Factors associated with postpartum hemorrhage maternal death in referral hospitals in Senegal and Mali: a cross-sectional epidemiological survey
Notice bibliographique
Résumé
BACKGROUND: Postpartum hemorrhage (PPH) is the leading cause of maternal mortality in Sub-Saharan-Africa (SSA). Although clinical guidelines treating PPH are available, their implementation remains a great challenge in resource poor settings. A better understanding of the factors associated with PPH maternal mortality is critical for preventing risk of hospital-based maternal death. The purpose of this study was thus to assess which factors contribute to maternal death occurring during PPH. The factors were as follows: women's characteristics, aspects of pregnancy and delivery; components of PPH management; and organizational characteristics of the referral hospitals in Senegal and Mali. METHODS: A cross-sectional survey nested in a cluster randomized trial (QUARITE trial) was carried out in 46 referral hospitals during the pre-intervention period from October 2007 to September 2008 in Senegal and Mali. Individual and hospital characteristics data were collected through standardized questionnaires. A multivariable logistic mixed model was used to identify the factors that were significantly associated with PPH maternal death. RESULTS: Among the 3,278 women who experienced PPH, 178 (5.4%) of them died before hospital discharge. The factors that were significantly associated with PPH maternal mortality were: age over 35 years (adjusted OR = 2.16 [1.26-3.72]), living in Mali (adjusted OR = 1.84 [1.13-3.00]), residing outside the region location of the hospital (adjusted OR = 2.43 [1.29-4.56]), pre-existing chronic disease before pregnancy (adjusted OR = 7.54 [2.54-22.44]), prepartum severe anemia (adjusted OR = 6.65 [3.77-11.74]), forceps or vacuum delivery (adjusted OR = 2.63 [1.19-5.81]), birth weight greater than 4000 grs (adjusted OR = 2.54 [1.26-5.10]), transfusion (adjusted OR = 2.17 [1.53-3.09]), transfer to another hospital (adjusted OR = 13.35 [6.20-28.76]). There was a smaller risk of PPH maternal death in hospitals with gynecologist-obstetrician (adjusted OR = 0.55 [0.35-0.89]) than those with only a general practitioner trained in emergency obstetric care (EmOC). CONCLUSIONS: Our findings may have direct implications for preventing PPH maternal death in resource poor settings. In particular, we suggest anemia should be diagnosed and treated before delivery and inter-hospital transfer of women should be improved, as well as the management of blood banks for a quicker access to transfusion. Finally, an extent training of general practitioners in EmOC would contribute to the decrease of PPH maternal mortality.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».