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Predicting In-Hospital Maternal Mortality in Senegal and Mali

Authors :
Alexandre Dumont
Noëlle Bru
Michal Abrahamowicz
Cheikh Ndour
Pierre Fournier
Mamadou Traoré
Aliou Diop
Arnaud Fauconnier
Simplice Dossou Gbété
Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP)
Centre National de la Recherche Scientifique (CNRS)-Université de Pau et des Pays de l'Adour (UPPA)
Laboratoire des Sciences du Génie Chimique (LSGC)
Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)
laboratoire d'Etudes et de recherches en Statistiques et Développement (LERSTAD)
Université Gaston Bergé Sénégal
Biologie Intégrative et Virologie des Insectes [Univ. de Montpellier II] (BIVI)
Institut National de la Recherche Agronomique (INRA)-Université Montpellier 2 - Sciences et Techniques (UM2)
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Ecole d'Ingénieurs de Purpan (INPT - EI Purpan)
Institut National Polytechnique (Toulouse) (Toulouse INP)
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP)
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées
Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS)
Risques cliniques et sécurité en santé des femmes et en santé périnatale (RISCQ)
Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)
Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de la Recherche Agronomique (INRA)
Source :
PLoS ONE, PLoS ONE, Public Library of Science, 2013, 8 (5), pp.11. ⟨10.1371/journal.pone.0064157⟩, PLoS ONE, Vol 8, Iss 5, p e64157 (2013)
Publication Year :
2013
Publisher :
HAL CCSD, 2013.

Abstract

International audience; 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. © 2013 Ndour et al.

Details

Language :
English
ISSN :
19326203
Database :
OpenAIRE
Journal :
PLoS ONE, PLoS ONE, Public Library of Science, 2013, 8 (5), pp.11. ⟨10.1371/journal.pone.0064157⟩, PLoS ONE, Vol 8, Iss 5, p e64157 (2013)
Accession number :
edsair.doi.dedup.....4644e0515e6d2b03eb2a178263a3d087
Full Text :
https://doi.org/10.1371/journal.pone.0064157⟩