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Development of a Novel Nomogram for Predicting Placenta Accreta in Patients With Scarred Uterus: A Retrospective Cohort Study

机译:开发一种新型甲型图预测胎儿患者患有疤痕子宫患者的胎盘:回顾性队列研究

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Objective: The aim of this study was to develop a nomogram to predict the risk of placenta accreta in scarred uterus patients in China. Methods: We retrospectively analyzed 8,371 singleton pregnancies with scarred uterus at Shengjing Hospital, affiliated with China Medical University. Two thirds of the patients were randomly assigned to the training set ( n = 5,581), and one third were assigned to the validation set ( n = 2,790). Multivariate logistic regression was performed by using the training set, and the nomogram was developed. Discrimination and calibration were performed by using both the training and validation sets. Results: The multivariate logistic regression model identified number of previous cesarean section, number of vaginal bleeding, medication during pregnancy, and placenta previa as covariates associated with placenta accreta. A nomogram was developed to predict the risk of placenta accreta in the training set with a Harrell's C-index of 0.93 and 0.927 in the training set and validation set, respectively. Calibration of the nomogram predicted placenta accreta corresponding closely with the actual placenta accreta. Conclusion: We developed a nomogram predicting the risk of placenta accreta in scarred uterus patients in China. Validation using both the training set and the validation set demonstrated good discrimination and calibration, suggesting good clinical utility.
机译:目的:本研究的目的是开发一个载体,以预测中国患有伤痕累累的子宫患者的胎盘Accreta风险。方法:我们回顾性地分析了8,371名单身妊娠与中国医科大学附属盛泾医院的伤痕累累的子宫。三分之二的患者随机分配给训练集(n = 5,581),分配给验证集(n = 2,790)。通过使用训练集进行多变量逻辑回归,并开发了NOM图。通过使用训练和验证集进行歧视和校准。结果:多元逻辑回归模型确定了先前的剖宫产,阴道出血,妊娠期间的药物数量,以及胎盘作为与胎盘相关的协变量。制定了一个载体图,以预测培训集和验证集中的哈拉尔C-Inde的培训中胎盘accReta的风险分别在训练集和验证集中。铭文校准预测胎盘Accreta与实际的胎盘相对应。结论:我们开发了一种预测中国患有伤痕累累的子宫患者胎盘血清患者的载体风险。验证使用培训集和验证集显示出良好的歧视和校准,旨在良好的临床效用。

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