Examining the Effect of Maternal Obesity on Outcome of Labor Induction in Patients with Preeclampsia
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Le résumé fourni par la source
OBJECTIVE: The objective of this investigation was to evaluate the effect of maternal obesity, as measured by prepregnancy body mass index (BMI), on the mode of delivery in women undergoing indicated induction of labor for preeclampsia. STUDY DESIGN: Following Institutional Review Board (IRB) approval, patients with preeclampsia who underwent an induction of labor from 1997 to 2007 were identified from a perinatal information database, which included historical and clinical information. Data analysis included bivariable and multivariable analyses of predictor variables by mode of delivery. An artificial neural network was trained and externally validated to independently examine predictors of mode of delivery among women with preeclampsia. RESULTS: Six hundred and eight women met eligibility criteria and were included in this investigation. Based on multivariable logistic regression (MLR) modeling, a 5-unit increase in BMI yields a 16% increase in the odds of cesarean delivery. An artificial neural network trained and externally validated confirmed the importance of obesity in the prediction of mode of delivery among women undergoing labor induction for preeclampsia. CONCLUSION: Among patients who are affected by preeclampsia, obesity complicates labor induction. The risk of cesarean delivery is enhanced by obesity, even with small increases in BMI. Prediction of mode of delivery by an artificial neural network performs similar to MLR among patients undergoing labor induction for preeclampsia.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Examining the Effect of Maternal Obesity on Outcome of Labor Induction in Patients with Preeclampsia
- Date Crossref
- 06/09/2010
- Éditeur
- Informa UK Limited
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Medical University of South Carolina Department of Obstetrics and Gynecology pays non établi dans la noticeUniversité ou école supérieure
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The University of Texas MD Anderson Cancer Center Department of Bioinformatics and Computational Biology pays non établi dans la noticeÉtablissement de santé
Department of Obstetrics and Gynecology — Medical University of South Carolina et Department of Bioinformatics and Computational Biology — The University of Texas MD Anderson Cancer Center.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.