Imperial College, London, UK.
J Epidemiol Community Health. 2010 Apr;64(4):330-4. doi: 10.1136/jech.2008.081554. Epub 2009 Oct 23.
Verbal autopsy is currently the only option for obtaining cause of death information in most populations with a widespread HIV/AIDS epidemic.
With the use of a data-driven algorithm, a set of criteria for classifying AIDS mortality was trained. Data from two longitudinal community studies in Tanzania and Zimbabwe were used, both of which have collected information on the HIV status of the population over a prolonged period and maintained a demographic surveillance system that collects information on cause of death through verbal autopsy. The algorithm was then tested in different times (two phases of the Zimbabwe study) and different places (Tanzania and Zimbabwe).
The trained algorithm, including nine signs and symptoms, performed consistently based on sensitivity and specificity on verbal autopsy data for deaths in 15-44-year-olds from Zimbabwe phase I (sensitivity 79%; specificity 79%), phase II (sensitivity 83%; specificity 75%) and Tanzania (sensitivity 75%; specificity 74%) studies. The sensitivity dropped markedly for classifying deaths in 45-59-year-olds.
Verbal autopsy can consistently measure AIDS mortality with a set of nine criteria. Surveillance should focus on deaths that occur in the 15-44-year age group for which the method performs reliably. Addition of a handful of questions related to opportunistic infections would enable other widely used verbal autopsy tools to apply this validated method in areas for which HIV testing and hospital records are unavailable or incomplete.
在艾滋病广泛流行的大多数地区,目前只有死因推断(verbal autopsy)才能获得死亡原因信息。
利用数据驱动算法,制定了一套用于分类艾滋病死亡的标准。我们使用了来自坦桑尼亚和津巴布韦两项纵向社区研究的数据,这两项研究都在较长时间内收集了人群的艾滋病毒状况信息,并建立了人口监测系统,通过死因推断收集死亡原因信息。然后,我们在不同时期(津巴布韦研究的两个阶段)和不同地点(坦桑尼亚和津巴布韦)对该算法进行了测试。
训练有素的算法包括 9 个体征和症状,根据津巴布韦第一阶段(15-44 岁人群的敏感性为 79%,特异性为 79%)、第二阶段(敏感性为 83%,特异性为 75%)和坦桑尼亚(敏感性为 75%,特异性为 74%)研究的死因推断数据,在敏感性和特异性方面表现一致。对于分类 45-59 岁人群的死亡,敏感性显著下降。
死因推断可以使用一套 9 项标准来一致地衡量艾滋病死亡率。监测应重点关注在 15-44 岁年龄组中可靠发生的死亡事件,因为该方法在此年龄组中的应用效果可靠。添加少量与机会性感染相关的问题,可以使其他广泛使用的死因推断工具能够在缺乏艾滋病毒检测和医院记录或记录不完整的地区应用这一经过验证的方法。