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Prospective evaluation of screening performance of first-trimester prediction models for preterm preeclampsia in an Asian population

Authors :
Alan Wright
Daljit Singh Sahota
Noppadol Chaiyasit
Wing Cheong Leung
George S. H. Yeo
Runmei Ma
Mingming Zheng
Yali Hu
Akihiko Sekizawa
Tuangsit Wataganara
Mahesh Choolani
Shigeru Saito
Tak Yeung Leung
Steven W. Shaw
Katsuhiko Naruse
Mayumi Tokunaka
Piya Chaemsaithong
Ritsuko K Pooh
Liona C. Poon
Suresh Seshadri
Source :
American Journal of Obstetrics and Gynecology. 221:650.e1-650.e16
Publication Year :
2019
Publisher :
Elsevier BV, 2019.

Abstract

The administration of aspirin16 weeks gestation to women who are at high risk for preeclampsia has been shown to reduce the rate of preterm preeclampsia by 65%. The traditional approach to identify such women who are at risk is based on risk factors from maternal characteristics, obstetrics, and medical history as recommended by the American College of Obstetricians and Gynecologists and the National Institute for Health and Care Excellence. An alternative approach to screening for preeclampsia has been developed by the Fetal Medicine Foundation. This approach allows the estimation of patient-specific risks of preeclampsia that requires delivery before a specified gestational age with the use of Bayes theorem-based model.The purpose of this study was to examine the diagnostic accuracy of the Fetal Medicine Foundation Bayes theorem-based model, the American College of Obstetricians and Gynecologists, and the National Institute for Health and Care Excellence recommendations for the prediction of preterm preeclampsia at 11-13There were 224 women (2.05%) who experienced preeclampsia, which included 73 cases (0.67%) of preterm preeclampsia. In pregnancies with preterm preeclampsia, the mean multiples of the median values of mean arterial pressure and uterine artery pulsatility index were significantly higher (mean arterial pressure, 1.099 vs 1.008 [P.001]; uterine artery pulsatility index, 1.188 vs 1.063[P=.006]), and the mean placental growth factor multiples of the median was significantly lower (0.760 vs 1.100 [P.001]) than in women without preeclampsia. The Fetal Medicine Foundation triple test achieved detection rates of 48.2%, 64.0%, 71.8%, and 75.8% at 5%, 10%, 15%, and 20% fixed false-positive rates, respectively, for the prediction of preterm preeclampsia. These were comparable with those of previously published data from the Fetal Medicine Foundation study. Screening that used the American College of Obstetricians and Gynecologists recommendations achieved detection rate of 54.6% at 20.4% false-positive rate. The detection rate with the use of National Institute for Health and Care Excellence guideline was 26.3% at 5.5% false-positive rate.Based on a large number of women, this study has demonstrated that the Fetal Medicine Foundation Bayes theorem-based model is effective in the prediction of preterm preeclampsia in an Asian population and that this method of screening is superior to the approach recommended by American College of Obstetricians and Gynecologists and the National Institute for Health and Care Excellence. We have also shown that the Fetal Medicine Foundation prediction model can be implemented as part of routine prenatal care through the use of the existing infrastructure of routine prenatal care.

Details

ISSN :
00029378
Volume :
221
Database :
OpenAIRE
Journal :
American Journal of Obstetrics and Gynecology
Accession number :
edsair.doi.dedup.....221e8385f7ba02debdb63d2c10d48e60