Curating a Knowledge Base for Individuals with Coinfection of HIV and SARS-CoV-2: EHR-based Data Mining

项目摘要 COVID-19大流行给艾滋病毒感染者带来沉重负担。根据15，522份数据 最近，世界卫生组织（WHO）对来自24个国家的艾滋病毒和SARS-CoV-2合并感染的住院患者进行了调查， 世卫组织（WHO）的报告首次证实，艾滋病病毒是导致严重 新冠肺炎。尽管艾滋病毒感染者发生严重COVID-19临床病程的风险普遍较高， SARS-CoV-2和HIV感染之间的相互作用尚不清楚。例如，2019年COVID-19的严重程度 HIV感染者与某些合并症相关，其中一些合并症更严重， 艾滋病病毒感染者的比例高于其他人群。然而，一些相互矛盾的发现表明， 合并症在COVID-19严重程度中的主要作用，无论是否感染HIV。低下者 CD 4 + T细胞计数（例如，<200~500 cells/µL）和未抑制的病毒载量与严重的临床 当然，在COVID-19暴露的背景下，抗逆转录病毒治疗（ART）暴露和依从性的作用 需要检查。合并感染的严重临床过程的风险因素尚未确定， COVID-19严重程度相同或相似的个体表现出不同的临床特征。填补 为了解决这些知识差距，本研究将为艾滋病毒/SARS患者建立一个基于EHR的队列， CoV-2合并感染，并开发基于EHR的大规模数据挖掘，以研究HIV与 SARS-CoV-2感染，并系统地识别和验证导致严重临床病程的因素 合并感染的可能性最终，收集的临床证据将被实施并用于临床试验 决策支持（CDS）原型，以帮助提供者在现实世界中筛选和转诊高危患者 诊所。

PROJECT SUMMARY The COVID-19 pandemic has cast a heavy burden on individuals with HIV infection. Based on data of 15,522 hospitalized patients with the coinfection of HIV and SARS-CoV-2 from 24 countries, a recent World Health Organization (WHO) report for the first time confirmed that HIV to be an independent risk factor for severe COVID-19. Despite a generally high risk of severe COVID-19 clinical course in individuals with HIV, the interactions between SARS-CoV-2 and HIV infections remain unclear. For example, the severity of COVID-19 in individuals with HIV is correlated with certain comorbidities in which some of these comorbidities are more prevalent in patients with HIV than other populations. Yet, several contradictory findings suggested the predominant role of comorbidities in the severity of COVID-19 regardless of HIV infection. Individuals with low CD4+ T-cell count (e.g., <200~500 cells/µL) and unsuppressed viral load are associated with severe clinical course, yet the role of antiretroviral therapy (ART) exposure and adherence in the context of COVID-19 exposure needs to be examined. Risk factors for the severe clinical course of the coinfection are undetermined because individuals with the same or similar severity level of COVID-19 show different clinical characteristics. To fill address these knowledge gaps, this study will establish an EHR-based cohort for individuals with HIV/SARS- CoV-2 coinfection and develop large-scale EHR-based data mining to examine the interactions between HIV and SARS-CoV-2 infections and systematically identify and validate factors contributing to the severe clinical course of the coinfection. Ultimately, collected clinical evidence will be implemented and used to pilot test a Clinical Decision Support (CDS) prototype to assist providers in screening and referral of at-risk patients in real-world clinics.