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Diagnostic value of doppler ultrasound indices of maternal renal interlobar vasculature in the prediction of preeclampsia

We aimed to determine the diagnostic accuracy of maternal renal vasculature Doppler ultrasound indices in the prediction of preeclampsia. A total of 40 pregnant women with a gestational age of more than 20 weeks were included and followed. The pregnant women underwent a Doppler ultrasound examinatio...

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Bibliographic Details
Published in:Journal of medicine and life 2021-03, Vol.14 (2), p.277-283
Main Authors: Salehi, Mohammad Gharib, Shobeiri, Elham, Naleini, Farhad, Bazargan, Mohammad Saied
Format: Article
Language:English
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Summary:We aimed to determine the diagnostic accuracy of maternal renal vasculature Doppler ultrasound indices in the prediction of preeclampsia. A total of 40 pregnant women with a gestational age of more than 20 weeks were included and followed. The pregnant women underwent a Doppler ultrasound examination to measure the resistance index (RI) of the interlobar arteries of right and left kidneys and the renal interlobar vein impedance index (RIVI). Of the included women, 15 patients developed preeclampsia based on clinical and laboratory criteria. The renal vascular Doppler ultrasound indices were compared between the two groups. Then, using the Receiver Operating Characteristic (ROC) analysis, the diagnostic accuracy of interlobar artery RI and RIVI were investigated in the prediction of preeclampsia occurrence. RIVI values of right and left kidneys were significantly higher in the preeclampsia group compared to the normal pregnancy group. The left kidney interlobar artery RI at a cut-point of 0.59 had a sensitivity of 100% and a specificity of 40% (area under curve=0.7, P-0.03) in the prediction of preeclampsia. The RIVI of the left kidney (adjusted odds ratio=17.14, 95% CI = 3.46 to 47.28) was statistically significant in predicting preeclampsia (P-0.006). We found that, besides other routine methods, using Doppler ultrasound and measuring RIVI can be reliable in the prediction of preeclampsia.
ISSN:1844-122X
1844-3117
DOI:10.25122/jml-2019-0161