未足月胎膜早破并发组织学绒毛膜羊膜炎预测模型Nomogram图的建立

The establishment of a nomogram for prediction of preterm premature rupture of membranes with histological chorioamnionitis

目的:建立未足月胎膜早破(PPROM)并发组织学绒毛膜羊膜炎(HCA)预测模型Nomogram图,提高对HCA的临床诊断效率,为HCA的早期诊断提供可靠的依据。方法:回顾分析2015年12月~2017年12月于中国医科大学附属盛京医院住院分娩的孕周为32~36+6周且符合本研究标准的胎膜早破患者168例,其中未并发HCA者90例(对照组),并发HCA者78例(病例组)。综合孕妇年龄、破膜时间、入院时和分娩前24h内白细胞计数、中性粒细胞百分比和C-反应蛋白水平等指标,利用SPSS22.0建立logistics回归预测模型,并采用受试者工作特征曲线检验其区分度、Hosmer-Lemeshow检验其校准度来评估预测模型,采用R语言绘制Nomogram图。结果:未足月胎膜早破并发HCA预测模型为:logit P=-2.643-0.051*Age+0.009*Time-0.020*WBC1-0.057*NE1+0.068*CRP1+0.285*WBC2+0.056*NE2+0.006*CRP2。将预测模型预测概率建立受试者工作特征曲线,其曲线下面积为0.781,表明该模型的区分度较好,诊断效果较好,采用Hosmer-Lemeshow检验发现该预测模型具有较好的校准能力。R语言建立Nomogram图,能迅速通过孕妇年龄、破膜时间、入院时和分娩前24h内白细胞计数、中性粒细胞百分比和C-反应蛋白水平评估HCA的发生率。结论:联合孕妇年龄、破膜时间、入院时和分娩前24h内白细胞计数、中性粒细胞百分比和C-反应蛋白水平等指标建立有效预测模型并绘制Nomogram图,有助于对未足月胎膜早破孕妇并发HCA进行早期诊断评估。

Objective:To establish a predictive model of Nomogram for preterm premature rupture of membranes with histological chorioamnionitis,which can provide the efficiency of clinical diagnosis and a reliable basis for the early diagnosis of histological chorioamnionitis.Methods:A retrospective analysis of 168 patients with premature rupture of membranes who met the standard of 32 to 36+6 weeks in the Department of Obstetrics and Gynecology,Shengjing Hospital,China Medical University from Dec.2015 to Dec.2017.The control group was 90 cases without histological chorioamnionitis,the case group was 78 cases with histological chorioamnionitis.Basic indicators of hospitalized pregnant women and laboratory indicators were included and detected,such as maternal age,membrane rupture time,the index of white blood cell count,neutrophil percentage,and C-reactive protein level were integrated at admission time and 24 hours before delivery.The logistic regression model was established using in SPSS 22.0,and the receiver operating characteristic curve was used to test the discrimination of the prediction model,the Hosmer-Lemeshow verified its calibration to evaluate the prediction model,and the Nomogram was plotted in R language.Results:The prediction model of premature rupture of membranes with histological chorioamnionitis was:logit P=-2.643-0.051×Age+0.009×Time-0.020×WBC1-0.057×NE1+0.068×CRP1+0.285×WBC2+0.056×NE2+0.006×CRP2.The ROC curve was established by predicting the prediction model's probabilities.The area under the curve was 0.781,indicating that the model had good discrimination and good diagnostic results.The Hosmer-Lemeshow test showed that the model had better calibration ability.A Nomogram,established by R language,could quickly assess the incidence of histological chorioamnionitis through maternal age,membrane rupture time,the index of white blood cell count,neutrophil percentage,and C-reactive protein level were integrated at admission time and 24 hours before delivery.Conclusion:An effective predictive model for the combination of maternal age,membrane rupture time,the index of white blood cell count,neutrophil percentage,and C-reactive protein level which were integrated at admission time and 24 hours before delivery may be helpful for prediction and early diagnostic assessment of preterm premature rupture of membranes with histological chorioamnionitis.