Usefulness of angiogenic factors in prenatal counseling of late-onset fetal growth-restricted and small-for-gestational-age gestations: a prospective observational study

Objectives To create a predictive model including biomarkers and evaluate its ability to predict adverse perinatal outcomes in late-onset small fetuses, ultimately helping to provide individualized counseling at the time of diagnosis. Methods This was a prospective observational study, including singleton pregnancies with an estimated fetal weight (EFW) below the 10th percentile, at a gestational age between 32 + 0 and 36 + 6 weeks of gestation (WG). Variables recorded at diagnosis to predict adverse pregnancy outcomes were: soluble fms-like tyrosine-kinase-1 to placental growth factor ratio (sFlt-1/PlGF), fetal Doppler (umbilical artery and middle cerebral artery), uterine artery pulsatility index (UtAPI), EFW percentile, gestational age, and the presence of maternal risk factors for placental insufficiency. Logistic regression models were developed for the prediction of three co-primary outcomes: composite adverse perinatal outcomes (APO), and the need for elective delivery before 35 or 37 WG. Results Sixty (52.2%) fetal growth restricted (FGR) and 55 (47.8%) small for gestational age (SGA) were enrolled. Thirteen (11.3%) women needed elective delivery before 35 WG and 27 (23.5%) women before 37 WG. At least one APO occurred in 43 (37.4%) pregnancies. The best marker in univariate analyses was the sFlt-1/PlGF ratio [AUC = 0.932 (95% CI, 0.864-0.999)]. The multivariate model including sFlt-1/PlGF showed a better predictive performance for APO than the multivariate model without sFlt-1/PlGF (P < 0.024). Conclusions sFlt-1/PlGF is a good predictor of APO at the time of late-onset FGR/SGA diagnosis. Our predictive models may be useful to provide early individualized prenatal counseling in this group of women. Further studies are needed to validate these preliminary findings in a larger cohort.

Automated summary

This study aims to create a predictive model involving biomarkers to evaluate its ability to predict adverse perinatal outcomes in patients with late-onset small fetuses, thus providing individualized counseling at the time of diagnosis.