ArticleBMC pregnancy and childbirth2026
The association of first and second-trimester serum biomarkers with adverse perinatal outcomes in late-preterm and term deliveries: a retrospective cohort study.
Article in BMC pregnancy and childbirth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundMaternal serum biomarkers, primarily introduced for aneuploidy screening, have also been investigated as predictors of adverse pregnancy outcomes. However, their value in late-preterm and term pregnancies remains unclear.
methodsIn this retrospective cohort study, 592 singleton pregnancies screened at a tertiary perinatology center between 2020 and 2025 were analyzed. Participants underwent either the first-trimester combined test (n = 461) or the second-trimester triple test (n = 131). Serum biomarker multiples of the median (MoM) were categorized as low (< 0.5), normal (0.5–2.0), or high (> 2.0). Perinatal outcomes—including Apgar scores, umbilical artery pH, neonatal intensive care unit (NICU) admission, and preterm premature rupture of membranes (PPROM)—were assessed using predefined group comparisons, multivariate adjustment, and ROC curve analysis.
resultsLow first-trimester free β-hCG was significantly associated with reduced Apgar scores at 1 and 5 min in term neonates (p = 0.025 and p = 0.005, respectively). In the second trimester, infants with normal AFP levels demonstrated lower umbilical artery pH compared to those with elevated AFP (p = 0.013), and low AFP was associated with an increased risk of NICU admission (p = 0.041). ROC analysis identified an AFP threshold ≥ 1.075 MoM as predictive of PPROM with 75.0% sensitivity and 69.3% specificity (AUC = 0.723, p = 0.035). No significant associations were observed for PAPP-A.
conclusionsFirst-trimester low free β-hCG and second-trimester AFP abnormalities showed modest associations with neonatal outcomes and PPROM in late-preterm and term pregnancies, whereas PAPP-A did not. These findings suggest limited standalone predictive capacity of serum biomarkers, underscoring the need for integrated multiparametric models in risk stratification.
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