Prediction of Placental Microflow Combined with Serum Cystatin C in Late-Onset Preeclampsia
10.3969/j.issn.1005-5185.2025.03.014
- VernacularTitle:胎盘微血流联合血清Cys C对晚发型子痫前期的预测价值
- Author:
Wenwen WANG
1
;
Lin TANG
1
;
Fan LI
1
;
Tong ZHU
1
;
Man QIN
1
;
Ling CHEN
1
Author Information
1. 石河子大学第一附属医院超声医学科,新疆 石河子 832000
- Publication Type:Journal Article
- Keywords:
Late-onset preeclampsia;
Vascularization index;
Flow index;
Vascularization-flow index;
Serum cystatin C;
Ultrasonography;
Forecasting
- From:
Chinese Journal of Medical Imaging
2025;33(3):304-309
- CountryChina
- Language:Chinese
-
Abstract:
Purpose To investigate the predictive value of placental microflow combined with serum cystatin C(Cys C)for late-onset preeclampsia(LOP).Materials and Methods This was a prospective study including 188 singleton pregnant women who underwent prenatal ultrasound examination and delivered in the First Affiliated Hospital,School of Medicine,Shihezi University from October 2021 to October 2022.The placental microvascular indexes,including vascularization index,flow index and vascularization-flow index(VFI),were detected by three-dimensional power Doppler ultrasound in the second trimester,and the serum Cys C level was detected.The pregnancy outcome of the pregnant women was divided into LOP group and normal group(NLOP group),and the predictive value of placental microflow combined with serum Cys C for LOP was analyzed.Results Placental vascularization index and VFI of the LOP group were lower than those of the NLOP group(29.77±11.97 vs.44.44±9.86,9.23±3.51 vs.15.05±4.38).However,serum Cys C in the LOP group was higher than that in the NLOP group[(1.13±0.17)mg/L vs.(0.84±0.18)mg/L],and the differences were statistically significant(t=-3.616,-4.790,4.682,all P<0.05).The area under the curve of placental VFI combined with serum Cys C for predicting LOP was 0.899,which had the highest predictive value.Conclusion Placental VFI combined with serum Cys C detection can help to improve the prediction efficiency of LOP,and it is better than each single item.
