@article{KUANG2025, 
author = {Na KUANG and Wenjiao HE and Xi XIONG and Zhengqiong CHEN},
title = {Predictive value and risk factors of embryo implantation site for placenta previa},
year = {2025},
journal = {Journal of Army Medical University},
volume = {47},
number = {14},
pages = {1670-1675},
keywords = {embryo implantation, placenta previa, risk factors, prediction model},
url = {https://www.sciopen.com/article/10.16016/j.2097-0927.202504006},
doi = {10.16016/j.2097-0927.202504006},
abstract = {ObjectiveTo develop a prediction model for placenta previa in early pregnancy by analyzing embryo implantation sites and related clinical factors, in order to provide an objective basis for early risk identification.MethodsA retrospective cohort study was conducted on 232 singleton pregnant women delivering in our hospital between September 2020 and March 2024. According to the final pre-delivery ultrasound findings, they were divided into placenta previa group (n=78) and a non-placenta previa group (n=154). Their ultrasound parameters [distance from lower gestational sac margin to cervical os, implantation site (lower/middle-upper uterine segment), and implantation position (anterior/posterior wall)], and clinical data [age, gravidity (categorized as <2 or ≥2 pregnancies), parity (<2 or ≥2 deliveries), and history of intrauterine procedures were collected through electronic medical records. Univariate analysis was used to screen potential predictors (P<0.1), and multivariate logistic regression analysis was employed to identify the predictors (P<0.05) for placenta previa. Then a nomogram prediction model was constructed, which was internally validated with Bootstrap (1000 bootstrap resamples) and assessed for discrimination with area under the receiver operating characteristic curve (AUC) and for calibration with Hosmer-Lemeshow goodness-of-fit test.ResultsThe placenta previa group showed significantly advanced age (≥35 years), lower education level (≤high school), multigravidity (≥2 pregnancies), multiparity (≥2 deliveries), more intrauterine procedures, distance of gestational sac-to-cervical os <5.5 mm, and larger proportion of lower uterine segment implantation than the non-placenta previa group (all P<0.1). But there were no statistical differences between the 2 groups in proportion of posterior wall implantation, history of cesarean section or assisted reproductive technology (ART). Multivariate logistic regression analysis confirmed lower uterine segment implantation (OR=40.40, 95%CI: 14.68~136.19, P<0.001), posterior wall implantation (OR=2.73, 95%CI:1.27~6.28, P=0.013), and intrauterine procedures (OR=3.48, 95%CI: 1.65~7.70, P=0.001) as independent risk factors. The model based on these predictors demonstrated excellent discrimination (AUC value=0.84, 95%CI: 0.79~0.90) and calibration (Hosmer-Lemeshow test Chi-square=3.455, P=0.750).ConclusionLower uterine segment/posterior wall implantation and intrauterine procedures are independent risk factors for placenta previa. Our nomogram model based on these factors shows good predictive efficiency, and can provide reference for early recognition of pregnant woman with high-risk placenta previa.}
}