剖宫产后子宫瘢痕愈合情况预测模型的建立  

Establishment of prediction model for uterine scar healing after cesarean section

作　　者：刘心怡[1] 刘健群[1] Liu Xinyi;Liu Jianqun(Department of Obstetrics and Gynecology,Hunan Provincial Maternal and Child Care Hospital,Changsha 410008,China)

机构地区：[1]湖南省妇幼保健院妇产科,长沙410008

出　　处：《中国医师杂志》2021年第8期1210-1213,1218,共5页Journal of Chinese Physician

摘　　要：目的通过分析剖宫产后子宫瘢痕愈合不良发生的相关影响因素,建立并评估个体化预测剖宫产后子宫瘢痕愈合不良发生风险的列线图模型。方法前瞻性选取2019年4月至2020年5月在湖南省妇幼保健院行剖宫产的170例孕产妇作为研究对象,并根据产妇剖宫产后子宫瘢痕愈合情况将其分为瘢痕愈合不良组(48例)和瘢痕愈合良好组(122例)。采用logistic回归模型分析剖宫产后子宫瘢痕愈合不良发生的相关影响因素。应用R语言(R 3.6.3)中的rms程序包绘制预测剖宫产后子宫瘢痕愈合不良发生风险的列线图模型。采用研究对象工作特征曲线(R0C)、校准曲线及Hosmer-Lemeshow拟合优度检验评估列线图模型并进行验证。结果Logistic回归模型显示,产前BMI、剖宫产次数、胎膜早破、切口位置临近宫颈内口、手术时间是剖宫产后发生子宫瘢痕愈合不良的独立危险因素(P<0.05)。根据上述logistic回归分析结果,绘制预测剖宫产后子宫瘢痕愈合不良发生风险的列线图模型。R0C结果显示,此列线图模型预测剖宫产后发生子宫瘢痕愈合不良发生风险的AUC为0.902;校准曲线为斜率接近1的直线,Hosmer-Lemeshow拟合优度检验χ^(2)=5.912,P=0.657,显示列线图模型具有良好一致性及较好校准度。结论本研究基于孕妇产前BMI、剖宫产次数、胎膜早破、切口位置临近宫颈内口、手术时间这5项独立影响因素构建的预测剖宫产后子宫瘢痕愈合不良发生风险的列线图模型,具有较好的准确度与区分度。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 membrane

关 键 词：剖宫产术 瘢痕 伤口愈合 模型 统计学 

分 类 号：R719.8[医药卫生—妇产科学]