Early Magnetic Resonance Imaging Measurements and Prediction of Second Trimester Pregnancy Loss: a Nomogram Model Analysis

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Juanjuan Liu, Minqin Xu, Ling Zhou, Li Yang, Hong Li, Xue Li
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Abstract

Objective: 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. Methods: 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. Results: 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. Conclusion: 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.
早期磁共振成像测量与第二孕期妊娠失败的预测:提名图模型分析
目的研究二胎妊娠流产妇女的磁共振成像(MRI)特征,并建立后续流产的提名图预测模型。方法:进行一项回顾性队列研究:对苏州大学附属第二医院2018年1月至2021年12月既往二胎妊娠流产妇女进行回顾性队列研究。共纳入 245 名患者。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。提取了产妇人口学特征、核磁共振宫颈测量数据。通过多变量逻辑回归分析确定自变量,构建预测模型。通过接受者操作特征曲线(ROC)分析,评估了该模型对女性第二孕期妊娠失败的预测能力,并通过验证数据进行了内部验证。结果在 77 名(31.42%)二胎妊娠流产妇女中观察到宫颈变薄,核磁共振成像显示宫颈管的平均纵向直径为(11.76±2.75)毫米。该模型的灵敏度为 80%,特异性为 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一参数,AUC 为 0.826。结论我们的观察结果表明,宫颈薄和宫颈管纵向直径能可靠地预测二胎妊娠失败。我们建立并验证了一个提名图模型,用于预测下一次妊娠中第二胎妊娠失败的个体概率,并有望改善干预措施的预测和指征。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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