摘要
目的 探索影响脑卒中患者跌倒风险的相关因素,预测跌倒风险等级.方法 回顾性分析2022年7月至2024年1月在华东医院就诊的脑卒中患者64例,记录患者就诊时的人口学资料性别、年龄、身高、体质量、卒中类型、病程,功能指标世界卫生组织残疾评定量表2.0(WHODAS 2.0)、Fugl-Meyer评定量表(FMA)、功能性前伸测试(FRT)、多方向伸展测试(MDRT)、蒙特利尔认知评估量表(MoCA),行走指标计时起立行走试验等.以脑卒中患者跌倒风险等级为因变量,先采用单因素分析,再采用判别分析对脑卒中患者跌倒风险因素进行观察.结果 纳入患者平均年龄约66岁,男性多于女性,脑梗死患者多于脑出血患者,平均病程(4.50±6.02)个月,跌倒风险等级轻度、中度、重度的脑卒中患者分别为19例、26例、19例.单因素分析显示,不同跌倒风险等级脑卒中患者间WHODAS 2.0、FMA、FMA-上肢部分(FMA-UE)、FMA-下肢部分(FMA-LE)、FRT、MDRT-向前(MDRT-F)、MDRT-向右(MDRT-R)、MoCA评分有显著性差异(F>2.277,P<0.05).判别分析显示,不同跌倒风险等级患者的功能参数方程不同,采用回顾法验证Fisher判别函数、Bayes判别函数正确率分别为75%、78.1%,误判率分别为25%、21.9%.结论 活动参与能力、上下肢运动功能、向前向右方向的稳定极限及认知功能影响脑卒中患者跌倒风险等级,通过功能指标建立判别函数可对跌倒风险等级进行预测.
Abstract
Objective To explore the factors affecting the fall risks in stroke patients,and predict the level of fall risk.Methods A retrospective analysis was conducted.A total of 64 stroke patients in Huadong Hospital from July,2022 to January,2024 were enrolled.The patient's demographic data,functional indicators and walking indicator,includ-ing gender,age,height,weight,stroke type,course of disease,WHO Disability Assessment Schedule 2.0(WHO-DAS 2.0),simplified Fugl-Meyer Assessment(FMA),Functional Reaching Test(FRT),Multi-Directional Reach Test(MDRT),Montreal Cognitive Assessment(MoCA)and Timed Up and Go Test were recorded.Using the risk level of falls in stroke patients as the dependent variable,first,a univariate analysis was conducted,and then dis-criminant analysis was followed to observe the risk factors for falls in stroke patients.Results All the included stroke patients had an average age of approximately 66 years old,more males than females,and more cerebral infarction patients than cerebral hemorrhage patients.The average course of the disease was(4.50±6.02)months.There were 19,26 and 19 stroke patients with mild,moderate and severe fall risk levels,respective-ly.One-way analysis of variance showed that the scores of WHODAS 2.0,FMA,FMA-Upper Extremities(FMA-UE),FMA-Lower Extremities(FMA-LE),FRT,MDRT-Forward(MDRT-F),MDRT-Right(MDRT-R)and Mo-CA were significantly differenct among stroke patients with different fall risk levels(F>2.277,P<0.05).Dis-criminant analysis showed that patients with different fall risk levels had different functional parameter equa-tions,using the retrospective method,the accuracy rates of Fisher discriminant function and Bayes discriminant function were 75%and 78.1%,and the misjudgment rates were 25%and 21.9%,respectively.Conclusion Activity and participation ability,upper and lower extremity motor function,stability limits of the forward and right direction and cognitive function are related factors to the risk level of falls.It could predicte the risk lev-el of falls by establishing a discriminant function through functional indicators.
基金项目
上海市科委项目(21MC1930200)
上海市科委项目(22Y31900200)
上海市卫健委卫生行业临床研究专项(20194Y0463)
国家科技期刊平台
NSTL
万方数据