门诊步态分析中的“跌倒风险评分”:疗养院居民跌倒风险评估的新验证。

Eduard Witiko Unger, Tim Pohlemann, Marcel Orth, Mika F R Rollmann, Maximilian M Menger, Steven C Herath, Tina Histing, Benedikt J Braun
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引用次数: 0

摘要

老年家庭住户摔倒的情况很常见。个人预防性训练可以降低跌倒风险。为了发现训练的必要性,需要对个人跌倒风险进行系统评估。因此,本研究的目的是评估基于自由场地鞋垫测量的跌倒风险评分是否可以区分老年家庭居民的风险组和健康的年轻对照组。已公布的跌倒风险评分用于75岁以上的养老院居民和一名年轻人(7.5(AUC:0.95),敏感性为86.7%(特异性83.3%)。跌倒风险评分能够检测养老院老年居民和年轻健康对照之间以及跌倒者和非跌倒者之间的差异。它的主要概念验证是基于特殊步态实验室外的运动数据进行的,它可以简化老年疗养院居民跌倒风险的确定,现在可以用于进一步的前瞻性研究。
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"Fall Risk Scoring" in Outpatient Gait Analysis: Validation of a New Fall Risk Assessment for Nursing Home Residents.

Falls in senior home residents are common. Individual preventive training can lower the fall risk. To detect the need for training, a systematic assessment of the individual fall risk is needed. The aim of this study was thus to assess whether a fall risk score based on free field insole measurements can distinguish between an at-risk group of senior home residents and a healthy young control group. A published fall risk score was used in senior home residents over the age of 75 and a young (< 40 years) control group to determine the individual fall risk. In addition, the fall events over 12 months were assessed. Statistical analysis including ROC analysis was performed to determine the ability of the score to detect participants at heightened fall risk. In total, 18 nursing home residents and 9 young control participants were included. Of the nursing home residents, 15 had at least one fall, with a total of 37 falls recorded over 12 months. In the control group, no falls were recorded. The fall risk score was significantly different between nursing home residents and the control group (9.2 + 3.2 vs. 5.7 ± 2.2). Furthermore, the score significantly differentiated fallers from non-fallers (10.3 ± 1.8 vs. 5.2 ± 2.5), with a cut-off > 7.5 (AUC: 0.95) and a sensitivity of 86.7% (specificity 83.3%). The fall risk score is able to detect the difference between senior nursing home residents and young, healthy controls, as well as between fallers and non-fallers. Its main proof of concept is demonstrated, as based on movement data outside special gait labs, and it can simplify the risk of fall determination in geriatric nursing home residents and can now be used in further, prospective studies.

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