摘要
目的应用CART决策树和logistic回归构建住院肝硬化患者发生衰弱风险预测模型,比较2种模型预测效果。方法采用便利抽样法,选取2023年3-10月某三级甲等医院确诊并收治的317例肝硬化患者,运用CART决策树和logistic回归构建住院肝硬化患者发生衰弱风险预测模型,内部验证采用Bootstrap重采样1000次的方法,采用准确度、灵敏度、特异度、阳性预测值、阴性预测值和受试者工作特征(ROC)曲线下面积(AUC)对2种模型的性能进行比较。结果CART决策树与logistic回归准确度为86.3%和89.1%、灵敏度为76.5%和92.5%、特异度为91.8%和82.8%、阳性预测值为84.8%和91.6%、阴性预测值为86.8%和83.8%、AUC为0.876和0.965。结论logistic模型对住院肝硬化患者发生衰弱风险的预测性能优于CART决策树模型,可为衰弱的早期筛查和预防提供参考。
Objective To construct fateful risk prediction models for inpatients with cirrhosis by CART decision tree and logistic regression respectively,and compare the prediction effects of 2 models.Methods A total of 317 patients with cirrhosis who met the admission criteria in a tertiary A hospital from March to October 2023 were selected by convenience sampling method,and CART decision tree and logistic regression were used to construct a frailty risk prediction model for inpatients with cirrhosis.In internal verification,the method of Bootstrap resampling 1000 times was used to compare the performance of 2 models by using accuracy,sensitivity,specificity,positive predictive value,negative predictive value,and area under the curve(AUC)of receiver operating characteristic(ROC).Result The accuracy of CART decision tree and logistic regression were 86.3%and 89.1%,the sensitivity was 76.5%and 92.5%,the specificity was 91.8%and 82.8%,the positive predictive value was 84.8%and 91.6%,the negative predictive value was 86.8%and 83.8%,and the AUC was 0.876 and 0.965.Conclusion logistic model is better than CART decision tree model in predicting frailty risk in inpatients with cirrhosis,which can provide reference for early screening and prevention of frailty.
作者
陆雅维
张会
许静
仲蕾
项晓婷
LU Yawei;ZHANG Hui;XU Jing;ZHONG Lei;XIANG Xiaoting(School of Nursing,Anhui Medical University,Hefei 230601,Anhui,China;The First Affiliated Hospital of Anhui Medical University,Hefei 230032,Anhui,China;Anhui Provincial Public Health Clinical Center,Hefei 230032,Anhui,China)
出处
《护士进修杂志》
2024年第24期2577-2583,共7页
Journal of Nurses Training
基金
国家重点研发计划主动健康和老龄化科技应对项目(编号:2020YFC2006500)。
关键词
回归分析
决策树
肝硬化疾病
衰弱
预测模型
regression analysis
decision tree
liver cirrhosis disease
enervation
prediction model
作者简介
陆雅维(1997-),女,安徽滁州,硕士,护师,研究方向:内科护理;通信作者:张会,Email:zhanghui310@126.com。
