Angiogenic factors assessment in pre‐eclampsia high‐risk population for the prediction of small‐for‐gestational age neonates: A prospective longitudinal study. Issue 2 (26th October 2022) - Mula, Raquel; Prats, Pilar; García, Sandra; Serra, Bernat; Scazzocchio, Elena; Meler, Eva
Abstract: Objective: The authors aimed to compare cross‐sectional versus longitudinal models for prediction of small‐for‐gestational age (SGA) neonates among pregnancies with high risk of early pre‐eclampsia (PE). Methods: A prospective longitudinal study was performed in Hospital Universitari Dexeus, Barcelona. The study population included 390 pregnancies with a high risk of early PE according to the first trimester algorithm. Cross‐sectional models combining first trimester risk plus placental growth factor and FMS‐like tyrosine kinase 1/placental growth factor ratio, respectively, were created at 19–22, 24–26, and 27–30 weeks and compared with a model assessing longitudinal changes of these parameters. Models adding mean uterine artery pulsatility index and abdominal circumference were evaluated. SGA neonates were defined as having a birth weight less than the tenth centile. Results: The predictive performance of a model assessing longitudinal changes of angiogenic factors was similar to that of single evaluations at the second and early third trimesters. The performance of the models combining angiogenic factors with mean uterine artery pulsatility index and abdominal circumference was better than those using only biochemical markers. However, the longitudinal evaluation of biochemical and biophysical parameters did not perform better than cross‐sectional evaluations. Conclusions: Evaluation of angiogenic factors are useful for prediction of SGA neonates in a high‐risk population for early PE. However, longitudinal models do not increase their predictive capacity. Synopsis: Angiogenic factors are useful markers for prediction of small‐for‐gestational age neonates in a high‐risk population although their longitudinal assessment does not increase their predictive capacity.