Mingxing Yan, Feng Li, Shi Jun, Liying Li, Wenqiang You, Liping Hu

Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University; Fujian Clinical Research Center for Maternal-Fetal Medicine; National Key Obstetric Clinical Specialty Construction Institution of China, Fuzhou, 350000, People’s Republic of China

Correspondence: Liping Hu, Obstetrics Department, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, 18 Daoshan Road, Gu’lou District, Fuzhou, Fujian, 350000, People’s Republic of China, Tel +86-18650735290, Fax +86-591-87279625, Email hlpywq@163.com

Background: Preeclampsia (PE) is a significant pregnancy complication associated with adverse maternal and fetal outcomes, particularly fetal growth restriction (FGR). Identifying risk factors for FGR in PE patients can facilitate timely management and improve neonatal outcomes.
Methods: This retrospective case-control study analyzed 714 singleton pregnancies complicated by preeclampsia at Fujian Maternity and Child Health Hospital from January 2016 to October 2023. Participants were categorized based on the presence of FGR. Clinical data, including demographic characteristics, laboratory parameters, intrapartum complications and neonatal outcomes, were collected and analyzed. We employed least absolute shrinkage and selection operator (LASSO) logistic regression to identify independent risk factors for FGR. An individualized predictive nomogram was then developed and validated using a training (499 participants) and a validation cohort (215 participants). The model’s discrimination, clinical usefulness, and calibration were assessed using the area under the receiver operating characteristic (ROC) curve, decision curve, and calibration analysis.
Results: The study identified 256 women with FGR and 458 without FGR.The research identified nine significant predictors for FGR in PE patients, including family history of hypertension, aspartate aminotransferase (AST), uric acid (URIC), mode of delivery, mean platelet volume (MPV), prothrombin time (PT), severity of preeclampsia, post-pregnancy weight, and gestational age. The nomogram demonstrated excellent predictive performance, with an area under the ROC curve (AUC) of 0.93 (95% CI 0.91– 0.96) in the training cohort and 0.90 (95% CI 0.85– 0.95) in the validation cohort. Calibration plots indicated that predicted probabilities closely matched observed outcomes in both cohorts, while decision curve analysis (DCA) indicated that the nomogram provided a satisfactory net benefit for patients at risk of FGR.
Conclusion: The nomogram developed in this study serves as a reliable tool for predicting FGR in pregnant individuals with preeclampsia. Its application could enhance clinical decision-making and improve fetal outcomes in at-risk populations. Further validation in diverse populations is recommended to strengthen its clinical utility.

Keywords: preeclampsia fetal growth restriction predictive model nomogram risk factors