Performance of InterVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards.
Performance of InterVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards.
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DOI：
10.1186/1478-7954-9-50
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发表时间：
2011-08-05
影响因子：
3.3
通讯作者：
Population Health Metrics Research Consortium (PHMRC)
中科院分区：
文献类型：
--
作者：
Lozano R;Freeman MK;James SL;Campbell B;Lopez AD;Flaxman AD;Murray CJ;Population Health Metrics Research Consortium (PHMRC)
InterVA是一种广泛传播的工具，用于使用口头尸检的信息进行死因归因。有几项研究试图验证该工具的一致性和准确性，但这些研究的主要局限性是，它们将通过医院记录审查或出院诊断确定的死亡原因与InterVA的结果进行了比较。这项研究提供了一个独特的机会，以评估InterVA的性能相比，医生认证的口头尸检（PCVA）和替代的自动化分析方法。使用临床诊断金标准选择12，542例死因推断病例，我们评估了InterVA在个体和人群水平上的性能，并将结果与PCVA进行比较，分别对成人，儿童和新生儿进行分析。根据Murray等人的建议，我们随机改变了500个测试数据集的原因组成，以了解该工具在不同设置中的性能。我们还将InterVA与另一种贝叶斯方法（简化症状模式（SSP））进行了对比，以了解该工具的优点和缺点。在所有年龄组中，InterVA在个体和人群水平上的表现都比PCVA差。在个体水平上，InterVA在成人、儿童和新生儿中的机会校正一致性分别为24.2%、24.9%和6.3%（不包括自由文本，考虑一个原因选择）。在人群水平上，InterVA实现了成人、儿童和新生儿的病因特异性死亡率分数准确度分别为0.546、0.504和0.404。与SSP的比较揭示了导致SSP的上级性能的四个特定特征。通过开发逐因模型（2%），使用所有项目而不是仅映射到InterVA项目的项目（7%），将概率分配给症状群（6%），以及使用经验而不是专家概率（高达8%）来实现机会校正一致性的增加。由于在缺乏可靠的生命登记系统的地区广泛使用口头尸检来了解疾病负担和确定卫生干预优先事项，因此对口头尸检的准确分析至关重要。虽然InterVA是一种负担得起的和可用的机制，用于使用口头尸检来分配死亡原因，但用户应该意识到其相对于其他方法的次优性能。
InterVA is a widely disseminated tool for cause of death attribution using information from verbal autopsies. Several studies have attempted to validate the concordance and accuracy of the tool, but the main limitation of these studies is that they compare cause of death as ascertained through hospital record review or hospital discharge diagnosis with the results of InterVA. This study provides a unique opportunity to assess the performance of InterVA compared to physician-certified verbal autopsies (PCVA) and alternative automated methods for analysis. Using clinical diagnostic gold standards to select 12,542 verbal autopsy cases, we assessed the performance of InterVA on both an individual and population level and compared the results to PCVA, conducting analyses separately for adults, children, and neonates. Following the recommendation of Murray et al., we randomly varied the cause composition over 500 test datasets to understand the performance of the tool in different settings. We also contrasted InterVA with an alternative Bayesian method, Simplified Symptom Pattern (SSP), to understand the strengths and weaknesses of the tool. Across all age groups, InterVA performs worse than PCVA, both on an individual and population level. On an individual level, InterVA achieved a chance-corrected concordance of 24.2% for adults, 24.9% for children, and 6.3% for neonates (excluding free text, considering one cause selection). On a population level, InterVA achieved a cause-specific mortality fraction accuracy of 0.546 for adults, 0.504 for children, and 0.404 for neonates. The comparison to SSP revealed four specific characteristics that lead to superior performance of SSP. Increases in chance-corrected concordance are attained by developing cause-by-cause models (2%), using all items as opposed to only the ones that mapped to InterVA items (7%), assigning probabilities to clusters of symptoms (6%), and using empirical as opposed to expert probabilities (up to 8%). Given the widespread use of verbal autopsy for understanding the burden of disease and for setting health intervention priorities in areas that lack reliable vital registrations systems, accurate analysis of verbal autopsies is essential. While InterVA is an affordable and available mechanism for assigning causes of death using verbal autopsies, users should be aware of its suboptimal performance relative to other methods.
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影响因子：
3.4
作者：
Byass, P;Fottrell, E;Van, DD
通讯作者：
Van, DD
影响因子：
5.5
作者：
Fottrell, Edward;Byass, Peter
通讯作者：
Byass, Peter
影响因子：
3.3
作者：
Flaxman, Abraham D.;Vahdatpour, Alireza;Murray, Christopher J. L.
通讯作者：
Murray, Christopher J. L.
影响因子：
3.3
作者：
Polprasert W;Rao C;Adair T;Pattaraarchachai J;Porapakkham Y;Lopez AD
通讯作者：
Lopez AD
DOI：
10.2471/blt.05.028712
发表时间：
2006-03-01
期刊：
Bulletin of the World Health Organization: International Journal of Public Health
影响因子：
--
作者：
Fantahun, Mesganaw;Fottrell, Edward;Byass, Peter
通讯作者：
Byass, Peter