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Abstract
To determine the factors predicting the probability of severe postpartum hemorrhage (SPPH) in women undergoing repeat cesarean delivery (RCD). This multicenter, retrospective cohort study involved women who underwent RCD from January 2017 to December 2017, in 11 public tertiary hospitals within 7 provinces of China. The all-variables model and the multivariable logistic regression model (pre-operative, operative and simple model) were developed to estimate the probability of SPPH in development data and external validated in validation data. Discrimination and calibration were evaluated and clinical impact was determined by decision curve analysis. The study consisted of 11,074 women undergoing RCD. 278 (2.5%) women experienced SPPH. The pre-operative simple model including 9 pre-operative features, the operative simple model including 4 pre-operative and 2 intraoperative features and simple model including only 4 closely related pre-operative features showed AUC 0.888, 0.864 and 0.858 in development data and 0.921, 0.928 and 0.925 in validation data, respectively. Nomograms were developed based on predictive models for SPPH. Predictive tools based on clinical characteristics can be used to estimate the probability of SPPH in patients undergoing RCD and help to allow better preparation and management of these patients by using a multidisciplinary approach of cesarean delivery for obstetrician.
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1 Key Laboratory for Major Obstetric Diseases of Guangdong Province,The Third Affiliated Hospital of Guangzhou Medical University, Department of Obstetrics and Gynecology, Guangzhou, China (GRID:grid.417009.b) (ISNI:0000 0004 1758 4591); Key Laboratory for Reproduction and Genetics of Guangdong Higher Education Institutes, Guangzhou, China (GRID:grid.417009.b)
2 Huazhong University of Science and Technology, Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Wuhan, China (GRID:grid.33199.31) (ISNI:0000 0004 0368 7223)
3 Southern Medical University, Department of Obstetrics and Gynecology, Nanfang Hospital, Guangzhou, China (GRID:grid.284723.8) (ISNI:0000 0000 8877 7471)
4 Northwest Women’s and Children’s Hospital, Department of Obstetrics and Gynecology, Xi’an, China (GRID:grid.440257.0)
5 Guangzhou Huadu District Maternal and Child Health Hospital, Department of Obstetrics and Gynecology, Guangzhou, China (GRID:grid.440257.0)
6 The First Affiliated Hospital of Zhengzhou University, Department of Obstetrics and Gynecology, Zhengzhou, China (GRID:grid.412633.1)
7 Peking University Third Hospital, Department of Obstetrics and Gynecology, Beijing, China (GRID:grid.411642.4) (ISNI:0000 0004 0605 3760)
8 The First Affiliated Hospital of Xinjiang Medical University, Department of Obstetrics and Gynecology, Ürümqi, China (GRID:grid.412631.3)
9 The First Affiliated Hospital of Chongqing Medical University, Department of Obstetrics and Gynecology, Chongqing, China (GRID:grid.452206.7)
10 The Second Affiliated Hospital of Guangzhou Medical University, Department of Obstetrics and Gynecology, Guangzhou, China (GRID:grid.412534.5)
11 The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People’s Hospital, Department of Obstetrics and Gynecology, Guangzhou, China (GRID:grid.410737.6) (ISNI:0000 0000 8653 1072)
12 Peking University Health Science Center, Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319)