Evidence map›Paper›PMID 31630097›Full record

ArticleBMJ open2019

Ability of verbal autopsy data to detect deaths due to uncontrolled hyperglycaemia: testing existing methods and development and validation of a novel weighted score.

Sarah Blackstock, Miles D Witham, Alisha N Wade, Amelia Crampin, David Beran, Graham D Ogle, Justine I Davies

Abstract read
In one paragraph

Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Sarah BlackstockDepartment of Paediatric Rheumatology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, London, UK.
Miles D WithamDepartment of Aging and Health, School of Medicine, University of Dundee, Dundee, UK.
Alisha N WadeMRC/Wits Rural Public Health and Health Transitions Research Unit, University of the Witwatersrand School of Public Health, Johannesburg, South Africa.
Amelia CrampinDepartment of Population Health, London School of Hygiene and Tropical Medicine, London, UK.
David BeranDivision of Tropical and Humanitarian Medicine, University of Geneva and Geneva University Hospitals, Geneva, Switzerland.
Graham D OgleLife for a Child Program, Diabetes NSW, Glebe, New South Wales, Australia.
Justine I DaviesMRC/Wits Rural Public Health and Health Transitions Research Unit, University of the Witwatersrand School of Public Health, Johannesburg, South Africa j.davies.6@bham.ac.uk.

Funding

Endocrine and metabolic diseases in rural South Africa-establishing burden and improving detectionK43TW010698 · FIC · WITS HEALTH CONSORTIUM (PTY), LTD · PI WADE, ALISHA NICOLE · 2017 to 2021
$581k
FIC NIH HHS K43 TW010698
6 · The paper itself

Abstract

objectivesVerbal autopsy (VA) is a useful tool to ascertain cause of death where no other mechanisms exist. We aimed to assess the utility of VA data to ascertain deaths due to uncontrolled hyperglycaemia and to develop a weighted score (WS) to specifically identify cases. Cases were identified by a study or site physician with training in diabetes. These diagnoses were also compared with diagnoses produced by a standard computer algorithm (InterVA-4).

settingThis study was done using VA data from the Health and Demographic Survey sites in Agincourt in rural South Africa. Validation of the WS was done using VA data from Karonga in Malawi.

participantsAll deaths from ages 1 to 49 years between 1992 and 2015 and between 2002 and 2016 from Agincourt and Karonga, respectively. There were 8699 relevant deaths in Agincourt and 1663 in Karonga.

resultsOf the Agincourt deaths, there were 77 study physician classified cases and 58 computer algorithm classified cases. Agreement between study physician classified cases and computer algorithm classified cases was poor (Cohen's kappa 0.14). Our WS produced a receiver operator curve with area under the curve of 0.952 (95% CI 0.920 to 0.985). However, positive predictive value (PPV) was below 50% when the WS was applied to the development set and the score was dominated by the necessity for a premortem diagnosis of diabetes. Independent validation showed the WS performed reasonably against site physician classified cases with sensitivity of 86%, specificity of 99%, PPV of 60% and negative predictive value of 99%.

conclusionOur results suggest that widely used VA methodologies may be missing deaths due to uncontrolled hyperglycaemia. Our WS may offer improved ability to detect deaths due to uncontrolled hyperglycaemia in large populations studies where no other means exist.

Indexed as

AutopsyCause of DeathAdolescentAdultAlgorithmsChildChild, PreschoolCohort StudiesFemaleHumansHyperglycemiaInfantMalawiMaleMiddle AgedReproducibility of Resultsdiabetes & endocrinologyepidemiologyhealth informatics

Identifiers

PMID31630097
PMCPMC6803086

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