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Incompleteness and misclassification of maternal death recording: a systematic review and meta-analysis

OBJECTIVE: To quantify the extent of incompleteness and misclassification of maternal and pregnancy related deaths, and to identify general and context-specific factors associated with incompleteness and/or misclassification of maternal death data. METHODS: We conducted a systematic review of incomp...

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Autores principales: Ahmed, Sahar M. A., Cresswell, Jenny A., Say, Lale
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647144/
https://www.ncbi.nlm.nih.gov/pubmed/37968585
http://dx.doi.org/10.1186/s12884-023-06077-4
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author Ahmed, Sahar M. A.
Cresswell, Jenny A.
Say, Lale
author_facet Ahmed, Sahar M. A.
Cresswell, Jenny A.
Say, Lale
author_sort Ahmed, Sahar M. A.
collection PubMed
description OBJECTIVE: To quantify the extent of incompleteness and misclassification of maternal and pregnancy related deaths, and to identify general and context-specific factors associated with incompleteness and/or misclassification of maternal death data. METHODS: We conducted a systematic review of incompleteness and/or misclassification of maternal and pregnancy-related deaths. We conducted a narrative synthesis to identify methods used to capture and classify maternal deaths, as well as general and context specific factors affecting the completeness and misclassification of maternal death recording. We conducted a meta-analysis of proportions to obtain estimates of incompleteness and misclassification of maternal death recording, overall and disaggregated by income and surveillance system types. FINDINGS: Of 2872 title-abstracts identified, 29 were eligible for inclusions in the qualitative synthesis, and 20 in the meta-analysis. Included studies relied principally on record linkage and review for identifying deaths, and on review of medical records and verbal autopsies to correctly classify cause of death. Deaths to women towards the extremes of the reproductive age range, those not classified by a medical examiner or a coroner, and those from minority ethnic groups in their setting were more likely misclassified or unrecorded. In the meta-analysis, we found maternal death recording to be incomplete by 34% (95% CI: 28–48), with 60% sensitivity (95% CI: 31–81.). Overall, we found maternal mortality was under-estimated by 39% (95% CI: 30–48) due to incompleteness and/or misclassification. Reporting of deaths away from the intrapartum, due to indirect causes or occurring at home were less complete than their counterparts. There was substantial between and within group variability across most results. CONCLUSION: Maternal deaths were under-estimated in almost all contexts, but the extent varied across settings. Countries should aim towards establishing Civil Registration and Vital Statistics systems where they are not instituted. Efforts to improve the completeness and accuracy of maternal cause of death recording, such as Confidential Enquiries into Maternal Deaths, are needed even where CRVS is considered to be well-functioning. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-023-06077-4.
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spelling pubmed-106471442023-11-15 Incompleteness and misclassification of maternal death recording: a systematic review and meta-analysis Ahmed, Sahar M. A. Cresswell, Jenny A. Say, Lale BMC Pregnancy Childbirth Research OBJECTIVE: To quantify the extent of incompleteness and misclassification of maternal and pregnancy related deaths, and to identify general and context-specific factors associated with incompleteness and/or misclassification of maternal death data. METHODS: We conducted a systematic review of incompleteness and/or misclassification of maternal and pregnancy-related deaths. We conducted a narrative synthesis to identify methods used to capture and classify maternal deaths, as well as general and context specific factors affecting the completeness and misclassification of maternal death recording. We conducted a meta-analysis of proportions to obtain estimates of incompleteness and misclassification of maternal death recording, overall and disaggregated by income and surveillance system types. FINDINGS: Of 2872 title-abstracts identified, 29 were eligible for inclusions in the qualitative synthesis, and 20 in the meta-analysis. Included studies relied principally on record linkage and review for identifying deaths, and on review of medical records and verbal autopsies to correctly classify cause of death. Deaths to women towards the extremes of the reproductive age range, those not classified by a medical examiner or a coroner, and those from minority ethnic groups in their setting were more likely misclassified or unrecorded. In the meta-analysis, we found maternal death recording to be incomplete by 34% (95% CI: 28–48), with 60% sensitivity (95% CI: 31–81.). Overall, we found maternal mortality was under-estimated by 39% (95% CI: 30–48) due to incompleteness and/or misclassification. Reporting of deaths away from the intrapartum, due to indirect causes or occurring at home were less complete than their counterparts. There was substantial between and within group variability across most results. CONCLUSION: Maternal deaths were under-estimated in almost all contexts, but the extent varied across settings. Countries should aim towards establishing Civil Registration and Vital Statistics systems where they are not instituted. Efforts to improve the completeness and accuracy of maternal cause of death recording, such as Confidential Enquiries into Maternal Deaths, are needed even where CRVS is considered to be well-functioning. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-023-06077-4. BioMed Central 2023-11-15 /pmc/articles/PMC10647144/ /pubmed/37968585 http://dx.doi.org/10.1186/s12884-023-06077-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ahmed, Sahar M. A.
Cresswell, Jenny A.
Say, Lale
Incompleteness and misclassification of maternal death recording: a systematic review and meta-analysis
title Incompleteness and misclassification of maternal death recording: a systematic review and meta-analysis
title_full Incompleteness and misclassification of maternal death recording: a systematic review and meta-analysis
title_fullStr Incompleteness and misclassification of maternal death recording: a systematic review and meta-analysis
title_full_unstemmed Incompleteness and misclassification of maternal death recording: a systematic review and meta-analysis
title_short Incompleteness and misclassification of maternal death recording: a systematic review and meta-analysis
title_sort incompleteness and misclassification of maternal death recording: a systematic review and meta-analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647144/
https://www.ncbi.nlm.nih.gov/pubmed/37968585
http://dx.doi.org/10.1186/s12884-023-06077-4
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