Global network for women's and children's health research: a system for low-resource areas to determine probable causes of stillbirth, neonatal, and maternal death.
Global network for women's and children's health research: a system for low-resource areas to determine probable causes of stillbirth, neonatal, and maternal death.
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DOI：
10.1186/s40748-015-0012-7
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Goldenberg RL
中科院分区：
文献类型：
--
作者：
McClure EM;Bose CL;Garces A;Esamai F;Goudar SS;Patel A;Chomba E;Pasha O;Tshefu A;Kodkany BS;Saleem S;Carlo WA;Derman RJ;Hibberd PL;Liechty EA;Hambidge KM;Krebs NF;Bauserman M;Koso-Thomas M;Moore J;Wallace DD;Jobe AH;Goldenberg RL
需要确定死亡原因，以制定减少孕产妇死亡、死产和新生儿死亡的战略，特别是在98%的死亡发生在资源匮乏的环境中。大多数现有的分类系统是为高收入环境设计的，在那里可以进行广泛的测试。作为一种替代办法而开发的口头尸检或审计需要大量时间，而且对于基于人口的评价来说一般不可行。此外，由于大多数分类取决于用户，分类的可靠性随时间和环境而变化。因此，我们试图开发基于最少数据的孕产妇、胎儿和新生儿死亡率分类系统，以便为低资源环境提供可靠的死因估计。在六个低资源国家（印度，巴基斯坦，危地马拉，刚果民主共和国，赞比亚和肯尼亚），我们评估了在产前护理和分娩时常规收集的数据，这些数据可以通过采访，观察或基本设备从母亲，非专业保健提供者或家庭获得，以告知死亡原因。使用这些以标准方式收集的基本数据，我们开发了一种算法，可以通过计算机编程确定死因。产妇死亡原因（创伤、流产、出血、感染和妊娠高血压疾病）、死产（产伤、先天性异常、感染、窒息、早产并发症）和新生儿死亡原因（先天性异常、感染、窒息、早产并发症）是根据现有的死因分类，并与世界卫生组织国际疾病分类系统相一致。我们的系统分配产妇，胎儿和新生儿死亡的原因使用家庭或非专业医疗服务提供者的基本数据，通过算法分配死亡原因，以消除不一致和偏见的来源。其主要优势是一致性，透明度和跨时间或地区的可比性，对医疗保健系统的负担最小。这一系统将对确定资源匮乏环境中的死亡原因作出重要贡献。
Determining cause of death is needed to develop strategies to reduce maternal death, stillbirth, and newborn death, especially for low-resource settings where 98% of deaths occur. Most existing classification systems are designed for high income settings where extensive testing is available. Verbal autopsy or audits, developed as an alternative, are time-intensive and not generally feasible for population-based evaluation. Furthermore, because most classification is user-dependent, reliability of classification varies over time and across settings. Thus, we sought to develop classification systems for maternal, fetal and newborn mortality based on minimal data to produce reliable cause-of-death estimates for low-resource settings. In six low-resource countries (India, Pakistan, Guatemala, DRC, Zambia and Kenya), we evaluated data which are collected routinely at antenatal care and delivery and could be obtained with interview, observation, or basic equipment from the mother, lay-health provider or family to inform causes of death. Using these basic data collected in a standard way, we then developed an algorithm to assign cause of death that could be computer-programmed. Causes of death for maternal (trauma, abortion, hemorrhage, infection and hypertensive disease of pregnancy), stillbirth (birth trauma, congenital anomaly, infection, asphyxia, complications of preterm birth) and neonatal death (congenital anomaly, infection, asphyxia, complications of preterm birth) are based on existing cause of death classifications, and compatible with the World Health Organization International Classification of Disease system. Our system to assign cause of maternal, fetal and neonatal death uses basic data from family or lay-health providers to assign cause of death by an algorithm to eliminate a source of inconsistency and bias. The major strengths are consistency, transparency, and comparability across time or regions with minimal burden on the healthcare system. This system will be an important contribution to determining cause of death in low-resource settings.