First-trimester screening and small for gestational age in twin pregnancies: a single center cohort study
First-trimester screening and small for gestational age in twin pregnancies: a single center cohort study

First-trimester screening and small for gestational age in twin pregnancies: a single center cohort study

Arch Gynecol Obstet. 2024 Dec 26. doi: 10.1007/s00404-024-07884-6. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aimed to investigate the association between maternal factors and first-trimester biophysical and biochemical markers with small for gestational age (SGA) neonates in twin pregnancies (TwPs).

METHODS: Single-center retrospective cohort study of TwPs followed from January 2010 to December 2022 at a tertiary perinatal center, Portugal. Maternal and pregnancy characteristics, mean arterial pressure, pregnancy-associated plasma protein-A (PAPP-A), β-human chorionic gonadotropin (β-HCG), and uterine artery pulsatility index (UtA-PI) were analyzed. Univariable, multivariable logistic regression (LR) and receiver-operating characteristic curve analyses were performed. The main outcome measures considered were: SGA < 3rd, < 5th and < 10th percentile, the composite outcome of SGA combined with preterm birth (PTB) (< 32, < 34, and < 36 weeks).

RESULTS: 572 TwPs were included, 450 (78.7%) DC and 122 (21.3%) MC. TwPs affected with SGA < 3rd, < 5th or < 10th percentiles were 120/572 (20.9%), 157/572 (27.4%) and 190/572 (33.2%), respectively. SGA < 3rd percentile was associated with a higher rate of PTB, 59.0% of cases < 32 weeks, OR 6.4 (95% CI: 3.2-12.7, p < 0.001). Shorter maternal height, UtA-PI ≥ 95th percentile, and low PAPP-A were identified as significant independent risk factors associated with SGA and SGA combined with PTB. The best LR model was obtained for the composite outcome SGA < 3rd percentile and PTB < 32 weeks, with an AUC of 0.834, a sensitivity rate of 77%, and a false positive rate of 17%.

CONCLUSION: The majority of pregnancies at risk for SGA combined with prematurity can be detected in the first trimester. However, larger datasets are necessary to develop robust predictive models.

PMID:39724362 | DOI:10.1007/s00404-024-07884-6