Psychosocial Injuries Research Center, Ilam University of Medical Sciences, Ilam, Iran ; Department of Midwifery, Faculty of Nursing and Midwifery, Ilam University of Medical Sciences, Ilam, Iran.
Arch Med Sci. 2013 Aug 30;9(4):684-9. doi: 10.5114/aoms.2013.36900. Epub 2013 Aug 8.
Preeclampsia is a major cause of maternal and prenatal mortality and morbidity worldwide. There are some risk factors that are of great value for prediction of preeclampsia by which the practitioners can counsel women regarding this disease. The aim of this study was to analyze the role of such risk factors as the predictors associated with preeclampsia among Iranian women using logistic regression.
The role of some risk factors such as demographic, anthropometric, medical and obstetrics variables in preeclampsia among 610 women attending the obstetric ward of Mustafa hospital in Ilam in the west of Iran was analyzed from May to September 2010. All the pregnant women referred to this hospital participated in the study except those cases that had abortion. Unvaried and Multiple logistic regression analyses were used to find the predictive factors behind preeclampsia. Standard errors of area compute using nonparametric methods. A p-value of 0.05 was considered statistically significant.
Prevalence of preeclampsia was 9.5% (95% CI 7.4-11.6%). Predictive model build using history of preeclampsia, history of hypertension, and history of infertility. Area Under the Receiver Operation Character (AUROC) was estimated 0.67 (95% CI 0.59-0.67, p < 0.01) that showed that using the model is much better than having a guess.
The odd of preeclampsia increased in women with a history of preeclampsia, hypertension and infertility. Recognition of these predictor factors would improve the ability to diagnose and monitor women likely to develop preeclampsia before the onset of disease for timely interventions.
子痫前期是全球孕产妇和围产儿死亡和发病的主要原因。有一些危险因素对于预测子痫前期具有重要价值,医生可以据此向妇女提供关于这种疾病的咨询。本研究旨在使用逻辑回归分析伊朗妇女中与子痫前期相关的这些危险因素作为预测因子的作用。
2010 年 5 月至 9 月,对伊朗西部伊拉姆省穆斯塔法医院产科病房的 610 名孕妇进行了一些危险因素(包括人口统计学、人体测量学、医学和产科变量)与子痫前期关系的分析,这些孕妇除流产外均参与了研究。使用非参数方法计算了面积标准误差。采用不变量和多元逻辑回归分析来寻找子痫前期背后的预测因素。p 值<0.05 为统计学显著。
子痫前期的患病率为 9.5%(95%CI 7.4-11.6%)。预测模型是基于子痫前期史、高血压史和不孕史建立的。接收器操作特征曲线下面积(AUROC)估计为 0.67(95%CI 0.59-0.67,p<0.01),表明使用该模型比猜测要好得多。
有子痫前期史、高血压史和不孕史的妇女发生子痫前期的风险增加。识别这些预测因素将提高在疾病发作前诊断和监测可能发生子痫前期的妇女的能力,以便及时进行干预。