Menéndez Clara, Quintó Llorenç, Castillo Paola, Carrilho Carla, Ismail Mamudo R, Lorenzoni Cesaltina, Fernandes Fabiola, Hurtado Juan Carlos, Rakislova Natalia, Munguambe Khátia, Maixenchs Maria, Macete Eusebio, Mandomando Inacio, Martínez Miguel J, Bassat Quique, Alonso Pedro L, Ordi Jaume
Barcelona Institute for Global Health (ISGlobal), Hospital Clinic of Barcelona, Universitat de Barcelona, Barcelona, Spain.
Centro de Investigação em Saúde de Manhiça, Maputo, Mozambique.
Gates Open Res. 2021 May 5;4:55. doi: 10.12688/gatesopenres.13132.3. eCollection 2020.
: Accurate information on causes of death (CoD) is essential to estimate burden of disease, track global progress, prioritize cost-effective interventions, and inform policies to reduce mortality. In low-income settings, where a significant proportion of deaths take place at home or in poorly-resourced peripheral health facilities, data on CoD often relies on verbal autopsies (VAs). Validations of VAs have been performed against clinical diagnosis, but never before against an acceptable gold standard: the complete diagnostic autopsy (CDA). We have validated a computer-coded verbal autopsy method -the InterVA- using individual and population metrics to determine CoD against the CDA, in 316 deceased patients of different age groups who died in a tertiary-level hospital in Maputo, Mozambique between 2013 and 2015. We found a low agreement of the model across all age groups at the individual (kappa statistic ranging from -0.030 to 0.232, lowest in stillbirths and highest in adults) and population levels (chance-corrected cause-specific mortality fraction accuracy ranging from -1.00 to 0.62, lowest in stillbirths, highest in children). The sensitivity in identifying infectious diseases was low (0% for tuberculosis, diarrhea, and disseminated infections, 32% for HIV-related infections, 33% for malaria and 36% for pneumonia). Of maternal deaths, 26 were assigned to eclampsia but only four patients actually died of eclampsia. These findings do not lead to building confidence in current estimates of CoD. They also call to the need to implement autopsy methods where they may be feasible, and to improve the quality and performance of current VA techniques.
准确的死因信息对于估计疾病负担、跟踪全球进展、确定具有成本效益的干预措施优先级以及为降低死亡率的政策提供依据至关重要。在低收入环境中，很大一部分死亡发生在家中或资源匮乏的基层卫生设施，死因数据通常依赖于口头尸检（VA）。VA已针对临床诊断进行了验证，但此前从未针对可接受的金标准：完整诊断尸检（CDA）进行过验证。我们在莫桑比克马普托一家三级医院2013年至2015年间死亡的316名不同年龄组的死者中，使用个体和人群指标，针对CDA验证了一种计算机编码的口头尸检方法——InterVA，以确定死因。我们发现该模型在所有年龄组的个体层面（kappa统计量范围为-0.030至0.232，死产组最低，成人组最高）和人群层面（机会校正的特定病因死亡率分数准确性范围为-1.00至0.62，死产组最低，儿童组最高）的一致性较低。识别传染病的敏感性较低（结核病、腹泻和播散性感染为0%，艾滋病毒相关感染为32%，疟疾为33%，肺炎为36%）。在孕产妇死亡中，26例被判定为子痫，但实际上只有4例患者死于子痫。这些发现无法让人对当前的死因估计建立信心。它们还呼吁在可行的情况下实施尸检方法，并提高当前VA技术的质量和性能。
