Establishment of prediction model for uterine scar healing after cesarean section
10.3760/cma.j.cn431274-20201231-01772
- VernacularTitle:剖宫产后子宫瘢痕愈合情况预测模型的建立
- Author:
Xinyi LIU
1
;
Jianqun LIU
Author Information
1. 湖南省妇幼保健院妇产科，长沙 410008
- Keywords:
Cesarean section;
Cicatrix;
Wound healing;
Models, statistical
- From:
Journal of Chinese Physician
2021;23(8):1210-1213,1218
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the related factors of poor uterine scar healing after cesarean section, to establish and evaluate a nomogram model for predicting the risk of poor uterine scar healing after cesarean section.Methods:A total of 170 pregnant women who underwent cesarean section in Hunan Provincical Maternal and Child Care Hospital from April 2019 to May 2020 were prospectively selected as the research objects, and they were divided into poor healing group (48 cases) and good healing group (122 cases) according to the uterine scar healing situation after cesarean section. Logistic regression model was used to analyze the related factors of poor uterine scar healing after cesarean section. The nomograph model for predicting the risk of poor uterine scar healing after cesarean section was drawn by using rms package in R language (R3.6.3). The nomogram model was evaluated and verified by receiver operating characteristic curve (ROC), calibration curve and Hosmer-Lemeshow goodness of fit test.Results:Logistic regression model showed that prenatal body mass index (BMI), the number of cesarean section, premature rupture of membranes, incision position near the cervical orifice, operation time were the independent risk factors of poor uterine scar healing after cesarean section ( P<0.05). According to the above results of logistic regression analysis, a nomogram model was drawn to predict the risk of poor uterine scar healing after cesarean section. The ROC results showed that the area under curve (AUC) of this nomogram model to predict the risk of poor uterine scar healing after cesarean section was 0.902. The calibration curve was a straight line with a slope close to 1 and Hosmer-Lemeshow goodness of fit test (χ 2=5.912, P=0.657) showed that the nomogram model has good consistency and good calibration. Conclusions:The nomogram model for predicting the risks of poor uterine scar healing after cesarean section is established based on the five independent factors of maternal prenatal BMI, number of cesarean section, premature rupture of membranes, incision position near the cervical orifice and operation time, which has good accuracy and differentiation.
