A Prediction Model of Preeclampsia in Hyperglycemia Pregnancy

Yan Fang,1,2 Huali Liu,1,2 Yuan Li,1,2 Ji Cheng,1 Xia Wang,1 Bing Shen,3 Hongbo Chen,1,2 Qunhua Wang4 1Department of Obstetrics and Gynaecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, People’s Republic of China; 2The Fifth Clinical College of Anhui Medical University, Hefei, People’s Republic of China; 3School of Basic Medicine, Anhui Medical University, Hefei, People’s Republic of China; 4Department of Obstetrics and Gynaecology, the First Affiliated Hospital of USTC, Hefei, People’s Republic of ChinaCorrespondence: Hongbo Chen, Maternal and Child Health Hospital Affiliated to Anhui Medical University, No. 15 Yimin Street, Luyang District, Hefei City, Anhui Province, People’s Republic of China, Email chenhongbo@ahmu.edu.cn Qunhua Wang, Department of Obstetrics and Gynaecology, the First Affiliated Hospital of USTC, Hefei, People’s Republic of China, Email wqh971234@163.comPurpose: To investigate the risk factors associated with preeclampsia in hyperglycemic pregnancies and develop a predictive model based on routine pregnancy care.Patients and Methods: The retrospective collection of clinical data was performed on 951 pregnant women with hyperglycemia, including those diagnosed with diabetes in pregnancy (DIP) and gestational diabetes mellitus (GDM), who delivered after 34 weeks of gestation at the Maternal and Child Health Hospital Affiliated to Anhui Medical University between January 2017 and December 2019. Observation indicators included liver and kidney function factors testing at 24– 29+6 weeks gestation, maternal age, and basal blood pressure. The indicators were screened univariately, and the “rms” package in R language was applied to explore the factors associated with PE in HIP pregnancy by stepwise regression. Multivariable logistic regression analysis was used to develop the prediction model. Based on the above results, a nomogram was constructed to predict the risk of PE occurrence in pregnan