Liu Juanjuan, Xu Minqin, Zhou Ling, Yang Li, Li Hong, Li Xue
Department of Obstetrics and Gynecology, Second Affiliated Hospital of Soochow University, Suzhou, People's Republic of China.
Department of Radiology, Second Affiliated Hospital of Soochow University, Suzhou, People's Republic of China.
Int J Womens Health. 2024 May 14;16:819-827. doi: 10.2147/IJWH.S453867. eCollection 2024.
To investigate the magnetic resonance imaging (MRI) features of women with prior second-trimester pregnancy loss, and to establish a nomogram prediction model for subsequent miscarriage.
A retrospective cohort study of women with prior second-trimester pregnancy loss from January 2018 to December 2021 in Second Affiliated Hospital of Soochow University was performed. A total of 245 patients were included. Data from January 2018 to December 2019 were used to construct the model, and data from January 2020 to December 2021 were used to evaluate the model. Data on maternal demographic characteristics, MRI cervical measurements were extracted. The prediction model was constructed with independent variables determined by multivariate logistic regression analyses. Through receiver-operating characteristic (ROC) curve analysis, the predictive ability of the model for subsequent second trimester pregnancy loss in women was evaluated, and internal validation was performed through validation data.
Thin cervix was observed in 77 (31.42%) women with prior second-trimester pregnancy loss, the mean longitudinal diameter of cervical canal on MRI was 11.76±2.75mm. The model reached a sensitivity of 80%, specificity of 75.90%, positive predictive value (PPV) of 55.80% and negative predictive value of 90.90%; ROC characteristics proved that the model was superior to any single parameter with an AUC of 0.826.
Our observations showed that thin cervix and longitudinal diameter of cervical canal reliably predicted second trimester pregnancy loss. We developed and validated a nomogram model to predict the individual probability of second trimester pregnancy loss in the next pregnancy and hopefully improve the prediction and indication of interventions.
探讨既往有孕中期流产史女性的磁共振成像（MRI）特征，并建立预测后续流产的列线图预测模型。
对苏州大学附属第二医院2018年1月至2021年12月有既往孕中期流产史的女性进行回顾性队列研究。共纳入245例患者。将2018年1月至2019年12月的数据用于构建模型，2020年1月至2021年12月的数据用于评估模型。提取产妇人口统计学特征、MRI宫颈测量数据。通过多因素逻辑回归分析确定自变量来构建预测模型。通过受试者工作特征（ROC）曲线分析评估该模型对女性后续孕中期流产的预测能力，并通过验证数据进行内部验证。
77例（31.42%）既往有孕中期流产史的女性宫颈较薄，MRI上宫颈管平均纵径为11.76±2.75mm。该模型的灵敏度为80%，特异度为75.90%，阳性预测值（PPV）为55.80%，阴性预测值为90.90%；ROC特征证明该模型优于任何单个参数，AUC为0.826。
我们的观察结果表明，宫颈较薄和宫颈管纵径可可靠地预测孕中期流产。我们开发并验证了一种列线图模型，以预测下一孕期孕中期流产的个体概率，有望改善干预的预测和指征。
