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使用HIV查试验的信号与切断比率来预测HIV感染

Yin-Feng Guo^1,2, Shui-Di Yan^1,2, Jia-Wen Xie^1,2

¹Center of Clinical Laboratory, School of Medicine, Zhongshan Hospital of Xiamen University, Xiamen University, Xiamen, China.

BMC infectious diseases

|December 13, 2023

概括

艾滋病毒查试验中的信号与切断 (S/CO) 比率可以有效预测艾滋病毒感染,减少重复和确认测试的需要. 这一发现对艾滋病毒检测策略具有重大公共卫生影响.

科学领域:

临床诊断临床诊断临床诊断
传染病流行病学传染病流行病学
生物统计学生物统计学

背景情况:

艾滋病毒查试验往往产生错误的阳性结果,需要进一步测试.
这增加了医疗保健成本和患者的焦虑.
需要改进的方法来准确确认艾滋病毒感染.

研究的目的:

为了评估艾滋病毒查试验的预测能力,对艾滋病毒感染的信号与截止 (S/CO) 比率进行预测.
为了建立一个最佳的S/CO比率切割值来预测艾滋病毒感染.
评估S/CO比率在完善艾滋病毒检测算法中的潜力.

主要方法:

门大学中山医院对艾滋病毒查阳性个体的回顾性分析.
评估S/CO比率与确诊的艾滋病毒感染状况之间的相关性.
接收器操作特征 (ROC) 曲线分析以确定最佳切断值.

主要成果:

总共有396,679名患者被分析,其中836名确诊感染艾滋病毒 (0.21%的患病率).
与未感染者相比,艾滋病毒感染者 (296.9) 的中位数S/CO比率显著高于未感染者 (2.41).
在ROC分析中,灵敏度为93.78%,特异性为93.12%,最佳S/CO切线为14.09 (AUC=0.9612).

结论:

艾滋病毒查试验S/CO比率可以准确预测艾滋病毒感染,潜在地减少了重新测试和确认测试的需要.
将S/CO比率分析集成到HIV测试算法中可以提高效率并降低成本.
这种方法为医疗和公共卫生艾滋病毒管理策略提供了显著的好处.

关键词:

艾滋病毒感染艾滋病毒感染敏感性和特异性敏感性和特异性信号与切断的比率.

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