文章基本信息

标题：Cluster Analysis as a Prediction Tool for Pregnancy Outcomes
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作者：Banjari, Ines ; Kenjerić, Daniela ; Šolić, Krešimir 等
期刊名称：Collegium Antropologicum
印刷版ISSN：0350-6134
出版年度：2015
卷号：39
期号：1
页码：247-252
语种：English
出版社：Hrvatsko antropološko društvo
摘要：Considering specifi c physiology changes during gestation and thinking of pregnancy as a »critical window«, classifi cation of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classifi cation of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offi ces’ were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classifi cation accuracy rate with three branches or groups of pregnant women showing statistically signifi cant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a signifi cantly higher incidence of delivering baby of higher birth weight but they gain signifi cantly less weight during pregnancy. Their babies are also longer, and these women have signifi cantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.
关键词：pregnant women; cluster analysis; pre-pregnancy BMI; maternal age; pregnancy outcomes; caesarean delivery; gestosis; weight gain; birth...