Preeclampsia Screening and Prediction
5
Issued Date
2026-01-01
Resource Type
Scopus ID
2-s2.0-105043195001
Journal Title
Prevention of Complications in Obstetrics
Start Page
195
End Page
218
Rights Holder(s)
SCOPUS
Bibliographic Citation
Prevention of Complications in Obstetrics (2026) , 195-218
Suggested Citation
Chaemsaithong P., Poon L.C. Preeclampsia Screening and Prediction. Prevention of Complications in Obstetrics (2026) , 195-218. 218. doi:10.1007/978-3-032-23479-7_13 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/117777
Title
Preeclampsia Screening and Prediction
Author(s)
Author's Affiliation
Corresponding Author(s)
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Abstract
Preeclampsia is a major cause of maternal and perinatal morbidity and mortality. Current evidence suggests that the administration of low-dose aspirin initiated before 16 weeks of gestation significantly reduces the rate of preterm preeclampsia by 62%. Therefore, it is key to identify patients at risk for preterm preeclampsia. Several first-trimester preeclampsia prediction models have been reported; however, most of them have not undergone or failed external validation. Effective screening recommended by the Fetal Medicine Foundation (FMF) consists of a combination of maternal risk factors, mean arterial pressure, uterine artery pulsatility index (UtA-PI), and placental growth factor (PlGF), which is also called the "FMF triple test." The FMF triple test has detection rates of 90% and 75% for the prediction of early and preterm preeclampsia, respectively, with a 10% false positive rate, and has undergone successful internal and external validations. The performance of screening by the FMF triple test is superior to that of the traditional method based on maternal risk factors alone. The number needed to screen to prevent one case of preterm preeclampsia by the FMF triple test is 250. Similar risk assessment can be performed in all pregnant women during the second or third trimester, irrespective of first-trimester screening results. Using PlGF, UtA-PI, and sFlt-1 combined with other investigative tools is part of risk assessment. The key to maintaining optimal screening performance is establishing standardized protocols for biomarker measurements and regular biomarker quality assessment, as inaccurate measurements can affect screening performance.