超声预测巨大儿的临床价值

目的评价产前超声检查预测巨大儿的临床价值。方法回顾性分析禹州市人民医院146例巨大儿和292例正常足月儿的产前超声检测参数：胎儿腹围（Ac）、股骨长径（FL）、双顶径（BPD）、头围（HC），Logistic回归建立巨大儿预测方程．对受试者工作特征曲线（ROC）、敏感性、特异性等指标评价预测效能。结果①巨大儿组AC（36．65±1．36）cm和FL（78．76±2．79）mm大于非巨大儿组AC（34．66±1．33）cm和FL（74．52±3．08）1T11TI，P。0．000。②AC（OR=3．454）和FL（OR=1．7381均入选以巨大儿为结果变量的回归方程，巨大儿预测方程：P=1／[1＋EXP（87．331-1．239AC-0．553FL）]。⑧万程预测巨大儿的ROC曲线下面积为0．941（95％CI：0．919-0．962）大于AC0．845（95％CI：0．807~0．883）和FL0．837（95％CI：0．797～0．877）的预测面积．P=O．000，方程、Ac和FL诊断巨大儿的敏感性分别是0．842、0．712和0．753，特异性分别是0．904、f）．853和0．812，一致率分别是0．884、0．806和0．792。结论超声测量的胎儿Ac和FL是预测巨大儿的显著参数，将这两个指标综合考虑可槎高巨大胎儿的诊断率。

Clinical value of prediction in fetal macrosomia with ultrasound

[ Objective ] To evaluate the clinical value of prediction in fetal maerosomia with ultrasound. [ Methods ] The ultrasound examination data, such as abdmoinal eireumferenees（AC）, femur lengths（FL）, biparietal diameters（BPD）, head eireumferences（HC） in 146 fetal maerosomia and 292 full-term infants were analyzed.The predicting equation of fetal maerosomia was established via logistic gression.we evaluate the diagnostic values adopting receiver operating eharaeteristie（ROC） curves, sensitivity and specificity. [ Resluts ] ① The fetal maerosomia had bigger AC（36.65 ± 1.36era vs 34.66 ± 1.33 era） and FL（78.76 ±2.79mm vs 74.52 ± 3.08ram） than the non-fetal maerosomia, P=0.000. ② Logistic regression analysis showed that AC（OR=3.454） and FL（OR=l.738） were entered into the regression equation.The predicting equation of fetal macrosomia-P=l/[l＋EXP（gT.331-1.239AC-O.553FL]. ③ The sensitivity, specifieity and aeeuraee of equation for fetal maerosomia were 0.842, 0.904 and 0.884, with an area under the ROC curve （AUC） of 0.941（95%CI：O.919-0.962）.The sensitivity, specificity and aecurace of AC for fetal maerosomia were 0.712, 0.853 and 0.806, with an AUC 0.845（95%CI：0.807-0.883）.The sensitivity, speeifieity and aeeurace of FL for fetal maerosomia were 0.753, 0.812 and 0.792, with an AUC 0.837（95%CI：0.797-0.877）. [ Conclusion ] AC and FL was reliable index to estimate the fetal macrosomia.By combination of two indices were more accuracy.