[Prediction model of fetal meconium-stained amniotic fluid in re-pregnant women with intrahepatic cholestasis of pregnancy].
To establish a prediction model of fetal meconium-stained amniotic fluid in re-pregnant women with intrahepatic cholestasis of pregnancy (ICP).



Clinical data of 180 re-pregnant women with ICP delivering in Women's Hospital, Zhejiang University School of Medicine between January 2009 to August 2014 were collected. An artificial neural network model (ANN) for risk evaluation of fetal meconium-stained fluid was established and assessed.



The sensitivity, specificity and accuracy of ANN for predicting fetal meconium-stained fluid were 68.0%, 85.0% and 80.3%, respectively. The risk factors with effect weight >10% were pregnancy complications, serum cholyglycine level,maternal age.



The established ANN model can be used for predicting fetal meconium-stained amniotic fluid in re-pregnant women with ICP.
Department of Obstetrics, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China.
Ling-fei
LF
He
Department of Obstetrics, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China.
Yun
Y
Zhao
Department of Obstetrics, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China.
Zheng-ping
ZP
Wang
D000653:Amniotic Fluid / Q000737:chemistry*; D002780:Cholestasis, Intrahepatic / Q000473:pathology*; D005260:Female; D005333:Fetus; D006801:Humans; D007231:Infant, Newborn; D008470:Meconium / Q000737:chemistry*; D016571:Neural Networks, Computer; D011247:Pregnancy; D011248:Pregnancy Complications / Q000473:pathology*; D012680:Sensitivity and Specificity