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电子步道可预测痴呆养老院居民的短期跌倒风险。

An electronic walkway can predict short-term fall risk in nursing home residents with dementia.

机构信息

Section of Geriatric Medicine, Department of Internal Medicine, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.

出版信息

Gait Posture. 2012 May;36(1):95-101. doi: 10.1016/j.gaitpost.2012.01.012. Epub 2012 Mar 3.

Abstract

OBJECTIVES

To evaluate the feasibility and validity of gait parameters measured with an electronic walkway system in predicting short-term fall risk in nursing home residents with dementia.

METHODS

57 ambulatory nursing home residents with moderate to severe dementia participated in this prospective cohort study. We used the GAITRite(®) 732 walkway system to assess gait parameters. Measurements were collected every 3 months over a 15 month period, with each measurement being a baseline for the subsequent measurement. Falls were retrieved from incident reports. The predictive validity of the GAITRite(®) parameters was expressed in terms of sensitivity and specificity. Logistic regression analysis was conducted to examine the association between these parameters and falls occurrence within three months.

RESULTS

Reduced velocity (OR=1.22; 95% CI 1.04-1.43) and reduced mean stride length (OR=1.19; 95% CI 1.03-1.40) were the best significant gait predictors of a fall within three months, with a sensitivity of 82% for velocity and 86% for mean stride length, and a specificity of 52% for velocity and for mean stride length. The test procedure took an average of 5 min per participant. Some verbal persuasion or physical cueing was necessary in 142 measurements (80.7%).

CONCLUSION

Gait parameters as measured with an electronic walkway system can be used for the prediction of short-term fall risk in nursing home residents with moderate to severe dementia. However some form of persuasion might be needed to perform the task. To refine our findings, large prospective studies on the predictive validity of gait parameters in this type of population are needed.

摘要

目的

评估电子步道系统测量的步态参数预测患有中度至重度痴呆的养老院居民短期跌倒风险的可行性和有效性。

方法

57 名行动自如的养老院患有中度至重度痴呆的居民参与了这项前瞻性队列研究。我们使用 GAITRite ® 732 步道系统评估步态参数。在 15 个月的时间内,每 3 个月收集一次测量结果,每次测量都是后续测量的基线。从事件报告中检索跌倒事件。GAITRite ® 参数的预测有效性用灵敏度和特异性来表示。逻辑回归分析用于检查这些参数与三个月内跌倒发生之间的关联。

结果

速度降低(OR=1.22;95%CI 1.04-1.43)和平均步长缩短(OR=1.19;95%CI 1.03-1.40)是三个月内跌倒的最佳显著步态预测指标,速度的灵敏度为 82%,平均步长的灵敏度为 86%,速度的特异性为 52%,平均步长的特异性为 52%。每次测试程序平均每个参与者需要 5 分钟。在 142 次测量中(80.7%)需要一些口头劝说或身体提示。

结论

电子步道系统测量的步态参数可用于预测患有中度至重度痴呆的养老院居民的短期跌倒风险。但是,执行任务可能需要某种形式的劝说。为了完善我们的研究结果,需要在这种人群中进行步态参数预测有效性的大型前瞻性研究。

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