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马来西亚一家三级护理医院中影响孕妇巨大儿的因素。

Factors influencing macrosomia in pregnant women in a tertiary care hospital in Malaysia.

作者信息

Yadav Hematram, Lee Nagarajah

机构信息

Division of Community Medicine, International Medical University, Kuala Lumpur, Malaysia.

出版信息

J Obstet Gynaecol Res. 2014 Feb;40(2):439-44. doi: 10.1111/jog.12209. Epub 2013 Oct 22.

Abstract

AIM

To identify the risk factors influencing the development of macrosomia among pregnant women and to develop a regression model to predict macrosomia.

METHODS

A cross-sectional study was conducted in a tertiary hospital in Malaysia involving 2332 pregnant women. The data was retrospectively collected from the obstetrics and gynecology department. The factors that influence fetal weight were collected from the antenatal cards and any additional information was collected by face-to-face interview using a questionnaire. A multiple regression model was developed to predict macrosomia using SPSS ver.18.

RESULTS

The significant variables that influence macrosomia in this study were mother's age, mother's body mass index (BMI), weight gain, parity, mother's ethnicity, father's BMI, gestational week, diabetes during pregnancy and neonatal sex. Diabetes during pregnancy is an important risk factor for macrosomia; by using this parameter alone the risk of macrosomia can be predicted with a sensitivity rate of 70% and specificity of 70%. By including other maternal factors such as maternal age, pre-pregnancy BMI, weight gain, parity, ethnicity, as well as father's BMI, gestational weeks and neonate sex, the sensitivity and specificity were improved to 80% and 75%, respectively.

CONCLUSION

A regression model was developed and this could be used in health centers to predict macrosomia for purpose of referral to higher centers.

摘要

目的

确定影响孕妇巨大儿发生的危险因素,并建立预测巨大儿的回归模型。

方法

在马来西亚一家三级医院对2332名孕妇进行了一项横断面研究。数据从妇产科进行回顾性收集。从产前卡片中收集影响胎儿体重的因素,并通过使用问卷进行面对面访谈收集任何其他信息。使用SPSS 18.0版建立多元回归模型来预测巨大儿。

结果

本研究中影响巨大儿的显著变量包括母亲年龄、母亲体重指数(BMI)、体重增加、产次、母亲种族、父亲BMI、孕周、孕期糖尿病和新生儿性别。孕期糖尿病是巨大儿的重要危险因素;仅使用该参数,巨大儿风险的预测灵敏度为70%,特异度为70%。纳入其他母亲因素,如母亲年龄、孕前BMI、体重增加、产次、种族,以及父亲BMI、孕周和新生儿性别后,灵敏度和特异度分别提高到80%和75%。

结论

建立了一个回归模型,可用于健康中心预测巨大儿,以便转诊至上级中心。

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