Ultrasound Obstet Gynecol. 2023 Oct 30. doi: 10.1002/uog.27522. Online ahead of print.
ABSTRACT
OBJECTIVE: To construct a prediction model for fetal growth restriction (FGR) during the first trimester (11-13+6 weeks) and evaluate its screening performance.
METHODS: Single pregnancies who underwent the first trimester (11-13+6 weeks) ultrasound screening at the Affiliated Suzhou Hospital of Nanjing Medical University from January 2019 to April 2022 were selected as prospective study subjects. Basic clinical information, ultrasound indicators, and serum indicators of pregnant women were collected. Fetal weight assessment was based on the fetal growth curve of the Southern Chinese population, and the definition of FGR was based on standards developed through the Delphi process. The least absolute shrinkage and selection operator (LASSO) regression method was used to select optimal features and analyze the predictive value of each indicator in the model. Finally, the model was constructed, and its discrimination, effectiveness, and clinical usefulness were evaluated.
RESULTS: A total of 1188 pregnant women were included in the final statistical analysis, of whom 108 had FGR. LASSO regression identified 7 predictive features, including a history of maternal hypertension, maternal smoking or passive smoking history, number of pregnancies, uterine artery pulsatility index (UtA PI), ductus venosus pulsatility index (DV PIV), placental growth factor multiples of the median (PlGF MOM), and soluble fms-like tyrosine kinase-1 (sFlt-1) MOM. The nomogram prediction model constructed based on the above predictors predicted FGR more accurately, and the area under the curve (AUC) in the validation cohort was 0.82 (95%CI: 0.74-0.90). The calibration curve and Hosmer-Lemeshow test demonstrated good calibration of the model, while the clinical decision curve and clinical impact curve conclusively support its practical value in the clinical setting.
CONCLUSION: The multi-index prediction model constructed during the first trimester is feasible and has good predictive value. This article is protected by copyright. All rights reserved.
PMID:37902789 | DOI:10.1002/uog.27522
