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Comparison of the Causes of Death Identified Using Automated Verbal Autopsy and Complete Autopsy among Brought-in-Dead Cases at a Tertiary Hospital in Sub-Sahara Africa

Background  Over one-third of deaths recorded at health facilities in Zambia are brought in dead (BID) and the causes of death (CODs) are not fully analyzed. The use of automated verbal autopsy (VA) has reportedly determined the CODs of more BID cases than the death notification form issued by the h...

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Autores principales: Yokobori, Yuta, Matsuura, Jun, Sugiura, Yasuo, Mutemba, Charles, Julius, Peter, Himwaze, Cordelia, Nyahoda, Martin, Mwango, Chomba, Kazhumbula, Lloyd, Yuasa, Motoyuki, Munkombwe, Brian, Mucheleng'anga, Luchenga
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Georg Thieme Verlag KG 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9200488/
https://www.ncbi.nlm.nih.gov/pubmed/35705183
http://dx.doi.org/10.1055/s-0042-1749118
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author Yokobori, Yuta
Matsuura, Jun
Sugiura, Yasuo
Mutemba, Charles
Julius, Peter
Himwaze, Cordelia
Nyahoda, Martin
Mwango, Chomba
Kazhumbula, Lloyd
Yuasa, Motoyuki
Munkombwe, Brian
Mucheleng'anga, Luchenga
author_facet Yokobori, Yuta
Matsuura, Jun
Sugiura, Yasuo
Mutemba, Charles
Julius, Peter
Himwaze, Cordelia
Nyahoda, Martin
Mwango, Chomba
Kazhumbula, Lloyd
Yuasa, Motoyuki
Munkombwe, Brian
Mucheleng'anga, Luchenga
author_sort Yokobori, Yuta
collection PubMed
description Background  Over one-third of deaths recorded at health facilities in Zambia are brought in dead (BID) and the causes of death (CODs) are not fully analyzed. The use of automated verbal autopsy (VA) has reportedly determined the CODs of more BID cases than the death notification form issued by the hospital. However, the validity of automated VA is yet to be fully investigated. Objectives  To compare the CODs identified by automated VA with those by complete autopsy to examine the validity of a VA tool. Methods  The study site was the tertiary hospital in the capital city of Zambia. From September 2019 to January 2020, all BID cases aged 13 years and older brought to the hospital during the daytime on weekdays were enrolled in this study. External COD cases were excluded. The deceased's relatives were interviewed using the 2016 World Health Organization VA questionnaire. The data were analyzed using InterVA, an automated VA tool, to determine the CODs, which were compared with the results of complete autopsies. Results  A total of 63 cases were included. The CODs of 50 BID cases were determined by both InterVA and complete autopsies. The positive predictive value of InterVA was 22%. InterVA determined the CODs correctly in 100% cases of maternal CODs, 27.5% cases of noncommunicable disease CODs, and 5.3% cases of communicable disease CODs. Using the three broader disease groups, 56.0% cases were classified in the same groups by both methods. Conclusion  While the positive predictive value was low, more than half of the cases were categorized into the same broader categories. However, there are several limitations in this study, including small sample size. More research is required to investigate the factors leading to discrepancies between the CODs determined by both methods to optimize the use of automated VA in Zambia.
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spelling pubmed-92004882022-06-16 Comparison of the Causes of Death Identified Using Automated Verbal Autopsy and Complete Autopsy among Brought-in-Dead Cases at a Tertiary Hospital in Sub-Sahara Africa Yokobori, Yuta Matsuura, Jun Sugiura, Yasuo Mutemba, Charles Julius, Peter Himwaze, Cordelia Nyahoda, Martin Mwango, Chomba Kazhumbula, Lloyd Yuasa, Motoyuki Munkombwe, Brian Mucheleng'anga, Luchenga Appl Clin Inform Background  Over one-third of deaths recorded at health facilities in Zambia are brought in dead (BID) and the causes of death (CODs) are not fully analyzed. The use of automated verbal autopsy (VA) has reportedly determined the CODs of more BID cases than the death notification form issued by the hospital. However, the validity of automated VA is yet to be fully investigated. Objectives  To compare the CODs identified by automated VA with those by complete autopsy to examine the validity of a VA tool. Methods  The study site was the tertiary hospital in the capital city of Zambia. From September 2019 to January 2020, all BID cases aged 13 years and older brought to the hospital during the daytime on weekdays were enrolled in this study. External COD cases were excluded. The deceased's relatives were interviewed using the 2016 World Health Organization VA questionnaire. The data were analyzed using InterVA, an automated VA tool, to determine the CODs, which were compared with the results of complete autopsies. Results  A total of 63 cases were included. The CODs of 50 BID cases were determined by both InterVA and complete autopsies. The positive predictive value of InterVA was 22%. InterVA determined the CODs correctly in 100% cases of maternal CODs, 27.5% cases of noncommunicable disease CODs, and 5.3% cases of communicable disease CODs. Using the three broader disease groups, 56.0% cases were classified in the same groups by both methods. Conclusion  While the positive predictive value was low, more than half of the cases were categorized into the same broader categories. However, there are several limitations in this study, including small sample size. More research is required to investigate the factors leading to discrepancies between the CODs determined by both methods to optimize the use of automated VA in Zambia. Georg Thieme Verlag KG 2022-06-15 /pmc/articles/PMC9200488/ /pubmed/35705183 http://dx.doi.org/10.1055/s-0042-1749118 Text en The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
spellingShingle Yokobori, Yuta
Matsuura, Jun
Sugiura, Yasuo
Mutemba, Charles
Julius, Peter
Himwaze, Cordelia
Nyahoda, Martin
Mwango, Chomba
Kazhumbula, Lloyd
Yuasa, Motoyuki
Munkombwe, Brian
Mucheleng'anga, Luchenga
Comparison of the Causes of Death Identified Using Automated Verbal Autopsy and Complete Autopsy among Brought-in-Dead Cases at a Tertiary Hospital in Sub-Sahara Africa
title Comparison of the Causes of Death Identified Using Automated Verbal Autopsy and Complete Autopsy among Brought-in-Dead Cases at a Tertiary Hospital in Sub-Sahara Africa
title_full Comparison of the Causes of Death Identified Using Automated Verbal Autopsy and Complete Autopsy among Brought-in-Dead Cases at a Tertiary Hospital in Sub-Sahara Africa
title_fullStr Comparison of the Causes of Death Identified Using Automated Verbal Autopsy and Complete Autopsy among Brought-in-Dead Cases at a Tertiary Hospital in Sub-Sahara Africa
title_full_unstemmed Comparison of the Causes of Death Identified Using Automated Verbal Autopsy and Complete Autopsy among Brought-in-Dead Cases at a Tertiary Hospital in Sub-Sahara Africa
title_short Comparison of the Causes of Death Identified Using Automated Verbal Autopsy and Complete Autopsy among Brought-in-Dead Cases at a Tertiary Hospital in Sub-Sahara Africa
title_sort comparison of the causes of death identified using automated verbal autopsy and complete autopsy among brought-in-dead cases at a tertiary hospital in sub-sahara africa
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9200488/
https://www.ncbi.nlm.nih.gov/pubmed/35705183
http://dx.doi.org/10.1055/s-0042-1749118
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