A Comparison of Preeclampsia Screening Using Clinical Risk Factors and the Fetal Medicine Foundation Algorithm.

Area of Science:

• Obstetrics and Gynecology
• Maternal-Fetal Medicine
• Clinical Diagnostics

Background:

• Preeclampsia is a significant cause of maternal and fetal morbidity.
• Early identification of high-risk pregnancies is crucial for timely intervention.
• Current screening methods include clinical risk factors and algorithmic approaches.

Purpose of the Study:

• To evaluate the efficacy of aspirin in preventing preterm preeclampsia.
• To compare the predictive performance of clinical factors versus the Fetal Medicine Foundation (FMF) algorithm for preeclampsia risk assessment.
• To determine the optimal screening tool for identifying women at risk of preeclampsia.

Main Methods:

• The study assessed the ability of aspirin to prevent preterm preeclampsia in high-risk populations.
• Risk stratification was performed using clinical factors and the FMF algorithm, which integrates placental growth factor (PlGF) with other biomarkers.
• Incidence rates of preeclampsia and preterm preeclampsia were analyzed in relation to FMF risk scores among nulliparous women.

Main Results:

• A low FMF risk score was associated with significantly low incidences of preeclampsia (<2.5%) and preterm preeclampsia (<0.5%).
• A high FMF risk score correlated with substantially higher incidences of preeclampsia (>6%) and preterm preeclampsia (>1.5%).
• The FMF algorithm demonstrated strong predictive value irrespective of traditional clinical risk factors.

Conclusions:

• Aspirin is effective in preventing the majority of preterm preeclampsia cases in identified high-risk women.
• The FMF algorithm, particularly when including PlGF, is a superior tool for preeclampsia screening compared to clinical factors alone.
• The FMF algorithm including PlGF should be adopted as the primary screening method for preeclampsia when available.