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预测巨大儿的测量指标评价
引用本文:梁家智,肖兵,李卉,庄琳.预测巨大儿的测量指标评价[J].四川大学学报(医学版),2008,39(4):635-637.
作者姓名:梁家智  肖兵  李卉  庄琳
作者单位:四川省妇幼保健院·四川省妇女儿童医院产科,成都,610031
摘    要:目的对临床使用的胎儿生长监测指标进行评价,寻找适于预测巨大儿的敏感指标。方法对我院2007年分娩的108例巨大儿及同期108例正常出生体重儿的临床资料进行统计分析,包括孕妇宫高、腹围测量值,超声测量胎儿径线(双顶径、股骨长、头围、腹围)。结果孕妇宫高、胎儿双顶径以及双顶径与股骨长之和用于预测巨大儿时,ROC曲线下面积>0.64,且具有统计学意义(P<0.05),这三项指标的诊断指数最高分别为143.5%,138.7%和149.4%。其他测量指标包括孕妇腹围、腹围与宫高之和、胎儿股骨长、腹围、头围用于预测巨大儿时,ROC曲线下面积均<0.63,且不具有统计学意义(P>0.05)。结论临床上孕妇的宫高以及B超下胎儿双顶径及双顶径与股骨长之和是预测巨大儿相对较好的指标。

关 键 词:巨大儿  宫高  双顶径  股骨长ROC曲线

Developing Parameters for Predicting Macrosomia
LIANG Jia-zhi,XIAO Bing,LI Hui,ZHUANG Lin.Developing Parameters for Predicting Macrosomia[J].Journal of West China University of Medical Sciences,2008,39(4):635-637.
Authors:LIANG Jia-zhi  XIAO Bing  LI Hui  ZHUANG Lin
Institution:Obstetrical Department, Sichuan Provincial Hospital for Women & Children, Chengdu 610031, China.
Abstract:OBJECTIVE: To identify appropriate fetal growth parameters that can be used in clinical practice for predicting macrosomia. METHODS: Clinical data of 108 macrosomia babies and 108 babies with normal birth weight who were delivered in 2007 in Sichuan Provincial Hospital for Women & Children were collected and compared. The parameters for the comparisons included maternal abdominal circumference (MAC), fundal height (FH), and fetal diameters measured by ultrasonic imaging such as biparietal diameter(BPD), head circumference (HC), femur length(FL), and abdominal circumference(AC). RESULTS: Maternal fundal height, fetal biparietal diameter, and biparietal diameter plus femur length produced greater than 0.64 of receiver operator characteristic (ROC) curve area for predicting macrosomia (P < 0.05), with a diagnostic index of 143. 5%, 138. 7% and 149.4%, respectively. Other parameters produced less than 0.63 ROC area for predicting macrosomia, with no statistical significance. CONCLUSION: Maternal FH, BPD and BPD plus FL are relatively sensitive parameters for predicting macrosomia.
Keywords:Macrosomia Fundal height Biparietal diameter Femur length ROC curve  
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