老年住院患者衰弱与肌少症以及主观社会隔离的相关性分析
Relationship of frailty with sarcopenia and subjective social isolation among elderly inpatients
杨丹 1迟晨汝 1陈梦奇 1周志庆 1刘欢 2王翠珍3
作者信息
- 1. 皖南医学院研究生学院,安徽 芜湖 241002
- 2. 皖南医学院弋矶山医院血液净化中心
- 3. 皖南医学院弋矶山医院肾内科
- 折叠
摘要
目的:了解老年住院患者衰弱现状,并分析其影响因素,以及老年住院患者衰弱与肌少症以及主观社会隔离之间的关系.方法:选取芜湖市某三甲医院518例老年住院患者为研究对象,采用一般资料调查表、Frail量表、SARC-F量表、主观社会隔离量表进行调查,采用Logistic回归分析影响老年住院患者衰弱的因素.结果:518名老年住院患者衰弱发生率为52.5%(272/518),Logistic回归分析显示,近1年内发生跌倒(OR=3.458,95%CI:1.454～8.229)、肌少症(OR=5.622,95%CI:2.494～12.677)、主观社会隔离(OR=181.165,95%CI:57.307～572.721)、多重用药(OR=2.409,95%CI:1.336～4.346)、年龄80～89岁(OR=8.982,95%CI:0.640～2.357)是老年住院患者衰弱的危险因素(P＜0.05).结论:老年住院患者衰弱发生率高,医护人员应对老年住院患者的衰弱状况评估予以重视,并及时采取具有针对性的干预措施减缓或预防老年住院患者衰弱的进程.
Abstract
Objective:To understand the status of frailty among elderly inpatients,analyze its influencing factors,and explore the relationship of frailty with sarcopenia,and subjective social isolation in elderly inpatients.Methods:A total of 518 elderly inpatients from a tertiary hospital in Wuhu were selected as the research subjects.General information questionnaire,Frail Scale,SARC-F Scale,and Subjective Social Isolation Scale were used for investigation.Logistic regression analysis was used to analyze the influencing factors of frailty among elderly inpatients.Results:The incidence of frailty in 518 elderly inpatients was 52.5%(272/518).Logistic regression analysis revealed that recent falls(OR=3.458,95%CI:1.454-8.229),sarcopenia(OR=5.622,95%CI:2.494-12.677),subjective social isolation(OR=181.165,95%CI:57.307-572.721),polypharmacy(OR=2.409,95%CI:1.336-4.346),and 80-89 years old(OR=8.982,95%CI:0.640-2.357)were risk factors for frailty in elderly inpatients(P＜0.05).Conclusions:The prevalence of frailty is high among elderly inpatients.Healthcare professionals should pay attention to the assessment of frailty in elderly inpatients,and promptly implement targeted interventions to slow down or prevent the progression of frailty.
关键词
老年住院患者/衰弱/肌少症/主观社会隔离Key words
elderly inpatients/frailty/sarcopenia/subjective social isolation引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据