First-trimester preterm preeclampsia prediction model for prevention with low-dose aspirin

Abstract

Introduction: Preeclampsia (PE) is a major maternal and fetal threat. Previous risk-scoring methods in guidelines lacked precision. The Fetal Medicine Foundation (FMF) proposed a first-trimester PE screening model using Bayes' theorem. PE Prediction Model: FMF prediction model combines maternal characteristics and medical/obstetrical history to determine prior risk and further incorporate maternal blood pressure, maternal serum biomarkers, and uterine Doppler pulsatility index expressed as multiples of the median (MoM) to estimate posterior risk. Low-Dose Aspirin Prevention: Low-dose aspirin is one of the potential PE prevention strategies. Initiating it before 16 weeks is crucial. Aspirin's antiplatelet and anti-inflammatory properties align with PE's pathophysiology. Dosing and resistance warrant further study, but a standard regimen of 150 mg nightly, starting before 16 weeks, is widely supported. PE Prevention in Practice: Clinical trials, including ASPRE, affirm aspirin's role in PE prevention. Starting aspirin based on FMF screening significantly reduces preterm PE and associated complications. Advancements and Prospects: Emerging research explores predictors like maternal ophthalmic arterial waveform. Regional variations, especially in Asian populations, are considered. Machine learning and AI show promise, but examiner expertise remains essential for accurate prediction. In conclusion, integrating FMF's first-trimester PE screening with low-dose aspirin offers a promising strategy. Further advancements may enhance precision and broaden prevention efforts.