摘要
目的分析子痫前期患者发生不良妊娠结局的危险因素,构建并验证预测模型。方法本研究采用回顾性分析,纳入2021年1月至2024年3月在郑州大学第三附属医院确诊为子痫前期并分娩的患者资料。根据是否发生不良妊娠结局,将患者分为不良组和非不良组。经筛选后,使用单因素和多因素logistic回归分析患者临床数据;通过R语言4.2.1对筛选出的独立危险因素绘制列线图,建立预测模型,并计算受试者工作特征曲线。通过曲线下面积(AUC)和Hosmer-Lemeshow(H-L)检验评估模型的区分度、校准度及临床效用,并采用Bootstrap自抽样法和十折交叉验证对预测模型进行内部验证。结果本研究共纳入472例子痫前期患者进行建模,其中不良组患者428例,非不良组患者44例。多因素logistic回归分析显示,子痫前期患者发生不良妊娠结局的独立危险因素(P<0.05)包括发病孕周≤34周、孕期最高舒张压≥110 mmHg、脐血流异常、尿液分析尿蛋白阳性、尿酸>369μmol/L、乳酸脱氢酶>246 U/L。基于这些独立危险因素构建的临床预测模型,AUC值为0.942(95%CI:0.909~0.975),最佳截断值为0.836,对应特异性为84.1%,敏感性为92.1%。H-L拟合优度检验结果显示χ^(2)=4.969,P=0.761,表明模型校准良好。决策曲线分析显示模型在临床决策中可获得较高净获益。模型验证显示该模型具备良好的泛化能力和实际应用价值。结论本研究基于临床数据筛选出6个独立危险因素,用于构建子痫前期患者不良妊娠结局预测模型,模型预测性能表现较优(AUC=0.942),校准度P=0.761,表明预测模型临床应用潜力较大。
Objective To analyze the risk factors for adverse pregnancy outcomes in patients with preeclampsia(PE)and to develop and validate a predictive model.Methods This retrospective study included data from patients diagnosed with preeclampsia(PE)who delivered at the Third Affiliated Hospital of Zhengzhou University-Henan Provincial Maternal and Child Health Hospital from January 2021 to March 2024.Patients were categorized into adverse and non-adverse outcome groups based on the occurrence of adverse pregnancy outcomes.After screening,univariate and multivariate logistic regression analyses were used to evaluate clinical data.Independent risk factors identified were then utilized to develop a nomogram and construct a predictive model via R software 4.2.1.The receiver operating characteristic curve was calculated,and the model's discrimination,calibration,and clinical utility were assessed through the area under the curve(AUC)and Hosmer-Lemeshow(H-L)test.Internal validation of the predictive model was performed using the bootstrap resampling method and ten-fold cross-validation.Results A total of 472 PE patients were included in this study to construct the model,comprising 428 patients with adverse pregnancy outcomes and 44 without.Multivariate logistic regression analysis identified independent risk factors for adverse pregnancy outcomes in PE patients(P<0.05),including gestational age at onset≤34 weeks,peak diastolic blood pressure during pregnancy≥110 mmHg,abnormal umbilical artery blood flow,positive urine protein analysis,serum uric acid>369μmol/L,and lactate dehydrogenase>246 U/L.Based on these independent risk factors,a clinical predictive model was constructed,yielding an AUC of 0.942(95%CI:0.909~0.975).The optimal cutoff value was 0.836,with a specificity of 84.1%and sensitivity of 92.1%.The H-L goodness-of-fit test indicated good calibration of the model(χ^(2)=4.969,P=0.761).Decision curve analysis shows that the model can achieve higher net benefits in clinical decision-making.The model validation shows that the model has good generalization ability and practical application value.Conclusion Based on clinical data,this study identified 6 independent risk factors to construct a predictive model for adverse pregnancy outcomes in preeclampsia patients.The model demonstrated strong predictive performance,with an AUC of 0.942 and good calibration(P=0.761),indicating substantial potential for clinical application.
作者
闫玉
张建新
李宏伟
卫元
丁燕子
付梦宇
张雪薇
阚玫麟
袁恩武
Yan Yu;Zhang Jianxin;Li Hongwei;Wei Yuan;Ding Yanzi;Fu Mengyu;Zhang Xuewei;Kan Meilin;Yuan Enwu(Department of Laboratory Medicine,the Third Affiliated Hospital of Zhengzhou University,Zhengzhou Henan 450052,China;The Third Clinical Medical College of Zhengzhou University,Zhengzhou Henan 450052,China)
出处
《中华临床实验室管理电子杂志》
2025年第1期17-26,共10页
Chinese Journal of Clinical Laboratory Management(Electronic Edition)
基金
河南省医学科技攻关计划省部共建重点项目(SBGJ202302081)。
关键词
子痫前期
临床资料
妊娠结局
风险评估
危险因素
预测模型
preeclampsia
clinical data
pregnancy outcomes
risk assessment
risk factors
predictive model
