老年肌少症住院患者跌倒预警模型构建与验证  

作　　者：陈双 胡苗苗 张晓晓 

机构地区：[1]浙江省温州市中心医院,325000

出　　处：《浙江临床医学》2025年第3期436-438,共3页Zhejiang Clinical Medical Journal

基　　金：温州市公益性科技计划项目(Y20210648)。

摘　　要：目的探讨老年肌少症住院患者跌倒的危险因素,并构建预测其住院期间跌倒风险的预警模型。方法回顾性分析2019年1月至2024年6月730例老年肌少症住院患者的临床资料。根据患者住院期间是否发生跌倒分跌倒组(n=240)和未跌倒组(n=490)。采用单因素和多因素Logistic回归分析方法,确定影响患者跌倒的因素,构建预测住院期间跌倒可能的列线图模型,并与圣托马斯跌倒风险评估量表(STRATIFY)、Morse跌倒评估量表比较。结果年龄、突发意识障碍、精神障碍、视觉障碍、站立或行走不稳、缺乏陪护监管、束缚管道、多药联用及1年内跌倒史是老年肌少症住院患者跌倒的独立危险因素(P<0.05)。构建列线图模型曲线下面积(AUC)为0.832(95%CI:0.799~0.866),明显高于STRATIFY量表AUC 0.745(95%CI:0.704~0.787)与Morse量表AUC 0.746(95%CI:0.707~0.785);临床决策曲线图优于STRATIFY与Morse评分量表,表现出更高的临床净获益。结论年龄、突发意识障碍、精神障碍、视觉障碍、站立或行走不稳、缺乏陪护监管、束缚管道、多药联用及1年内跌倒史是老年肌少症住院患者跌倒的风险因素。依据以上因素构建的列线图模型可用于老年肌少症住院患者跌倒风险预警,且具有良好的校准度与区分度。Objective To explore the risk factors for falls in elderly patients with sarcopenia during hospitalization and to establish a predictive warning model for their fall risk during hospitalization.Methods Retrospective analysis of clinical data of 730 hospitalized elderly patients with sarcopenia from January 2019 to June 2024.According to whether the patient experienced a fall during hospitalization,they were divided into a fall group(n=240)and a non fall group(n=490).Using single factor and multiple factor logistic regression analysis methods,identified the factors that affect patient falls,constructed a column chart model to predict the possibility of falls during hospitalization,and its performance was compared with the St.Thomas'risk assessment tool in falling elderly inpatients(STRATIFY)and Morse fall risk assessment scales.Results Age,sudden onset of altered consciousness,mental disorders,visual impairment,instability in standing or walking,lack of supervision,use of restraining devices,polypharmacy,and a history of falls within the past year were identified as risk factors for falls in elderly patients with sarcopenia(P<0.05 for all).The area under the curve(AUC)of the nomogram model constructed from these variables was 0.832(95%CI:0.799~0.866),significantly higher than that of the STRATIFY scale(AUC:0.745,95%CI:0.704~0.787)and the Morse scale(AUC:0.746,95%CI:0.707~0.785).The decision curve analysis(DCA)of the nomogram also demonstrated significantly better performance than the STRATIFY and Morse scoring scales,showing higher clinical net benefits.Conclusion Age,sudden onset of consciousness disorders,mental disorders,visual impairments,unstable standing or walking,lack of accompanying supervision,restricted access,multiple drug use,and a history of falls within one year are risk factors for falls in hospitalized elderly patients with sarcopenia.The column chart model constructed based on the above factors can be used for fall risk warning in hospitalized elderly patients with sarcopenia,and has good calibra

关 键 词：老年 肌少症 住院跌倒 预测模型 列线图 

分 类 号：R473.5[医药卫生—护理学] R685[医药卫生—临床医学]