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Performance and Predictive Value of First Trimester Screening Markers for Down Syndrome in Iranian Pregnancies

机译:伊朗怀孕唐氏综合征综合征的前三个月筛查的性能及预测价值

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Objective: To investigate the performance of first trimester Down syndrome (DS) screening markers in Iranian pregnancies. Although sonographic and serum markers are currently recommended for the first trimester screening of Down syndrome, the screening performance of the markers depends on the race and ethnicity. Materials and methods: A retrospective case-control study using first trimester screening results recorded with the prenatal diagnostic multi-centers in Iran. A total of 6, 384 pregnant women were examined from March 2012 to February 2017. Totally 100 Down syndrome cases and 266 matched controls were selected and the maternal characteristics, sonographic and biochemical screening data were collected. Statistical analysis was performed using logistic regression and descriptive statistics. A decision tree model was designed using the chi-squared automatic interaction detection method based on serum markers. Results: For screening of DS pregnancies, PAPP-A (cut-off 0. 795 MoM) yielded the highest sensitivity (86%) and NB marker presented highest specificity (96. 24%). combination of the biochemical markers PAPP-A and β-hCG (cut-off: 1. 55 MoM) showed the highest sensitivity over other combined markers. The decision-tree model based on serum markers improved (91% DR For a 5% FPR) first trimester screening performance. Conclusion: The novel decision-tree model base on serum markers revealed a better predictive value to achieve high sensitivity and specificity of first trimester Down syndrome screening in Iranian population.
机译:目的:探讨孕季度唐氏综合征(DS)筛查标志物在伊朗怀孕中的表现。虽然目前推荐超声波和血清标记用于唐氏综合征的第一个妊娠期筛查,但标记的筛选性能取决于种族和种族。材料与方法:使用伊朗产前诊断多中心记录的前三个月筛选结果进行回顾性案例对照研究。从2012年3月到2017年3月举行了6,384名孕妇。选择了100次衰退综合征病例和266种匹配对照,并收集了母体特征,超声波和生化筛查数据。使用Logistic回归和描述性统计进行统计分析。使用基于血清标记的CHI方向自动相互作用检测方法设计了决策树模型。结果:用于筛选DS怀孕,PAPP-A(截止0. 795 MOM)产生最高的敏感性(86%),NB标记呈现出最高的特异性(96.24%)。生物化学标志物PAPP-A和β-HCG的组合(截止:15mom)显示出对其他组合标记的最高敏感性。基于血清标记的决策树模型(91%FPR)提高了(91%FPR)前三个月筛选性能。结论:血清标志物的新型决策模型碱基显示出更好的预测值,以实现伊朗人口综合征筛查的高敏感性和特异性。

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