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预测老年社区内的跌倒情况:比较姿势摆动、反应时间、伯格平衡量表以及特定活动平衡信心(ABC)量表在跌倒者与非跌倒者之间的差异。

Predicting falls within the elderly community: comparison of postural sway, reaction time, the Berg balance scale and the Activities-specific Balance Confidence (ABC) scale for comparing fallers and non-fallers.

作者信息

Lajoie Y, Gallagher S P

机构信息

School of Human Kinetics, University of Ottawa, 125 University St, Ottawa, Ont., Canada K1N6N5.

出版信息

Arch Gerontol Geriatr. 2004 Jan-Feb;38(1):11-26. doi: 10.1016/s0167-4943(03)00082-7.

Abstract

Simple reaction time, the Berg balance scale, the Activities-specific Balance Confidence (ABC) scale and postural sway were studied in order to determine cut-off scores as well as develop a model used in the prevention of fallers within the elderly community. One hundred and twenty-five subjects, 45 fallers and 80 non-fallers were evaluated throughout the study and results indicated that non-fallers have significantly faster reaction times, have higher scores on the Berg balance scale and the ABC scale as well as sway at slower frequencies when compared to fallers. Furthermore, all risk factors were subsequently entered into a logistic regression analysis and results showed that reaction time, the total Berg score and the total ABC score contributed significantly to the prediction of falls with 89% sensitivity and 96% specificity. A second logistic regression was carried out with the same previous variables as well as all questions of the Berg and ABC scales. Results from the logistic analysis revealed that three variables were associated with fall status with 91% sensitivity and 97% specificity. Results from the following study would seem rather valuable as an assessment tool for health care professionals in the identification and monitoring of potential fallers within nursing homes and throughout the community.

摘要

为了确定临界值并开发一种用于预防老年社区跌倒者的模型,对简单反应时间、伯格平衡量表、特定活动平衡信心(ABC)量表和姿势摆动进行了研究。在整个研究过程中,对125名受试者进行了评估,其中45名跌倒者和80名非跌倒者,结果表明,与跌倒者相比,非跌倒者的反应时间明显更快,在伯格平衡量表和ABC量表上得分更高,并且摆动频率更低。此外,所有风险因素随后都被纳入逻辑回归分析,结果显示,反应时间、伯格总分和ABC总分对跌倒预测有显著贡献,敏感性为89%,特异性为96%。进行了第二次逻辑回归,使用了与之前相同的变量以及伯格量表和ABC量表的所有问题。逻辑分析结果显示,三个变量与跌倒状态相关,敏感性为91%,特异性为97%。以下研究结果对于医疗保健专业人员在养老院和整个社区识别和监测潜在跌倒者方面作为评估工具似乎相当有价值。

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