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

项目总结 新冠肺炎疫情给艾滋病病毒感染者带来了沉重的负担。基于15,522年的数据 来自24个国家的HIV和SARS-CoV-2混合感染住院患者，最近的世界卫生组织 世界卫生组织(WHO)的报告首次证实，艾滋病毒是严重急性呼吸综合征的独立危险因素 新冠肺炎。尽管艾滋病毒携带者出现严重新冠肺炎临床病程的风险普遍较高，但 SARS-CoV-2与艾滋病毒感染之间的相互作用尚不清楚。例如，新冠肺炎在中国的严重性 艾滋病毒携带者与某些共病相关，其中一些共病更多 在HIV患者中的流行程度高于其他人群。然而，几个相互矛盾的发现表明 合并症在新冠肺炎严重程度中的主导作用，与艾滋病毒感染无关。有低收入的个人 CD_4~+T细胞计数(例如，200~500个/µL)和未抑制的病毒载量与严重的临床相关 当然，然而，在新冠肺炎接触的背景下，抗逆转录病毒治疗(ART)暴露和坚持的作用 需要进行检查。合并感染的严重临床病程的危险因素尚不确定，因为 新冠肺炎严重程度相同或相近的个体表现出不同的临床特征。填满 为了解决这些知识差距，这项研究将为艾滋病毒/SARS患者建立一个基于电子健康记录的队列- CoV-2合并感染并开发基于EHR的大规模数据挖掘以检查HIV与 SARS-CoV-2感染，系统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试点临床测试 决策支持(CDS)原型，帮助提供者在现实世界中筛查和转介高危患者 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.