Predicting in-hospital maternal mortality in Senegal and Mali.

OBJECTIVE: We sought to identify predictors of in-hospital maternal mortality among women attending referral hospitals in Mali and Senegal. METHODS: We conducted a cross-sectional epidemiological survey using data from a cluster randomized controlled trial (QUARITE trial) in 46 referral hospitals in...

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Main Authors: Cheikh Ndour, Simplice Dossou Gbété, Noelle Bru, Michal Abrahamowicz, Arnaud Fauconnier, Mamadou Traoré, Aliou Diop, Pierre Fournier, Alexandre Dumont
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3667861?pdf=render
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spelling doaj-b79fc0b1f76b41aa9aeb2bc1e9b5725b2020-11-25T01:15:27ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0185e6415710.1371/journal.pone.0064157Predicting in-hospital maternal mortality in Senegal and Mali.Cheikh NdourSimplice Dossou GbétéNoelle BruMichal AbrahamowiczArnaud FauconnierMamadou TraoréAliou DiopPierre FournierAlexandre DumontOBJECTIVE: We sought to identify predictors of in-hospital maternal mortality among women attending referral hospitals in Mali and Senegal. METHODS: We conducted a cross-sectional epidemiological survey using data from a cluster randomized controlled trial (QUARITE trial) in 46 referral hospitals in Mali and Senegal, during the pre-intervention period of the trial (from October 1st 2007 to October 1st 2008). We included 89,518 women who delivered in the 46 hospitals during this period. Data were collected on women's characteristics, obstetric complications, and vital status until the hospital discharge. We developed a tree-like classification rule (classification rule) to identify patient subgroups at high risk of maternal in-hospital mortality. RESULTS: Our analyses confirm that patients with uterine rupture, hemorrhage or prolonged/obstructed labor, and those who have an emergency ante-partum cesarean delivery have an increased risk of in-hospital mortality, especially if they are referred from another health facility. Twenty relevant patterns, based on fourteen predictors variables, are used to predict in-hospital maternal mortality with 81.41% sensitivity (95% CI = [77.12%-87.70%]) and 81.6% specificity (95% CI = [81.16%-82.02%]). CONCLUSION: The proposed class association rule method will help health care professionals in referral hospitals in Mali and Senegal to identify mothers at high risk of in-hospital death, and can provide scientific evidence on which to base their decisions to manage patients delivering in their health facilities.http://europepmc.org/articles/PMC3667861?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Cheikh Ndour
Simplice Dossou Gbété
Noelle Bru
Michal Abrahamowicz
Arnaud Fauconnier
Mamadou Traoré
Aliou Diop
Pierre Fournier
Alexandre Dumont
spellingShingle Cheikh Ndour
Simplice Dossou Gbété
Noelle Bru
Michal Abrahamowicz
Arnaud Fauconnier
Mamadou Traoré
Aliou Diop
Pierre Fournier
Alexandre Dumont
Predicting in-hospital maternal mortality in Senegal and Mali.
PLoS ONE
author_facet Cheikh Ndour
Simplice Dossou Gbété
Noelle Bru
Michal Abrahamowicz
Arnaud Fauconnier
Mamadou Traoré
Aliou Diop
Pierre Fournier
Alexandre Dumont
author_sort Cheikh Ndour
title Predicting in-hospital maternal mortality in Senegal and Mali.
title_short Predicting in-hospital maternal mortality in Senegal and Mali.
title_full Predicting in-hospital maternal mortality in Senegal and Mali.
title_fullStr Predicting in-hospital maternal mortality in Senegal and Mali.
title_full_unstemmed Predicting in-hospital maternal mortality in Senegal and Mali.
title_sort predicting in-hospital maternal mortality in senegal and mali.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2013-01-01
description OBJECTIVE: We sought to identify predictors of in-hospital maternal mortality among women attending referral hospitals in Mali and Senegal. METHODS: We conducted a cross-sectional epidemiological survey using data from a cluster randomized controlled trial (QUARITE trial) in 46 referral hospitals in Mali and Senegal, during the pre-intervention period of the trial (from October 1st 2007 to October 1st 2008). We included 89,518 women who delivered in the 46 hospitals during this period. Data were collected on women's characteristics, obstetric complications, and vital status until the hospital discharge. We developed a tree-like classification rule (classification rule) to identify patient subgroups at high risk of maternal in-hospital mortality. RESULTS: Our analyses confirm that patients with uterine rupture, hemorrhage or prolonged/obstructed labor, and those who have an emergency ante-partum cesarean delivery have an increased risk of in-hospital mortality, especially if they are referred from another health facility. Twenty relevant patterns, based on fourteen predictors variables, are used to predict in-hospital maternal mortality with 81.41% sensitivity (95% CI = [77.12%-87.70%]) and 81.6% specificity (95% CI = [81.16%-82.02%]). CONCLUSION: The proposed class association rule method will help health care professionals in referral hospitals in Mali and Senegal to identify mothers at high risk of in-hospital death, and can provide scientific evidence on which to base their decisions to manage patients delivering in their health facilities.
url http://europepmc.org/articles/PMC3667861?pdf=render
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