实用临床医药杂志2025，Vol.29Issue(12)：55-61,7.DOI:10.7619/jcmp.20250457
基于LASSO-Logistic回归分析构建住院老年阿尔茨海默病患者临床结局的列线图模型
Establishment of a Nomogram model for clinical outcomes in hospitalized elderly patients with Alzheimer's disease based on LASSO-Logistic regression analysis
摘要
Abstract
Objective To screen the influencing factors associated with adverse clinical out-comes in hospitalized elderly patients with Alzheimer's disease(AD)using LASSO-Logistic regression analysis and to construct a nomogram prediction model.Methods A retrospective selection of 214 hospitalized elderly patients with AD who visited the Department of Geriatric Medicine in the hospital from February 2021 to March 2023 was conducted,and clinical data of all patients were collected.Patients were divided into adverse events group(n=53)and non-adverse events group(n=161)based on the occurrence of adverse clinical outcomes.After variable screening using LASSO regres-sion,multivariate Logistic regression analysis was performed to identify independent factors influen-cing adverse clinical outcomes in hospitalized elderly patients with AD.A Nomogram model for pre-dicting adverse clinical outcomes in these patients was established based on the results of multivariate analysis.The predictive performance,calibration,and clinical utility of the Nomogram model were evaluated using the concordance index,calibration curve,and decision curve analysis(DCA).The diagnostic performance of the Nomogram model for adverse clinical outcomes in hospitalized elderly patients with AD was assessed using the receiver operating characteristic(ROC)curve and the area under the curve(AUC).Results LASSO-Logistic regression analysis revealed that the Mini-Men-tal State Examination(MMSE)score was an independent protective factor against adverse clinical outcomes in hospitalized elderly patients with AD(P＜0.05),while the Charlson Comorbidity In-dex(CCI score),creatinine,urea,and fasting blood glucose(FBG)levels were all independent risk factors for adverse clinical outcomes in these patients(P＜0.05).The Nomogram model con-structed based on the influencing factors screened by LASSO-Logistic regression analysis showed a concordance index of 0.994(95％CI,0.958 to 1.000)for predicting adverse clinical outcomes in hospitalized elderly patients with AD.The Hosmer-Lemeshow test results indicated x2=1.909,P=0.984,suggesting good model fit.The DCA result demonstrated that the model had favorable threshold probabilities and net clinical benefits.Conclusion The Nomogram model for predicting clinical outcomes in elderly inpatients with AD constructed based on LASSO-Logistic regression anal-ysis exhibits high predictive value,and can be used to forecast the occurrence of adverse clinical outcomes in these patients.关键词
LASSO-Logistic回归分析/老年患者/阿尔茨海默病/临床结局/列线图/预测模型/简易智力状态检查量表/空腹血糖Key words
LASSO-Logistic regression analysis/elderly patients/Alzheimer's disease/clini-cal outcomes/Nomogram/prediction model/the Mini-Mental State Examination/fasting blood glucose分类
医药卫生引用本文复制引用
单燕,徐亚萍,诸葛恒艳,陆秋英..基于LASSO-Logistic回归分析构建住院老年阿尔茨海默病患者临床结局的列线图模型[J].实用临床医药杂志,2025,29(12):55-61,7.基金项目
江苏省优势学科建设工程项目(YSHL2101-871) （YSHL2101-871）
