Evidence map›Paper›PMID 35421964›Full record

ArticleBMC public health2022

Validation of physician certified verbal autopsy using conventional autopsy: a large study of adult non-external causes of death in a metropolitan area in Brazil.

Carmen Diva Saldiva de André, Ana Luiza Bierrenbach, Lucia Pereira Barroso, Paulo Afonso de André, Lisie Tocci Justo, Luiz Alberto Amador Pereira, Mauro T Taniguchi, Cátia Martinez Minto, Pedro Losco Takecian, Leonardo Tadashi Kamaura and 10 more

Abstract read
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Carmen Diva Saldiva de AndréUniversity of São Paulo, Institute of Mathematics and Statistics, São Paulo, Brazil.
Ana Luiza BierrenbachSírio-Libanês Hospital, São Paulo, Brazil.
Lucia Pereira BarrosoUniversity of São Paulo, Institute of Mathematics and Statistics, São Paulo, Brazil.
Paulo Afonso de AndréDepartment of Pathology, University of São Paulo School of Medicine, Av. Dr. Arnaldo, 455 1st floor Room 1155, São Paulo, SP, 01246-903, Brazil.
Lisie Tocci JustoDepartment of Pathology, University of São Paulo School of Medicine, Av. Dr. Arnaldo, 455 1st floor Room 1155, São Paulo, SP, 01246-903, Brazil.
Luiz Alberto Amador PereiraDepartment of Pathology, University of São Paulo School of Medicine, Av. Dr. Arnaldo, 455 1st floor Room 1155, São Paulo, SP, 01246-903, Brazil.
Mauro T TaniguchiIndependent consultant, São Paulo, Brazil.
Cátia Martinez MintoSão Paulo Health State Secretary, São Paulo, Brazil.
Pedro Losco TakecianUniversity of São Paulo, Institute of Mathematics and Statistics, São Paulo, Brazil.
Leonardo Tadashi KamauraUniversity of São Paulo, Institute of Mathematics and Statistics, São Paulo, Brazil.
João Eduardo FerreiraUniversity of São Paulo, Institute of Mathematics and Statistics, São Paulo, Brazil.
Riley H HazardMelbourne School of Population and Global Health, The University of Melbourne, Carlton, VIC, Australia.
Deirdre MclaughlinMelbourne School of Population and Global Health, The University of Melbourne, Carlton, VIC, Australia.
Ian RileyMelbourne School of Population and Global Health, The University of Melbourne, Carlton, VIC, Australia.
Alan D LopezMelbourne School of Population and Global Health, The University of Melbourne, Carlton, VIC, Australia.
Ana Maria de Oliveira RamosFederal University of Rio Grande do Norte, Health Sciences Center, Natal, Brazil.
Maria de Fatima Marinho de SouzaVital Strategies, São Paulo, Brazil.
Elisabeth Barboza FrançaFederal University of Minas Gerais, School of Medicine, Belo Horizonte, Brazil.
Paulo Hilário Nascimento SaldivaDepartment of Pathology, University of São Paulo School of Medicine, Av. Dr. Arnaldo, 455 1st floor Room 1155, São Paulo, SP, 01246-903, Brazil.
Luiz Fernando Ferraz da SilvaDepartment of Pathology, University of São Paulo School of Medicine, Av. Dr. Arnaldo, 455 1st floor Room 1155, São Paulo, SP, 01246-903, Brazil. burns@usp.br.ORCID 0000-0002-0181-6357

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReliable mortality data are essential for the development of public health policies. In Brazil, although there is a well-consolidated universal system for mortality data, the quality of information on causes of death (CoD) is not even among Brazilian regions, with a high proportion of ill-defined CoD. Verbal autopsy (VA) is an alternative to improve mortality data. This study aimed to evaluate the performance of an adapted and reduced version of VA in identifying the underlying causes of non-forensic deaths, in São Paulo, Brazil. This is the first time that a version of the questionnaire has been validated considering the autopsy as the gold standard.

methodsThe performance of a physician-certified verbal autopsy (PCVA) was evaluated considering conventional autopsy (macroscopy plus microscopy) as gold standard, based on a sample of 2060 decedents that were sent to the Post-Mortem Verification Service (SVOC-USP). All CoD, from the underlying to the immediate, were listed by both parties, and ICD-10 attributed by a senior coder. For each cause, sensitivity and chance corrected concordance (CCC) were computed considering first the underlying causes attributed by the pathologist and PCVA, and then any CoD listed in the death certificate given by PCVA. Cause specific mortality fraction accuracy (CSMF-accuracy) and chance corrected CSMF-accuracy were computed to evaluate the PCVA performance at the populational level.

resultsThere was substantial variability of the sensitivities and CCC across the causes. Well-known chronic diseases with accurate diagnoses that had been informed by physicians to family members, such as various cancers, had sensitivities above 40% or 50%. However, PCVA was not effective in attributing Pneumonia, Cardiomyopathy and Leukemia/Lymphoma as underlying CoD. At populational level, the PCVA estimated cause specific mortality fractions (CSMF) may be considered close to the fractions pointed by the gold standard. The CSMF-accuracy was 0.81 and the chance corrected CSMF-accuracy was 0.49.

conclusionsThe PCVA was efficient in attributing some causes individually and proved effective in estimating the CSMF, which indicates that the method is useful to establish public health priorities.

Indexed as

PhysiciansAdultAutopsyBrazilCause of DeathHumansSurveys and QuestionnairesDeath certificationMortality surveillanceNatural deathUnderlying cause of deathVerbal autopsyVital statistics

Identifiers

PMID35421964
PMCPMC9008898

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.