合并诊断作为区分健康结局不佳患者和健康结局较好患者的因素,复制了目前对CF发病机制和临床表现的认识。我们通过讨论我们的初步发现与其他已发表工作的关系、我们方法的优势和局限性以及我们未来的方向来得出结论。