Comparing verbal autopsy cause of death findings as determined by physician coding and probabilistic modelling: a public health analysis of 54 000 deaths in Africa and Asia
Comparing verbal autopsy cause of death findings as determined by physician coding and probabilistic modelling: a public health analysis of 54 000 deaths in Africa and Asia
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DOI：
10.7189/jogh.05.010402
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发表时间：
2015-06-01
影响因子：
7.2
通讯作者：
Tollman, Stephen M.
中科院分区：
文献类型：
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作者：
Byass, Peter;Herbst, Kobus;Tollman, Stephen M.
民事登记和人口动态统计的覆盖范围在全球范围内各不相同，非洲和亚洲的大多数死亡要么没有登记，要么没有登记死因。一个重要的制约因素是，在没有医生参与的情况下，缺乏适用于登记死亡和确定死亡原因的工具。口头验尸（采访死亡的护理人员和证人，并将他们的信息解释为死亡原因）是唯一可用的解决办法。死因信息的自动解释的死因尸检数据是必不可少的快速，一致和负担得起的processing.Methods口头尸检档案，涵盖54 182例死亡来自5个非洲和亚洲国家的基础上，他们的地理，流行病学和方法的多样性，与现有的医生编码的死因归因。这些数据被统一到世卫组织2012年死因推断标准格式中，并使用InterVA-4模型进行处理。根据年龄组、性别和来源，计算了来自InterVA-4和医生编码的60个WHO 2012死因类别的死因特异性死亡率分数，并评估了两种方法的结果的一致性和死因类别分数的比率。作为替代指标，使用Wilcoxon配对符号秩检验和随机等效性的两个单侧检验。结果-InterVA-4和医生代码之间的整体一致性相关系数为0.83（95%CI 0.75至0.91），这增加到0.97（95%CI 0.96至0.99）时，艾滋病毒/艾滋病和肺结核死亡合并成一个单一的类别。按来源划分的InterVA-4和医生代码之间超过一半（53%）的原因类别比率在99%水平下与统一无显著差异，按年龄组增加至62%。Wilcoxon随机等效性检验也证明了equivalent.Conclusions这些研究结果显示了强大的一致性之间的InterVA-4和医生编码的结果在这个大而多样的数据集。虽然这些分析不能证明这两种方法构成绝对真理，但这些发现之间具有高度的公共卫生等效性。鉴于迫切需要从目前未登记死亡的环境中获取足够的死因数据，并且由于世卫组织2012年死因推断标准和InterVA-4工具代表了相对简单、廉价且可用的大规模确定死因的方法，因此它们应该被用作填补死因数据空白的当前首选工具。
Background Coverage of civil registration and vital statistics varies globally, with most deaths in Africa and Asia remaining either unregistered or registered without cause of death. One important constraint has been a lack of fit-for-purpose tools for registering deaths and assigning causes in situations where no doctor is involved. Verbal autopsy (interviewing care-givers and witnesses to deaths and interpreting their information into causes of death) is the only available solution. Automated interpretation of verbal autopsy data into cause of death information is essential for rapid, consistent and affordable processing.Methods Verbal autopsy archives covering 54 182 deaths from five African and Asian countries were sourced on the basis of their geographical, epidemiological and methodological diversity, with existing physician-coded causes of death attributed. These data were unified into the WHO 2012 verbal autopsy standard format, and processed using the InterVA-4 model. Cause-specific mortality fractions from InterVA-4 and physician codes were calculated for each of 60 WHO 2012 cause categories, by age group, sex and source.Results from the two approaches were assessed for concordance and ratios of fractions by cause category. As an alternative metric, the Wilcoxon matched-pairs signed ranks test with two one-sided tests for stochastic equivalence was used. Findings The overall concordance correlation coefficient between InterVA-4 and physician codes was 0.83 (95% CI 0.75 to 0.91) and this increased to 0.97 (95% CI 0.96 to 0.99) when HIV/AIDS and pulmonary TB deaths were combined into a single category. Over half (53%) of the cause category ratios between InterVA-4 and physician codes by source were not significantly different from unity at the 99% level, increasing to 62% by age group. Wilcoxon tests for stochastic equivalence also demonstrated equivalence.Conclusions These findings show strong concordance between InterVA-4 and physician-coded findings over this large and diverse data set. Although these analyses cannot prove that either approach constitutes absolute truth, there was high public health equivalence between the findings. Given the urgent need for adequate cause of death data from settings where deaths currently pass unregistered, and since the WHO 2012 verbal autopsy standard and InterVA-4 tools represent relatively simple, cheap and available methods for determining cause of death on a large scale, they should be used as current tools of choice to fill gaps in cause of death data.