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Predictive factors for preeclampsia in pregnant women: A unvariate and multivariate logistic regression analysis

机译:孕妇先​​兆子痫的预测因素:单因素和多因素logistic回归分析

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Introduction: Several risk factors have been used to predict preeclampsia. The role of some risk factors as predictors associated with preeclampsia among Iranian women was analyzed in the present study using logistic regression. Materials and Methods: 610 women attending the obstetric ward of Mustafa hospital in Ilam were enrolled in this study. Demographic variables such as age, Body Mass Index (BMI), medical and obstetrics variables such as education, number of pregnancy, abortion and parity from May to September 2010 were analyzed. We used the unvaried and multiple logistic regression analyses to predict preeclampsia. Results: The history of preeclampsia, hypertension, and infertility showed to be good independent predicator variables for preeclampsia using multivariate logistic regression analysis (OR was 5.46, 2.34 and 3.07 respectively). Area Under the Receiver Operation Character (AUROC) was estimated to be 0.67 (95% CI 0.59-0.67, p<0.01) indicating the efficacy of the model for the prediction. Conclusion: The history of preeclampsia, hypertension and infertility predict preeclampsia with an increased odds ratio. Using such variables in regression analysis can help to diagnose preeclampsia beforehand and hence allow timely intervention.
机译:简介:一些风险因素已被用来预测先兆子痫。在本研究中,使用logistic回归分析了某些危险因素作为伊朗妇女先兆子痫相关的预测因子的作用。材料与方法:610名在伊拉姆穆斯塔法医院产科病房就诊的妇女参加了这项研究。分析了2010年5月至2010年9月的人口统计变量,例如年龄,体重指数(BMI),医学和妇产科变量,例如教育程度,怀孕次数,流产和均等。我们使用无变量和多元逻辑回归分析来预测先兆子痫。结果:采用多元逻辑回归分析,先兆子痫,高血压和不育的历史是先兆子痫的良好独立预测变量(OR分别为5.46、2.34和3.07)。接收器操作特征下的面积(AUROC)估计为0.67(95%CI 0.59-0.67,p <0.01),表明该模型可用于预测。结论:先兆子痫,高血压和不育的病史预测先兆子痫的患病几率增加。在回归分析中使用此类变量可以帮助事先诊断先兆子痫,因此可以及时进行干预。

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