滨州医学院学报2026，Vol.49Issue(2)：200-204,5.DOI:10.19739/j.cnki.issn1001-9510.2026.02.016
高脂血症性急性胰腺炎患者疾病严重程度预测模型构建
Construction of a prediction model for disease severity in patients with hyperlipidemic acute pancreatitis
摘要
Abstract
Objective To construct a disease severity predictive model for patients with hyperlipidemia acute pancreatitis by using machine learning methods.Methods A retrospective study was conducted on 320 patients with hyperlipidemic acute pan-creatitis in a tertiary hospital in Binzhou City,Shandong Province,and the clinical examination indicators and the Atlanta severity score of pancreatitis were used as variables to construct the machine learning predictive model.Results The Logistic regression showed that body mass index(BMI),triglyceride(TG),glucose(Glu),amylase(AMY)and white blood cell(WBC)were in-dependent influencing factors for the severity of acute pancreatitis with hyperlipidemia,and serum calcium level and high density lipoprotein cholesterol(HDL-C)level were protective factors for the severity of acute pancreatitis with hyperlipidemia.The logis-tic regression model's receiver operating characteristic(ROC)curve area under the curve(AUC)value for the test set was 0.949,the Adaboost model AUC value was 0.969,the gradient boosting decision tree(GBDT)model AUC value was 0.938,and the random forest(RF)model AUC value was 0.951.Among the severity prediction models for hyperlipidemic acute pancre-atitis,the logistic regression test set calibration curve was closest to the ideal calibration curve in the 0-0.7 probability range.Conclusion The logistic multivariate regression model constructed with machine learning demonstrates superior overall predictive performance compared to other machine learning models in predicting the severity of patients with hyperlipidemic acute pancreatitis.关键词
猪源纤维蛋白粘合剂/胸腔镜肺癌根治手术/胸腔引流量/胸腔引流管带管时间/术后住院时间Key words
hyperlipidemia acute pancreatitis/patient/severity/predictive model分类
医药卫生引用本文复制引用
潘永正,崔景晶,李丽,陈嘉豪,肖奕君,王庆华..高脂血症性急性胰腺炎患者疾病严重程度预测模型构建[J].滨州医学院学报,2026,49(2):200-204,5.基金项目
山东省自然科学基金项目(ZR2022MH117) （ZR2022MH117）
国家级大学生创新创业训练计划(202410440004) （202410440004）
山东省大学生创新创业训练计划(S202410440089) （S202410440089）
