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研究孕妇肥胖对先兆子痫患者引产结局的影响。

Examining the effect of maternal obesity on outcome of labor induction in patients with preeclampsia.

作者信息

Robinson Christopher J, Hill Elizabeth G, Alanis Mark C, Chang Eugene Y, Johnson Donna D, Almeida Jonas S

机构信息

Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Medical University of South Carolina, Charleston, South Carolina 29425, USA.

出版信息

Hypertens Pregnancy. 2010;29(4):446-56. doi: 10.3109/10641950903452386.

Abstract

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.

摘要

目的

本研究旨在评估孕前体重指数(BMI)所衡量的孕妇肥胖对因子痫前期接受引产的妇女分娩方式的影响。

研究设计

经机构审查委员会(IRB)批准,从包含历史和临床信息的围产期信息数据库中识别出1997年至2007年期间接受引产的子痫前期患者。数据分析包括按分娩方式对预测变量进行双变量和多变量分析。训练并外部验证了一个人工神经网络,以独立检查子痫前期妇女分娩方式的预测因素。

结果

608名妇女符合纳入标准并被纳入本研究。基于多变量逻辑回归(MLR)模型,BMI每增加5个单位,剖宫产几率增加16%。经过训练并外部验证的人工神经网络证实了肥胖在预测子痫前期引产妇女分娩方式中的重要性。

结论

在子痫前期患者中,肥胖使引产复杂化。即使BMI小幅增加,肥胖也会增加剖宫产风险。在子痫前期引产患者中,人工神经网络对分娩方式的预测表现与MLR相似。

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本文引用的文献

2
Obesity in pregnancy: pre-conceptional to postpartum consequences.
J Obstet Gynaecol Can. 2008 Jun;30(6):477-488. doi: 10.1016/S1701-2163(16)32863-8.
3
Prediction of pelvic organ prolapse using an artificial neural network.
Am J Obstet Gynecol. 2008 Aug;199(2):193.e1-6. doi: 10.1016/j.ajog.2008.04.029. Epub 2008 Jun 4.
4
Obesity and mode of delivery in primigravid and multigravid women.
Am J Perinatol. 2008 Mar;25(3):163-7. doi: 10.1055/s-2008-1061496. Epub 2008 Feb 25.
5
Risk of uterine rupture and adverse perinatal outcome at term after cesarean delivery.
Obstet Gynecol. 2007 Oct;110(4):801-7. doi: 10.1097/01.AOG.0000284622.71222.b2.
6
Maternal obesity and risk of cesarean delivery: a meta-analysis.
Obes Rev. 2007 Sep;8(5):385-94. doi: 10.1111/j.1467-789X.2007.00397.x.
7
Effect of Body Mass Index on pregnancy outcomes in nulliparous women delivering singleton babies.
BMC Public Health. 2007 Jul 24;7:168. doi: 10.1186/1471-2458-7-168.
8
Evidence-based strategies for reducing cesarean section rates: a meta-analysis.
Birth. 2007 Mar;34(1):53-64. doi: 10.1111/j.1523-536X.2006.00146.x.
10
Risks of adverse outcomes in the next birth after a first cesarean delivery.
Obstet Gynecol. 2007 Feb;109(2 Pt 1):270-6. doi: 10.1097/01.AOG.0000250469.23047.73.

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