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

 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.

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