Journal
ULTRASOUND IN OBSTETRICS & GYNECOLOGY
Volume 34, Issue 2, Pages 142-148Publisher
WILEY
DOI: 10.1002/uog.6452
Keywords
gestational hypertension; pre-eclampsia; screening; uterine artery Doppler
Funding
- The Fetal Medicine Foundation [1037116]
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Objectives To examine the performance of screening for hypertensive disorders in pregnancy by a combination of the maternal factor-derived a-priori risk with the uterine artery (UtA) pulsatility index (PI) and to determine whether it is best in such screening to use the mean PI of the two arteries, the highest PI or the lowest PI. Methods This was a prospective screening study for pre-eclampsia (PE) requiring delivery before 34 weeks (early PE), late PE and gestational hypertension (G H) in women attending their routine first hospital visit in pregnancy at 11 + 0 to 13 + 6 weeks of gestation. Maternal history was recorded and color flow Doppler imaging was used to measure the left and right UtA-PI. The performance of screening for PE and GH by a combination of the maternal factor-derived a-priori risks determined in a previous study and the UtA-PI was assessed. Results There were 8061 (96.4%) cases unaffected by PE or GH, 37 (0.4%) that developed early PE, 128 (1.5%) with late PE and 140 (1.7%) with GH. The lowest, mean and highest UtA-PI were significantly higher in early PE and late PE than in the controls (P < 0.000.1) and in early PE than late PE (P < 0.0001). The lowest UtA-PI was higher in GH than in controls (P = 0.014). The best performance in screening was provided by the lowest PI. The detection rate of early PE at a 10% false-positive rate increased from 47% in screening by maternal factors alone to 81% in screening by maternal factors and the lowest UtA-PI. The respective detection rates for late PE increased from 41% to 45% and those for GH increased from 31% to 35%. Conclusions The patient-specific risk for PE and GH can be derived by combining the disease-specific maternal factor-derived a-priori risk with the measurement of the lowest UtA-PI in a multivariate regression model. Copyright (C) 2009 ISUOG. Published by John Wiley & Sons, Ltd.
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