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用"我们所有人"研究计划进行计算表型化:识别艾滋病毒感染者或艾滋病毒感染风险较低的人群

Xueying Yang^1,2, Jiajia Zhang^1,3, Ruilie Cai^1,3

¹South Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, United States.

|August 24, 2023

概括

研究人员在我们所有人 (AoU) 数据库中确定了艾滋病毒感染者 (PWH) 和暴露前预防 (PrEP) 用户. 这种计算表型化方法整合了用于艾滋病毒研究的电子健康记录和调查数据.

科学领域:

生物医学信息学生物医学信息学
公共卫生公共卫生
临床研究临床研究

背景情况:

我们所有人 (AoU) 数据库为了解健康状况提供了丰富的资源.
准确识别特定的患者队列,如艾滋病毒感染者 (PWH) 和暴露前预防 (PrEP) 用户,对于有针对性的研究至关重要.
在 AoU 数据库中整合不同的数据源可以提高队列识别的准确性.

研究的目的:

在我们所有人 (AoU) 数据库中开发和验证一种计算表型化方法,用于识别艾滋病毒感染者 (PWH) 和暴露前预防 (PrEP) 用户.
为了利用电子健康记录 (EHR) 数据和自我报告的调查数据进行全面的队列识别.
通过使用 AoU 数据库,为未来与艾滋病毒相关的研究建立一个框架.

主要方法:

计算表型被用来识别PWH和PrEP使用者.
包括标准是基于特定的条件,实验室测量,或药物记录在EHR数据中.
通过在自报调查数据中的具体问题来实现确认.

主要成果:

该研究分析了截至2022年7月1日的AoU数据库数据.
总共有4575个确定的和3092个可能的成年PWH被确定.
此外,还确定了564名PrEP使用者. 最常见的PWH鉴定方法包括药物和疾病的组合 (43.4%) 和单独的药物暴露 (28.6%).

结论:

开发的计算表型化方法有效地在AoU数据库中识别PWH和PrEP用户.
这种方法为使用AoU数据进行与艾滋病毒相关的研究的研究人员提供了有价值的框架.
电子健康记录和调查数据的整合提高了艾滋病毒研究队列识别的精度.

关键词:

我们所有人,我们所有人艾滋病毒/艾滋病病毒/艾滋病病毒现型定制现型定制现型定制代表人数不足代表人数不足

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