Suppr超能文献

表面患病率,真实患病率。

The apparent prevalence, the true prevalence.

机构信息

Global Virus Network, Middle East Region, Shiraz, Iran.

Research Center for Health Sciences, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran.

出版信息

Biochem Med (Zagreb). 2022 Jun 15;32(2):020101. doi: 10.11613/BM.2022.020101.

Abstract

Serologic tests are important for conducting seroepidemiologic and prevalence studies. However, the tests used are typically imperfect and produce false-positive and false-negative results. This is why the seropositive rate (apparent prevalence) does not typically reflect the true prevalence of the disease or condition of interest. Herein, we discuss the way the true prevalence could be derived from the apparent prevalence and test sensitivity and specificity. A computer simulation based on the Monte-Carlo algorithm was also used to further examine a situation where the measured test sensitivity and specificity are also uncertain. We then complete our review with a real example. The apparent prevalence observed in many prevalence studies published in medical literature is a biased estimation and cannot be interpreted correctly unless we correct the value.

摘要

血清学检测对于开展血清流行病学和患病率研究非常重要。然而,这些检测方法通常并不完美,会产生假阳性和假阴性的结果。这就是为什么血清阳性率(表面患病率)通常不能反映所关注疾病或病症的真实患病率。在此,我们讨论了如何从表面患病率和检测灵敏度及特异性推导出真实患病率。我们还使用基于蒙特卡罗算法的计算机模拟进一步研究了在测量的检测灵敏度和特异性也不确定的情况下的情况。最后,我们用一个真实的例子来完成我们的综述。除非我们纠正这个数值,否则在许多发表在医学文献中的患病率研究中观察到的表面患病率是一个有偏差的估计,不能正确解释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8247/9195606/6a6aae3ace99/bm-32-2-020101-f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验