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基于老年人正常步态特征的步态滑脱致跌倒类型评估。

Gait Slip-Induced Fall-Type Assessment Based on Regular Gait Characteristics in Older Adults.

机构信息

Department of Physical Therapy, University of Illinois at Chicago, Chicago, IL,USA.

出版信息

J Appl Biomech. 2022 Apr 28;38(3):148-154. doi: 10.1123/jab.2021-0337. Print 2022 Jun 1.

Abstract

Older adults could experience split falls or feet-forward falls following an unexpected slip in gait due to different neuromuscular vulnerabilities, and different intervention strategies would be required for each type of faller. Thus, this study aimed to investigate the key factors affecting the fall types based on regular gait pattern. A total of 105 healthy older adults who experienced a laboratory-induced slip and fall were included. Their natural walking trial immediately prior to the novel slip trial was analyzed. To identify the factors related to fall type, gait characteristics and demographic factors were determined using univariate logistic regression, and then stepwise logistic regression was conducted to assess the slip-induced fall type based on these factors. The best fall-type prediction model involves gait speed and recovery foot angular velocity, which could predict 70.5% of feet-forward falls and 86.9% of split falls. Body mass index was also a crucial fall-type prediction with an overall prediction accuracy of 70.5%. Along with gait parameters, 84.1% of feet-forward falls and 78.7% of split falls could be predicted. The findings in this study revealed the determinators related to fall types, which enhances our knowledge of the mechanism associated to slip-induced fall and would be helpful for the development of tailored interventions for slip-induced fall prevention.

摘要

老年人在步态意外滑倒后可能会经历分裂性跌倒或脚前向跌倒,这是由于不同的神经肌肉脆弱性所致,每种跌倒类型都需要不同的干预策略。因此,本研究旨在根据常规步态模式探讨影响跌倒类型的关键因素。共纳入 105 名在实验室诱发滑倒后经历自然滑倒的健康老年人。分析了他们在新的滑倒试验之前的自然行走试验。为了确定与跌倒类型相关的因素,使用单变量逻辑回归确定步态特征和人口统计学因素,然后进行逐步逻辑回归,根据这些因素评估滑倒引起的跌倒类型。最佳跌倒类型预测模型涉及步态速度和恢复脚角度速度,可预测 70.5%的脚前向跌倒和 86.9%的分裂性跌倒。体重指数也是关键的跌倒类型预测因素,总体预测准确率为 70.5%。除了步态参数外,84.1%的脚前向跌倒和 78.7%的分裂性跌倒都可以预测。本研究的结果揭示了与跌倒类型相关的决定因素,这增强了我们对与滑倒相关跌倒机制的认识,并有助于开发针对滑倒预防的定制干预措施。

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