Implementation of First-Trimester Screening and Prevention of Preeclampsia: A Stepped Wedge Cluster-Randomized Trial in Asia.

Background: This trial aimed to assess the efficacy, acceptability, and safety of a first-trimester screen-and-prevent strategy for preterm preeclampsia in Asia.

Methods: Between August 1, 2019, and February 28, 2022, this multicenter stepped wedge cluster randomized trial included maternity/diagnostic units from 10 regions in Asia. The trial started with a period where all recruiting centers provided routine antenatal care without study-related intervention.

Validation of the first-trimester machine learning model for predicting pre-eclampsia in an Asian population.

Objectives: To evaluate the performance of an artificial intelligence (AI) and machine learning (ML) model for first-trimester screening for pre-eclampsia in a large Asian population.

Methods: This was a secondary analysis of a multicenter prospective cohort study in 10 935 participants with singleton pregnancies attending for routine pregnancy care at 11-13 weeks of gestation in seven regions in Asia between December 2016 and June 2018. We applied the AI+ML model for the first-trimester prediction of preterm pre-eclampsia (<37 weeks), term pre-eclampsia (≥37 weeks), and any pre-eclampsia, which was derived and tested in a cohort of pregnant participants in the UK (Model 1).

Urine Congo red test for the detection of preeclampsia in pregnant women presenting with suspected preeclampsia.

Objectives: To determine the predictive performance of the urine Congo red point-of-care test for the identification of preeclampsia in women presenting with suspected preeclampsia.

Methods: A prospective multi-center cohort study was conducted to include women with suspected preeclampsia ( = 244). The urine Congo red test was determined (score range 1-8).

Evaluation of screening performance of first-trimester competing-risks prediction model for small-for-gestational age in Asian population.

Objective: To examine the external validity of the Fetal Medicine Foundation (FMF) competing-risks model for the prediction of small-for-gestational age (SGA) at 11-14 weeks' gestation in an Asian population.

Methods: This was a secondary analysis of a multicenter prospective cohort study in 10 120 women with a singleton pregnancy undergoing routine assessment at 11-14 weeks' gestation. We applied the FMF competing-risks model for the first-trimester prediction of SGA, combining maternal characteristics and medical history with measurements of mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI) and serum placental growth factor (PlGF) concentration.

Accuracy of placental growth factor alone or in combination with soluble fms-like tyrosine kinase-1 or maternal factors in detecting preeclampsia in asymptomatic women in the second and third trimesters: a systematic review and meta-analysis.

Objective: This study aimed to: (1) identify all relevant studies reporting on the diagnostic accuracy of maternal circulating placental growth factor) alone or as a ratio with soluble fms-like tyrosine kinase-1), and of placental growth factor-based models (placental growth factor combined with maternal factors±other biomarkers) in the second or third trimester to predict subsequent development of preeclampsia in asymptomatic women; (2) estimate a hierarchical summary receiver-operating characteristic curve for studies reporting on the same test but different thresholds, gestational ages, and populations; and (3) select the best method to screen for preeclampsia in asymptomatic women during the second and third trimester of pregnancy by comparing the diagnostic accuracy of each method.

Data Sources: A systematic search was performed through MEDLINE, Embase, CENTRAL, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform databases from January 1, 1985 to April 15, 2021.