Kalter Henry D, Roubanatou Abdoulaye-Mamadou, Koffi Alain, Black Robert E
Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Ministry of Health, Niamey, Niger.
J Glob Health. 2015 Jun;5(1):010415. doi: 10.7189/jogh.05.010415.
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.
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.
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 (χ(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.
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.
本研究是由世界卫生组织/联合国儿童基金会支持的儿童健康流行病学参考小组（CHERG）开展的一系列口头尸检调查之一，目的是直接估算撒哈拉以南非洲高优先级国家新生儿和儿童死亡原因。该研究的目的是确定尼日尔新生儿（0 - 27天）和儿童（1 - 59个月）死亡的原因分布情况。
对2011年尼日尔国家死亡率调查确定的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了口头尸检访谈。使用两种方法确定每例死亡的原因：按层次排列的计算机化专家算法以及为每个儿童填写死亡证明的医生。将两种方法的结果相互比较，并进行合理性检查以评估哪种方法更可取。讨论了本研究的一些直接测量结果与CHERG建模的死亡原因估计值的比较情况。
专家算法和医生确定的新生儿死亡原因分布相似，两种方法的前三大原因相同，且除两个其他原因外，所有其他原因在彼此的一个等级范围内。虽然儿童死亡原因的差异更大，但通过分析算法标准以及医生对所需最低诊断标准的应用，通常可以辨别原因。在比较中纳入所有算法（主要和共病）和医生（直接、根本和促成）诊断可最大程度减少差异，11项新生儿诊断中有5项、13项儿童诊断中有9项的kappa系数大于0.40。通过算法诊断，早发型新生儿感染与母亲感染显著相关（χ(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对应。
在国家死亡率调查背景下进行的口头尸检可提供新生儿和儿童死亡原因分布的有用估计值。虽然当前研究发现专家算法和医生分析之间有合理的一致性，但也证明了两种算法诊断的更大合理性，需要进行验证工作以确定研究结果。直接的大规模死因测量可以补充、加强并在某些情况下可能比建模估计更可取。
