现代妇产科进展2026，Vol.35Issue(3)：173-181,9.DOI:10.13283/j.cnki.xdfckjz.2026.03.030
基于Cox比例风险模型的子痫前期母儿结局分层及预后模型的建立
Development of a stratification and prognostic model for maternal and neonatal out-comes in preeclampsia based on Cox proportional hazards modeling
摘要
Abstract
Objective:To investigate the independent risk factors for maternal and neo-natal adverse outcomes in preeclampsia,and to construct stratified prediction models for mater-nal and neonatal adverse outcomes based on the Cox proportional hazards model,so as to pro-vide references for the timing of clinical preeclampsia delivery.Methods:A retrospective study was conducted using clinical data from 280 patients with preeclampsia between 20 and 37 weeks of gestation at the First Affiliated Hospital of Guangxi Medical University.Prediction models for maternal and neonatal adverse outcomes were developed separately.Patients were categorized into groups with and without adverse outcomes.Independent risk factors were screened using LASSO(Least Absolute Shrinkage and Selection Operator)regression,and prediction models were constructed based on Cox proportional hazards regression.The predictive performance was evaluated by the area under the curve(AUC)of the receiver operating characteristic(ROC)curve.Calibration was assessed using calibration curves.Internal validation was performed using the bootstrap resampling method,and external validation was conducted on a dataset of 150 ca-ses from another hospital.Results:The maternal adverse outcome prediction model incorporated platelet count,creatinine,alanine aminotransferase,peak systolic blood pressure prior to admis-sion,24-hour urinary protein quantification,and stratified gestational age at admission.The mod-el's C-index was 0.701(95%CI:0.63～0.77).The areas under the curve(AUC)for predic-ting outcomes at 2,7,and 14 days of expectant management were 0.791,0.755,and 0.80,re-spectively.The neonatal adverse outcome prediction model incorporated stratified gestational age at delivery,gestational days at admission,fetal distress,mean arterial pressure at admission,and creatinine.This model achieved a C-index of 0.85(95%CI:0.82～0.87),with AUCs of 0.914,0.95,and 0.963 for predicting outcomes at 2,7,and 14 days of expectant management,respectively.Both internal and external validation indicated good predictive performance for the two models.Conclusion:Platelet count,creatinine,alanine aminotransferase,peak systolic blood pressure prior to admission,24-hour urinary protein quantification,and stratified gestational age at admission are independent risk factors for maternal adverse outcomes in preeclampsia.Strati-fied gestational age at delivery,gestational days at admission,fetal distress,mean arterial pres-sure at admission,and creatinine are risk factors for neonatal adverse outcomes.The constructed stratified prediction models for maternal and neonatal adverse outcomes in PE can effectively predict the risk of adverse outcomes,guide clinical decision-making regarding the timing of de-livery,and thereby reduce the risk of adverse outcomes to improve perinatal outcomes.关键词
COX比例风险模型/子痫前期/母儿结局/分层模型/预测模型Key words
Cox proportional hazards regression model/Pre-eclampsia/Maternal and neonatal outcomes/Hierarchical model/Prediction model分类
医药卫生引用本文复制引用
何桂宁,龙玉,吴敏,曾雅畅..基于Cox比例风险模型的子痫前期母儿结局分层及预后模型的建立[J].现代妇产科进展,2026,35(3):173-181,9.基金项目
广西适宜技术应用项目(No:S2022080) （No:S2022080）
广西医科大学第一附属医院临床研究攀登计划青年科技启明星项目(No:YYZS2023016) （No:YYZS2023016）
国家自然科学基金地区科学基金项目(No:82560310) （No:82560310）
广西自然科学基金(No:2024GXNSFAA010368) （No:2024GXNSFAA010368）
