Automated versus physician assignment of cause of death for verbal autopsies: randomized trial of 9374 deaths in 117 villages in India
Automated versus physician assignment of cause of death for verbal autopsies: randomized trial of 9374 deaths in 117 villages in India
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DOI：
10.1186/s12916-019-1353-2
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发表时间：
2019-06-27
期刊：
影响因子：
9.3
通讯作者：
Clark, Samuel J.
中科院分区：
文献类型：
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作者：
Jha, Prabhat;Kumar, Dinesh;Clark, Samuel J.
背景医生指定死因（COD）的口头尸检通常用于医疗死亡证明不常见的情况。它仍然没有回答，如果自动化算法可以取代医生assignment.MethodsWe随机口头尸检采访死亡在印度农村的117个村庄，无论是医生或自动COD分配。24名经过培训的非专业（非医疗）测量员使用基于笔记本电脑的电子系统应用分配的方法。25名医生中的两名被随机分配，独立编码医生分配组中的死亡。（朴素贝叶斯分类器（NBC），King-Lu，InSilicoVA，InSilicoVA-NT，InterVA-4，和SmartVA）对自动化组中的每例死亡进行编码。主要结局与标准医生分配组中的COD分布一致。死亡被分配到医生（标准），和4723自动arms.ResultsThe两个手臂几乎相同的人口统计学和关键症状模式。对于成人、儿童和新生儿死亡，自动算法与标准的平均一致性分别为62%、56%和59%。自动算法显示出不一致的结果，即使是相对容易识别的原因，如道路交通伤害。自动算法低估了成年人的癌症和自杀死亡人数，高估了成年人和儿童的其他伤害。在所有年龄段中，与标准的平均加权一致性为62%（范围79-45%），最佳至最差的自动化算法为InterVA-4、InSilicoVA-NT、InSilicoVA、SmartVA、NBC和King-Lu。在自动化手臂的成人死亡的原因，个人水平的灵敏度是低的算法之间，但两个独立的医生在医生arm.ConclusionsWhile可取的，自动化的算法需要进一步的发展和严格的评估之间的高。registrationClinicalTrials.gov报告与医生口头尸检的COD分配配对，尽管有一些限制，仍然是一种可靠记录无人值守死亡的死亡模式的可行方法。2016年4月11日提交。
BackgroundVerbal autopsies with physician assignment of cause of death (COD) are commonly used in settings where medical certification of deaths is uncommon. It remains unanswered if automated algorithms can replace physician assignment.MethodsWe randomized verbal autopsy interviews for deaths in 117 villages in rural India to either physician or automated COD assignment. Twenty-four trained lay (non-medical) surveyors applied the allocated method using a laptop-based electronic system. Two of 25 physicians were allocated randomly to independently code the deaths in the physician assignment arm. Six algorithms (Naive Bayes Classifier (NBC), King-Lu, InSilicoVA, InSilicoVA-NT, InterVA-4, and SmartVA) coded each death in the automated arm. The primary outcome was concordance with the COD distribution in the standard physician-assigned arm. Four thousand six hundred fifty-one(4651) deaths were allocated to physician (standard), and 4723 to automated arms.ResultsThe two arms were nearly identical in demographics and key symptom patterns. The average concordances of automated algorithms with the standard were 62%, 56%, and 59% for adult, child, and neonatal deaths, respectively. Automated algorithms showed inconsistent results, even for causes that are relatively easy to identify such as road traffic injuries. Automated algorithms underestimated the number of cancer and suicide deaths in adults and overestimated other injuries in adults and children. Across all ages, average weighted concordance with the standard was 62% (range 79-45%) with the best to worst ranking automated algorithms being InterVA-4, InSilicoVA-NT, InSilicoVA, SmartVA, NBC, and King-Lu. Individual-level sensitivity for causes of adult deaths in the automated arm was low between the algorithms but high between two independent physicians in the physician arm.ConclusionsWhile desirable, automated algorithms require further development and rigorous evaluation. Lay reporting of deaths paired with physician COD assignment of verbal autopsies, despite some limitations, remains a practicable method to document the patterns of mortality reliably for unattended deaths.Trial registrationClinicalTrials.gov, NCT02810366. Submitted on 11 April 2016.