Analysis of risk factors and construction of prediction model for early-onset severe preeclampsia complicated with placental abruption
10.3760/cma.j.cn431274-20241022-01595
- VernacularTitle:早发型重度子痫前期并发胎盘早剥的危险因素分析及预测模型构建
- Author:
Na XIA
1
;
Qiong WU
;
Lina WANG
Author Information
1. 无锡市妇幼保健院产科，无锡 214000
- Publication Type:Journal Article
- Keywords:
Early onset preeclampsia;
Abruptio placentae;
Risk factors;
Pregnancy outcome
- From:
Journal of Chinese Physician
2025;27(11):1638-1642
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the risk factors of early-onset severe preeclampsia complicated with placental abruption and construct a prediction model.Methods:The medical records of 100 patients with early-onset severe preeclampsia admitted to the Wuxi Maternity and Child Health Hospital from January 2022 to December 2023 were retrospectively analyzed. Patients were divided into the abruption group (33 cases) and non-abruption group (67 cases) according to the presence of placental abruption. Clinical data of the two groups were compared, and multivariate logistic regression analysis was used to identify risk factors for placental abruption, based on which a nomogram prediction model was established. The receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the model. Additionally, the impact of the severity of placental abruption on maternal and infant outcomes was analyzed.Results:There were no statistically significant differences in age, gestational age at diagnosis, low gestational weight gain, short umbilical cord, abnormal amniotic fluid, or history of abortion between the two groups (all P>0.05). Statistically significant differences were observed in gestational age at delivery, thrombomodulin (TM), placental growth factor (PLGF), placental pathological changes, and proportion of hereditary thrombotic diseases between the two groups (all P<0.05). Multivariate logistic regression analyses showed that smaller gestational age at delivery, higher TM level, lower PLGF level, presence of placental pathological changes, and complicated hereditary thrombotic diseases were associated with a higher risk of placental abruption. The prediction curve of the nomogram model was basically consistent with the calibration curve, showing good discriminative ability. The area under the curve (AUC) was 0.979(95% CI: 0.956, 1.000), with a sensitivity of 93.9%, specificity of 92.5%, and Youden index of 0.864. In patients with severe placental abruption, adverse maternal and infant outcomes increased significantly, including perinatal death and maternal massive hemorrhage. Conclusions:Gestational age, TM, PLGF, placental pathological changes, and hereditary thrombotic diseases are important factors affecting early-onset severe preeclampsia complicated with placental abruption. The constructed prediction model has high predictive efficiency, which can be used for early clinical identification of high-risk patients and timely intervention to reduce the risk of adverse maternal and infant outcomes.
