Cargando…

Predictors of uterine rupture in a large sample of women in Senegal and Mali: cross-sectional analysis of QUARITE trial data

BACKGROUND: The purpose of this study was to investigate predictors of uterine rupture in a large sample of sub-Saharan African women. Uterine rupture is rare in high-income countries, but it is more common in low-income settings where health systems are often under-resourced. However, understanding...

Descripción completa

Detalles Bibliográficos
Autores principales: Delafield, Rebecca, Pirkle, Catherine M., Dumont, Alexandre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6211600/
https://www.ncbi.nlm.nih.gov/pubmed/30382820
http://dx.doi.org/10.1186/s12884-018-2064-y
_version_ 1783367368188100608
author Delafield, Rebecca
Pirkle, Catherine M.
Dumont, Alexandre
author_facet Delafield, Rebecca
Pirkle, Catherine M.
Dumont, Alexandre
author_sort Delafield, Rebecca
collection PubMed
description BACKGROUND: The purpose of this study was to investigate predictors of uterine rupture in a large sample of sub-Saharan African women. Uterine rupture is rare in high-income countries, but it is more common in low-income settings where health systems are often under-resourced. However, understanding of risk factors contributing to uterine rupture in such settings is limited due to small sample sizes and research rarely considers system and individual-level factors concomitantly. METHODS: Cross-sectional data analysis from the pre-intervention period (Oct. 1, 2007- Oct. 1, 2008) of the QUARITE trial, a large-scale maternal mortality study. This research examines uterine rupture among 84,924 women who delivered in one of 46 referral hospitals in Mali and Senegal. A mixed-effects logistic regression model identified individual and geographical risk factors associated with uterine rupture, accounting for clustering by hospital. RESULTS: Five hundred sixty-nine incidences of uterine rupture (0.67% of sample) were recorded. Predictors of uterine rupture: grand multiparity defined as > 5 live births (aOR = 7.57, 95%CI; 5.19–11.03), prior cesarean (aOR = 2.02, 95%CI; 1.61–2.54), resides outside hospital region (aOR = 1.90, 95%CI: 1.28–2.81), no prenatal care visits (aOR = 1.80, 95%CI; 1.44–2.25), and birth weight of > 3600 g (aOR = 1.61, 95%CI; 1.30–1.98). Women who were referred and who had an obstructed labor had much higher odds of uterine rupture compared to those who experienced neither (aOR: 46.25, 95%CI; 32.90–65.02). CONCLUSIONS: The results of this large study confirm that the referral system, particularly for women with obstructed labor and increasing parity, is a main determinant of uterine rupture in this context. Improving labor and delivery management at each level of the health system and communication between health care facilities should be a priority to reduce uterine rupture. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12884-018-2064-y) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6211600
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-62116002018-11-08 Predictors of uterine rupture in a large sample of women in Senegal and Mali: cross-sectional analysis of QUARITE trial data Delafield, Rebecca Pirkle, Catherine M. Dumont, Alexandre BMC Pregnancy Childbirth Research Article BACKGROUND: The purpose of this study was to investigate predictors of uterine rupture in a large sample of sub-Saharan African women. Uterine rupture is rare in high-income countries, but it is more common in low-income settings where health systems are often under-resourced. However, understanding of risk factors contributing to uterine rupture in such settings is limited due to small sample sizes and research rarely considers system and individual-level factors concomitantly. METHODS: Cross-sectional data analysis from the pre-intervention period (Oct. 1, 2007- Oct. 1, 2008) of the QUARITE trial, a large-scale maternal mortality study. This research examines uterine rupture among 84,924 women who delivered in one of 46 referral hospitals in Mali and Senegal. A mixed-effects logistic regression model identified individual and geographical risk factors associated with uterine rupture, accounting for clustering by hospital. RESULTS: Five hundred sixty-nine incidences of uterine rupture (0.67% of sample) were recorded. Predictors of uterine rupture: grand multiparity defined as > 5 live births (aOR = 7.57, 95%CI; 5.19–11.03), prior cesarean (aOR = 2.02, 95%CI; 1.61–2.54), resides outside hospital region (aOR = 1.90, 95%CI: 1.28–2.81), no prenatal care visits (aOR = 1.80, 95%CI; 1.44–2.25), and birth weight of > 3600 g (aOR = 1.61, 95%CI; 1.30–1.98). Women who were referred and who had an obstructed labor had much higher odds of uterine rupture compared to those who experienced neither (aOR: 46.25, 95%CI; 32.90–65.02). CONCLUSIONS: The results of this large study confirm that the referral system, particularly for women with obstructed labor and increasing parity, is a main determinant of uterine rupture in this context. Improving labor and delivery management at each level of the health system and communication between health care facilities should be a priority to reduce uterine rupture. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12884-018-2064-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-11-01 /pmc/articles/PMC6211600/ /pubmed/30382820 http://dx.doi.org/10.1186/s12884-018-2064-y Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Delafield, Rebecca
Pirkle, Catherine M.
Dumont, Alexandre
Predictors of uterine rupture in a large sample of women in Senegal and Mali: cross-sectional analysis of QUARITE trial data
title Predictors of uterine rupture in a large sample of women in Senegal and Mali: cross-sectional analysis of QUARITE trial data
title_full Predictors of uterine rupture in a large sample of women in Senegal and Mali: cross-sectional analysis of QUARITE trial data
title_fullStr Predictors of uterine rupture in a large sample of women in Senegal and Mali: cross-sectional analysis of QUARITE trial data
title_full_unstemmed Predictors of uterine rupture in a large sample of women in Senegal and Mali: cross-sectional analysis of QUARITE trial data
title_short Predictors of uterine rupture in a large sample of women in Senegal and Mali: cross-sectional analysis of QUARITE trial data
title_sort predictors of uterine rupture in a large sample of women in senegal and mali: cross-sectional analysis of quarite trial data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6211600/
https://www.ncbi.nlm.nih.gov/pubmed/30382820
http://dx.doi.org/10.1186/s12884-018-2064-y
work_keys_str_mv AT delafieldrebecca predictorsofuterineruptureinalargesampleofwomeninsenegalandmalicrosssectionalanalysisofquaritetrialdata
AT pirklecatherinem predictorsofuterineruptureinalargesampleofwomeninsenegalandmalicrosssectionalanalysisofquaritetrialdata
AT dumontalexandre predictorsofuterineruptureinalargesampleofwomeninsenegalandmalicrosssectionalanalysisofquaritetrialdata