Your browser doesn't support javascript.
loading
Validation of SmartVA using conventional autopsy: A study of adult deaths in Brazil.
Hart, John D; de André, Paulo Afonso; de André, Carmen Diva Saldiva; Adair, Tim; Barroso, Lucia Pereira; Valongueiro, Sandra; Bierrenbach, Ana Luiza; de Carvalho, Patrícia Ismael; Antunes, Maria Bernadete de Cerqueira; de Oliveira, Conceição Maria; Pereira, Luiz Alberto Amador; Minto, Cátia Martinez; Bezerra, Tânia Maria da Silva; Costa, Sérgio Parente; de Azevedo, Bárbara Araújo; de Lima, José Ricardo Alves; Mota, Denise Souza de Meira; Ramos, Ana Maria de Oliveira; de Souza, Maria de Fátima Marinho; da Silva, Luiz Fernando Ferraz; França, Elisabeth Barboza; McLaughlin, Deirdre; Riley, Ian D; Saldiva, Paulo Hilário Nascimento.
Afiliação
  • Hart JD; Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • de André PA; University of São Paulo, School of Medicine, São Paulo, São Paulo, Brazil.
  • de André CDS; University of São Paulo, Institute of Mathematics and Statistics, São Paulo, São Paulo, Brazil.
  • Adair T; Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Barroso LP; University of São Paulo, Institute of Mathematics and Statistics, São Paulo, São Paulo, Brazil.
  • Valongueiro S; Federal University of Pernambuco, Recife, Pernambuco, Brazil.
  • Bierrenbach AL; Sírio-Libanês Hospital, São Paulo, São Paulo, Brazil.
  • de Carvalho PI; Vital Strategies, São Paulo, São Paulo, Brazil.
  • Antunes MBC; Executive Secretary of Health Surveillance of the State of Pernambuco, Brazil.
  • de Oliveira CM; University of Pernambuco, Recife, Pernambuco, Brazil.
  • Pereira LAA; Executive Secretary of the Municipal Health Surveillance of Recife, Pernambuco, Brazil.
  • Minto CM; University of São Paulo, School of Medicine, São Paulo, São Paulo, Brazil.
  • Bezerra TMDS; São Paulo Health State Secretary, São Paulo, São Paulo, Brazil.
  • Costa SP; Secretary of State for Health, Recife, Pernambuco, Brazil.
  • de Azevedo BA; Health Surveillance, Municipal Department of Health, Olinda, Pernambuco, Brazil.
  • de Lima JRA; Secretary of State for Health, Recife, Pernambuco, Brazil.
  • Mota DSM; Recife Autopsy Service, Recife, Brazil.
  • Ramos AMO; Recife Autopsy Service, Recife, Brazil.
  • de Souza MFM; Federal University of Rio Grande do Norte, Health Sciences Center, Natal, Rio Grande do Norte, Brazil.
  • da Silva LFF; Natal Autopsy Service, Natal, Rio Grande do Norte, Brazil.
  • França EB; Vital Strategies, São Paulo, São Paulo, Brazil.
  • McLaughlin D; University of São Paulo, School of Medicine, São Paulo, São Paulo, Brazil.
  • Riley ID; São Paulo Autopsy Service, University of São Paulo, Sao Paulo, Brazil.
  • Saldiva PHN; Federal University of Minas Gerais, School of Medicine, Belo Horizonte, Minas Gerais, Brazil.
Lancet Reg Health Am ; 5: 100081, 2022 Jan.
Article em En | MEDLINE | ID: mdl-36776454
ABSTRACT

Background:

Accurate cause of death data are essential to guide health policy. However, mortality surveillance is limited in many low-income countries. In such settings, verbal autopsy (VA) is increasingly used to provide population-level cause of death data. VAs are now widely interpreted using the automated algorithms SmartVA and InterVA. Here we use conventional autopsy as the gold standard to validate SmartVA methodology.

Methods:

This study included adult deaths from natural causes in São Paulo and Recife for which conventional autopsy was indicated. VA was conducted with a relative of the deceased using an amended version of the SmartVA instrument to suit the local context. Causes of death from VA were produced using the SmartVA-Analyze program. Physician coded verbal autopsy (PCVA), conducted on the same questionnaires, and Global Burden of Disease Study data were used as additional comparators. Cause of death data were grouped into 10 broad causes for the validation due to the real-world utility of VA lying in identifying broad population cause of death patterns.

Findings:

The study included 2,060 deaths in São Paulo and 1,079 in Recife. The cause specific mortality fractions (CSMFs) estimated using SmartVA were broadly similar to conventional autopsy for cardiovascular diseases (46.8% vs 54.0%, respectively), cancers (10.6% vs 11.4%), infections (7.0% vs 10.4%) and chronic respiratory disease (4.1% vs 3.7%), causes accounting for 76.1% of the autopsy dataset. The SmartVA CSMF estimates were lower than autopsy for "Other NCDs" (7.8% vs 14.6%) and higher for diabetes (13.0% vs 6.6%). CSMF accuracy of SmartVA compared to autopsy was 84.5%. CSMF accuracy for PCVA was 93.0%.

Interpretation:

The results suggest that SmartVA can, with reasonable accuracy, predict the broad cause of death groups important to assess a population's epidemiological transition. VA remains a useful tool for understanding causes of death where medical certification is not possible.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research País/Região como assunto: America do sul / Brasil Idioma: En Revista: Lancet Reg Health Am Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research País/Região como assunto: America do sul / Brasil Idioma: En Revista: Lancet Reg Health Am Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Austrália