摘要
目的 分析社区和住院老年慢病患者肌少症的影响因素,建立肌少症风险预测模型.方法 于2020年3月至2022年3月募集居住于江苏省南京市某社区251例老年人、以及江苏省人民医院老年医学科住院患者152例,共计403例慢病患者作为研究对象.采用一般资料调查、血清标本收集、简易营养评估量表、简易精神状态检查量表、老年人抑郁量表进行评估.采用二元Logistic回归分析确定影响因素,构建肌少症风险预测模型,并通过列线图展示,使用受试者工作特征(ROC)曲线及曲线下面积(AUC)评价模型的区分度.结果 社区慢病患者肌少症患病率为4.0％(10/251),住院慢病患者肌少症患病率为36.2％(55/152).二分类Logistic回归分析结果显示,住院(OR=14.391、95％CI:6.284～32.955、P＜0.001)、男性(OR=3.321、95％CI:1.587～6.950、P=0.001)、较低的低密度脂蛋白胆固醇(OR=2.542、95％CI:1.160～5.572、P=0.020)、认知功能障碍(OR=2.654、95％CI:1.269～5.550、P=0.010)、用药种类≥4 种(OR=2.328、95％CJ:1.952～5.689、P=0.044)是发生肌少症的独立影响因素.基于以上危险因素绘制了肌少症风险预测模型的列线图,预测模型的AUC为0.860(95％CI:0.815～0.912),灵敏度为0.831,特异性为0.760.结论 老年慢病患者肌少症患病率较高,基于是否住院、性别、低密度脂蛋白胆固醇水平、认知功能、用药种类构建的风险预测模型对于肌少症的预测具有一定的价值,为肌少症的早期筛查和干预提供依据.
Abstract
Objective To analyze the factors influencing sarcopenia in older patients with chronic diseases,both in community settings and hospitals,and to develop a risk prediction model for sarcopenia.Methods We recruited a total of 403 older adults with chronic diseases,consisting of 251 individuals from a community in Nanjing,Jiangsu Province,and 152 hospitalized patients from the Department of Geriatrics at Jiangsu Province Hospital.Assessments were conducted using a general information questionnaire,serum sample collection,the mini nutritional assessment-short form(MNA-SF),the mini-mental state examination(MMSE),and the geriatric depression scale(GDS).Binary Logistic regression analysis was employed to identify influencing factors and to construct a risk prediction model for sarcopenia,which was illustrated using a nomogram.The model's discrimination was evaluated using the receiver operating characteristic(ROC)curve and the area under the curve(AUC).Results The prevalence of sarcopenia among community-dwelling older adults with chronic conditions was found to be 4.0％(10/251).In contrast,the prevalence in hospitalized older adults with chronic conditions was significantly higher at 36.2％(55/152).Binary Logistic regression analysis identified several independent risk factors for sarcopenia,including hospitalization(OR=14.391、95％CI:6.284-32.955、P＜0.001),male gender(OR=3.321、95％CI:1.587-6.950、P=0.001),lower low-density lipoprotein cholesterol(LDL-C)levels(OR=2.542、95％CI:1.160-5.572、P=0.020),cognitive impairment(OR=2.654、95％CI:1.269-5.550、P=0.010),and the use of four or more types of medication(OR=2.328、95％CI:1.952-5.689、P=0.044).Based on these risk factors,a nomogram was developed as a predictive model for assessing sarcopenia risk.The AUC for this prediction model was 0.860(95％CI:0.815-0.912),indicating a sensitivity of 0.831 and a specificity of 0.760.Conclusions The incidence of sarcopenia is notably high among older patients with chronic diseases.A risk prediction model that incorporates factors such as hospitalization history,gender,LDL-C levels,cognitive function,and types of medication demonstrates significant potential for predicting sarcopenia.This model serves as a valuable foundation for the early screening and intervention of sarcopenia.
维普
万方数据