脑卒中患者并发肌少症的影响因素及其风险预测列线图模型构建  

Influencing Factors of Sarcopenia in Patients with Stroke and Construction of Nomogram Model for Predicting Its Risk

作　　者：程姐 计海霞[2] 李佩芳[1] 罗董杭 尤敏[1] 戚媛媛 王婷[1] 吴杰[1] CHENG Jie;JI Haixia;LI Peifang;LUO Donghang;YOU Min;QI Yuanyuan;WANG Ting;WU Jie(Department of Encephalopathy,Acupuncture Hospital of Anhui University of Traditional Chinese Medicine,Hefei 230061,China;Department of Neurology,the First Affiliated Hospital of Anhui Medical University,Hefei 230088,China;School of Nursing,Anhui University of Chinese Medicine,Hefei 230012,China)

机构地区：[1]安徽中医药大学第二附属医院脑病科,安徽省合肥市230061 [2]安徽医科大学第一附属医院神经内科,安徽省合肥市230088 [3]安徽中医药大学护理学院,安徽省合肥市230012

出　　处：《实用心脑肺血管病杂志》2024年第11期31-36,共6页Practical Journal of Cardiac Cerebral Pneumal and Vascular Disease

基　　金：安徽省临床医学研究转化专项(202304295107020113)。

摘　　要：目的探讨脑卒中患者并发肌少症的影响因素,并构建其风险预测列线图模型。方法采用随机抽样法选取2023年10—12月就诊于安徽中医药大学第二附属医院的脑卒中患者268例为研究对象,采用随机数字表法按照7∶3的比例将患者分为训练集(n=187)与测试集(n=81)。收集患者的临床资料,根据肌少症发生情况将训练集患者分为肌少症组和非肌少症组。采用多因素Logistic回归分析探讨脑卒中患者并发肌少症的影响因素,并构建脑卒中患者并发肌少症的风险预测列线图模型;采用Hosmer-Lemeshow拟合优度检验评价该列线图模型在训练集与测试集中的拟合程度;采用ROC曲线分析该列线图模型对训练集与测试集脑卒中患者并发肌少症的预测价值;绘制决策曲线以评价该列线图模型在训练集与测试集中的临床有效性。结果非肌少症组74例,肌少症组113例。非肌少症组与肌少症组病情严重程度、日常生活活动能力、脑卒中发病至就诊时间、卧床时间、吞咽障碍发生率、肢体功能障碍发生率、白细胞计数、C反应蛋白比较,差异有统计学意义(P<0.05)。多因素Logistic回归分析结果显示,病情严重程度、C反应蛋白为脑卒中患者并发肌少症的独立影响因素(P<0.05)。基于上述因素构建脑卒中患者并发肌少症的风险预测列线图模型。Hosmer-Lemeshow拟合优度检验结果显示,在训练集和测试集中,该列线图模型的拟合程度较好(P<0.05)。ROC曲线分析结果显示,该列线图模型预测训练集、测试集脑卒中患者并发肌少症的AUC分别为0.835〔95%CI(0.775~0.895)〕、0.870〔95%CI(0.780~0.950)〕。决策曲线分析结果显示,在训练集中,当阈值概率为0.15~0.95时,该列线图模型的临床净获益率>0;在测试集中,当阈值概率为0.34~0.98时,该列线图模型的临床净获益率>0。结论病情严重程度、C反应蛋白为脑卒中患者并发肌少症的独立影响因Objective To investigate the influencing factors of sarcopenia in patients with stroke,and construct its risk prediction nomogram model.Methods A total of 268 stroke patients admitted to Acupuncture Hospital of Anhui University of Traditional Chinese Medicine from OctobeRto DecembeR2023 were randomly selected as the research subjects.Patients were divided into training set(n=187)and testing set(n=81)in a ratio of 7∶3 by the random numbeRtable method.Clinical data of the patients were collected,and patients in training set were divided into the sarcopenia group and the non-sarcopenia group according to the presence of sarcopenia.Multivariate Logistic regression analysis was used to explore the influencing factors for sarcopenia in patients with stroke and the risk prediction nomogram model of sarcopenia in patients with stroke was constructed.The Hosmer-Lemeshow goodness of fit test was used to evaluate the fitting of the nomogram model in the training set and the testing set.The ROC curve was used to analyze the predictive value of the model foRsarcopenia in patients with stroke in the training set and the testing set.Decision curve was drawn to assess the clinical utility of the nomogram model in the training set and the testing set.Results There were 74 cases in the non-sarcopenia group and 113 cases in the sarcopenia group.There were significant differences in the severity of disease,activity of daily living,time of onset of stroke,bed rest time,incidence of dysphagia,incidence of limb dysfunction,leukocyte count,and C-reactive protein between the non-sarcopenia group and the sarcopenia group(P<0.05).Multivariate Logistic regression analysis showed that the severity of disease and C-reactive protein were independent influencing factors foRsarcopenia in patients with stroke(P<0.05).The risk prediction nomogram model of sarcopenia in patients with stroke was constructed according to these factors.The Hosmer-Lemeshow goodness of fit test showed that the nomogram model fited well in the training set and the test

关 键 词：脑卒中 肌减少症 影响因素分析 列线图 

分 类 号：R743.3[医药卫生—神经病学与精神病学] R746.4[医药卫生—临床医学]