使用电子健康记录数据在艾滋病毒感染者中识别临床表型
Anoop Mayampurath1, Sheriff Isakka2, Joseph A Mason3
1Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA.
AIDS and behavior
|October 6, 2025
概括
在艾滋病毒护理中确定患者子组对于减少对随访的损失 (LTFU) 至关重要. 两种不同的临床表型与LTFU风险的增加显著相关,突出了针对性干预的机会.
科学领域:
- 公共卫生 公共卫生
- 临床医学 临床医学
- 数据科学数据科学数据科学
背景情况:
- 失去随访 (LTFU) 影响近一半的艾滋病毒感染者 (PWH),阻碍有效的护理.
- 电子健康记录 (EHR) 提供了丰富的数据,以了解艾滋病毒管理中的患者异质性.
研究的目的:
- 使用EHR数据在PWH中识别不同的临床表型.
- 评估这些表型与艾滋病毒护理中的LTFU之间的关联.
主要方法:
- 隐藏类分析了4,316次来自849名成年人在城市艾滋病毒诊所的访问 (2017-2020年).
- 提取了人口,社会史,实验室,诊断和临床笔记的特征.
- 后勤回归分析了与LTFU和高病毒负载的关联.
主要成果:
- 确定了六个不同的患者亚组 (表型).
- 现型2 (年轻男性,新患者) 显示LTFU风险最高 (OR 1.57) 和病毒载量增加 (OR 1.74).
- 现型4 (白人/西班牙裔,更少提到物质使用) 增加了LTFU风险 (OR1.39),但降低了未抑制的病毒载荷风险 (OR0.65).
结论:
- 在城市艾滋病毒诊所环境中,确定了六种临床相关的PWH表型.
- 两种表型与LTFU风险增加有显著关联.
- 结果可以指导量身定制的干预措施,以改善在艾滋病毒护理中的保留.
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