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Prediction model of fetal meconium-stained amniotic fluid in re-pregnant women with intrahepatic cholestasis of pregnancy / 浙江大学学报·医学版
Journal of Zhejiang University. Medical sciences ; (6): 264-268, 2015.
Article in Chinese | WPRIM | ID: wpr-255200
ABSTRACT
<p><b>OBJECTIVE</b>To establish a prediction model of fetal meconium-stained amniotic fluid in re-pregnant women with intrahepatic cholestasis of pregnancy (ICP).</p><p><b>METHODS</b>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.</p><p><b>RESULTS</b>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.</p><p><b>CONCLUSION</b>The established ANN model can be used for predicting fetal meconium-stained amniotic fluid in re-pregnant women with ICP.</p>
Subject(s)
Full text: Available Index: WPRIM (Western Pacific) Main subject: Pathology / Pregnancy Complications / Chemistry / Cholestasis, Intrahepatic / Sensitivity and Specificity / Neural Networks, Computer / Fetus / Amniotic Fluid / Meconium Type of study: Diagnostic study / Prognostic study Limits: Female / Humans / Infant, Newborn / Pregnancy Language: Chinese Journal: Journal of Zhejiang University. Medical sciences Year: 2015 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Pathology / Pregnancy Complications / Chemistry / Cholestasis, Intrahepatic / Sensitivity and Specificity / Neural Networks, Computer / Fetus / Amniotic Fluid / Meconium Type of study: Diagnostic study / Prognostic study Limits: Female / Humans / Infant, Newborn / Pregnancy Language: Chinese Journal: Journal of Zhejiang University. Medical sciences Year: 2015 Type: Article