Direct estimates of national neonatal and child cause-specific mortality proportions in Niger by expert algorithm and physician-coded analysis of verbal autopsy interviews
Direct estimates of national neonatal and child cause-specific mortality proportions in Niger by expert algorithm and physician-coded analysis of verbal autopsy interviews
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DOI：
10.7189/jogh.05.010415
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发表时间：
2015-06-01
影响因子：
7.2
通讯作者：
Black, Robert E.
中科院分区：
文献类型：
--
作者：
Kalter, Henry D.;Roubanatou, Abdoulaye-Mamadou;Black, Robert E.
背景 这项研究是世界卫生组织/联合国儿童基金会支持的儿童健康流行病学参考小组（CHERG）进行的一系列口头尸检调查之一，旨在直接估计撒哈拉以南非洲高度优先国家的新生儿和儿童死亡原因。本研究的目的是确定尼日尔新生儿（0-27 天）和儿童（1-59 个月）死亡率的原因分布。 方法 对 2011 年尼日尔全国死亡率调查确定的 2007 年至 2010 年期间 453 例新生儿死亡和 620 例儿童死亡的随机样本进行口头尸检访谈。使用两种方法确定每个死亡的原因：按层次结构排列的计算机专家算法以及医生为每个孩子填写的死亡证明。对两种方法的结果进行了比较，并进行了合理性检查以评估哪种方法是首选方法。讨论了本研究的一些直接测量值与 CHERG 模型死因估计的比较。 结果 通过专家算法和医生确定的新生儿死亡原因分布相似，两种方法得出的前三个原因相同，除两个其他原因外，所有其他原因都在一个等级内。尽管儿童死亡原因差异较大，但通常可以通过分析算法标准以及医生应用所需的最低诊断标准来辨别原因。在比较中包括所有算法（原发性和共病）和医生（直接、基础和贡献）诊断，可以最大限度地减少差异，11 例新生儿诊断中的 5 例和 13 例儿童诊断中的 9 例的 kappa 系数大于 0.40。通过算法诊断，早发型新生儿感染与孕产妇感染显着相关（chi(2) = 13.2，P < 0.001），儿童脑膜炎死亡的地理分布与脑膜炎监测病例和死亡的地理分布密切相关。 结论 在全国死亡率调查背景下进行的口头尸检可以对新生儿和儿童死亡的原因分布进行有用的估计。虽然当前的研究发现专家算法和医生分析之间存在合理的一致性，但它也证明了两种算法诊断的更大合理性，并且需要验证工作来确定研究结果。对死亡原因的直接、大规模测量可以加强补充，并且在某些情况下可能优于模型估计。
Background This study was one of a set of verbal autopsy investigations undertaken by the WHO/UNCEF-supported Child Health Epidemiology Reference Group (CHERG) to derive direct estimates of the causes of neonatal and child deaths in high priority countries of sub-Saharan Africa. The objective of the study was to determine the cause distributions of neonatal (0-27 days) and child (1-59 months) mortality in Niger.Methods Verbal autopsy interviews were conducted of random samples of 453 neonatal deaths and 620 child deaths from 2007 to 2010 identified by the 2011 Niger National Mortality Survey. The cause of each death was assigned using two methods: computerized expert algorithms arranged in a hierarchy and physician completion of a death certificate for each child. The findings of the two methods were compared to each other, and plausibility checks were conducted to assess which is the preferred method. Comparison of some direct measures from this study with CHERG modeled cause of death estimates are discussed.Findings The cause distributions of neonatal deaths as determined by expert algorithms and the physician were similar, with the same top three causes by both methods and all but two other causes within one rank of each other. Although child causes of death differed more, the reasons often could be discerned by analyzing algorithmic criteria alongside the physician's application of required minimal diagnostic criteria. Including all algorithmic (primary and co-morbid) and physician (direct, underlying and contributing) diagnoses in the comparison minimized the differences, with kappa coefficients greater than 0.40 for five of 11 neonatal diagnoses and nine of 13 child diagnoses. By algorithmic diagnosis, early onset neonatal infection was significantly associated (chi(2) = 13.2, P < 0.001) with maternal infection, and the geographic distribution of child meningitis deaths closely corresponded with that for meningitis surveillance cases and deaths.Conclusions Verbal autopsy conducted in the context of a national mortality survey can provide useful estimates of the cause distributions of neonatal and child deaths. While the current study found reasonable agreement between the expert algorithm and physician analyses, it also demonstrated greater plausibility for two algorithmic diagnoses and validation work is needed to ascertain the findings. Direct, large-scale measurement of causes of death complement, can strengthen, and in some settings may be preferred over modeled estimates.