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Updated: Oct 25, 2025

The 4-vessel Sampling Approach to Integrative Studies of Human Placental Physiology In Vivo
Published on: August 2, 2017
The clinical value of platelet parameters combined with sFlt-1/PlGF in predicting preeclampsia
Yan Li1, Lifang Sun1, Xiuli Zheng1
1Department of Obstetrics and Gynecology, Beijing Jishuitan Hospital, Beijing, China.
Background:
The aim of this study is to evaluate the association between platelet parameters and soluble vascular endothelial growth factor receptor-1 (sFlt-1)/placenta growth factor (PlGF) in preeclampsia (PE) and establish a prediction model by analyzing commonly used biochemical markers.
Methods:
A nested case-control study involving 270 pregnant women in their second trimester from the Beijing Jishuitan Hospital was conducted. They were divided into PE group and control group. The levels of PlGF, sFlt-1, sFlt-1/PlGF, and platelet parameters were recorded and compared at 20-24 gestational weeks. The correlation between platelet parameters and PlGF, sFlt-1, and sFlt-1/PLGF was then analyzed. A receiver operating characteristic (ROC) curve was used to calculate the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of various biomarkers in predicting PE.
Results:
In PE group, the levels of mean platelet volume (MPV), platelet distribution width (PDW), sFlt-1, and sFlt-1/PLGF were higher than in the control group, while the levels of platelet count (PC), PC/MPV, and PLGF in PE group were lower. Spearman correlation analysis showed that PC and PC/MPV were negatively correlated with sFlt-1 and sFlt-1/PLGF, and positively correlated with PLGF, while further analysis found that PC/MPV had the largest area under the ROC curve with sensitivity of 83.7% and specificity of 86.2%. The area under curve (AUC) of sFlt-1, PLGF, and sFlt-1/PLGF for predicting PE were 0.731, 0.772, and 0.825, respectively. Their AUCs could be improved to 0.820, 0.838, and 0.873 when combined with PC/MPV.
Conclusions:
The accuracy of sFlt-1/PlGF in predicting the risk of PE in the second trimester is significantly improved when combined with PC/MPV, which is expected to be an ideal tool for PE prediction.
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