Yan Mingxing, Li Feng, Jun Shi, Li Liying, You Wenqiang, Hu Liping
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.
Int J Gen Med. 2025 Apr 28;18:2289-2301. doi: 10.2147/IJGM.S510654. eCollection 2025.
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.
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.
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.
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.
子痫前期(PE)是一种严重的妊娠并发症,与不良的母婴结局相关,尤其是胎儿生长受限(FGR)。识别PE患者发生FGR的危险因素有助于及时进行管理并改善新生儿结局。
这项回顾性病例对照研究分析了2016年1月至2023年10月在福建省妇幼保健院发生的714例单胎妊娠合并子痫前期的病例。根据是否存在FGR对参与者进行分类。收集并分析临床数据,包括人口统计学特征、实验室参数、产时并发症和新生儿结局。我们采用最小绝对收缩和选择算子(LASSO)逻辑回归来识别FGR的独立危险因素。然后使用一个训练队列(499名参与者)和一个验证队列(215名参与者)开发并验证了一个个体化预测列线图。使用受试者操作特征(ROC)曲线下面积、决策曲线和校准分析来评估该模型的辨别力、临床实用性和校准情况。
该研究确定了256例有FGR的女性和458例无FGR的女性。该研究确定了PE患者发生FGR的九个重要预测因素,包括高血压家族史、天冬氨酸转氨酶(AST)、尿酸(URIC)、分娩方式、平均血小板体积(MPV)、凝血酶原时间(PT)、子痫前期的严重程度、产后体重和孕周。列线图显示出优异的预测性能,训练队列中的ROC曲线下面积(AUC)为0.93(95%CI 0.91 - 0.96),验证队列中的AUC为0.90(95%CI 0.85 - 0.95)。校准图表明,两个队列中预测概率与观察到的结局密切匹配,而决策曲线分析(DCA)表明,列线图为有FGR风险的患者提供了令人满意的净效益。
本研究中开发的列线图是预测子痫前期孕妇发生FGR的可靠工具。其应用可增强临床决策,并改善高危人群的胎儿结局。建议在不同人群中进一步验证以加强其临床实用性。