中风患者跨越障碍时的步态特征与跌倒风险之间的关系前瞻性队列研究

IF 2.2 3区医学 Q3 NEUROSCIENCES

Gait & posture Pub Date : 2025-04-02 DOI:10.1016/j.gaitpost.2025.03.022

Xianglin Wan , Zihao Zhu , Feng Xu , Qiujie Li

{"title":"中风患者跨越障碍时的步态特征与跌倒风险之间的关系前瞻性队列研究","authors":"Xianglin Wan , Zihao Zhu , Feng Xu , Qiujie Li","doi":"10.1016/j.gaitpost.2025.03.022","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>In daily life, stroke patients frequently experience falls during obstacle crossing. Analyzing the gait characteristics of patients in high-risk falling scenarios can help identify and predict fall risks.</div></div><div><h3>Research question</h3><div>Exploring the predictive power of gait characteristics during obstacle crossing for fall risk in stroke patients.</div></div><div><h3>Methods</h3><div>Recruitment of 38 stroke patients with unilateral hemiplegia discharged from rehabilitation. A Qualisys motion capture system and two Kistler force plates were used to record the marker positions and the ground reaction forces during crossing an obstacle 4 cm in height with the affected limb as the leading limb. Gait spatio-temporal parameters, joint angles, and joint moments were calculated. Following a 12-month follow-up survey to collect data on falls among participants, independent samples <em>t</em>-test and binary logistic regression models were employed to identify predictors associated with future fall risk.</div></div><div><h3>Results</h3><div>During the follow-up period, 13 participants experienced at least one fall and were categorized into the fall group; 14 participants did not experience any falls and were categorized into the non-fall group. Binary logistic regression analysis revealed that the toe-clearance distance of the trailing limb, as well as the peak ankle plantarflexion moment of the trailing limb during double support phase, are effective predictors of fall risk in stroke patients (<em>P</em> < 0.05). The overall correct prediction rate of the regression model incorporating both factors was 85.2 %.</div></div><div><h3>Significance</h3><div>Gait analysis during obstacle crossing holds potential clinical value in identifying future fall risk in stroke patients.</div></div>","PeriodicalId":12496,"journal":{"name":"Gait & posture","volume":"120 ","pages":"Pages 9-16"},"PeriodicalIF":2.2000,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Association between gait characteristics during obstacle crossing and fall risk in stroke patients: A prospective cohort study\",\"authors\":\"Xianglin Wan , Zihao Zhu , Feng Xu , Qiujie Li\",\"doi\":\"10.1016/j.gaitpost.2025.03.022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>In daily life, stroke patients frequently experience falls during obstacle crossing. Analyzing the gait characteristics of patients in high-risk falling scenarios can help identify and predict fall risks.</div></div><div><h3>Research question</h3><div>Exploring the predictive power of gait characteristics during obstacle crossing for fall risk in stroke patients.</div></div><div><h3>Methods</h3><div>Recruitment of 38 stroke patients with unilateral hemiplegia discharged from rehabilitation. A Qualisys motion capture system and two Kistler force plates were used to record the marker positions and the ground reaction forces during crossing an obstacle 4 cm in height with the affected limb as the leading limb. Gait spatio-temporal parameters, joint angles, and joint moments were calculated. Following a 12-month follow-up survey to collect data on falls among participants, independent samples <em>t</em>-test and binary logistic regression models were employed to identify predictors associated with future fall risk.</div></div><div><h3>Results</h3><div>During the follow-up period, 13 participants experienced at least one fall and were categorized into the fall group; 14 participants did not experience any falls and were categorized into the non-fall group. Binary logistic regression analysis revealed that the toe-clearance distance of the trailing limb, as well as the peak ankle plantarflexion moment of the trailing limb during double support phase, are effective predictors of fall risk in stroke patients (<em>P</em> < 0.05). The overall correct prediction rate of the regression model incorporating both factors was 85.2 %.</div></div><div><h3>Significance</h3><div>Gait analysis during obstacle crossing holds potential clinical value in identifying future fall risk in stroke patients.</div></div>\",\"PeriodicalId\":12496,\"journal\":{\"name\":\"Gait & posture\",\"volume\":\"120 \",\"pages\":\"Pages 9-16\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Gait & posture\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0966636225001547\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gait & posture","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0966636225001547","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}

引用次数: 0

摘要

在日常生活中，脑卒中患者经常在过障碍时摔倒。分析高危跌倒患者的步态特征有助于识别和预测跌倒风险。研究问题：探索脑卒中患者过障时步态特征对跌倒风险的预测能力。方法选取脑卒中单侧偏瘫康复出院患者38例。采用Qualisys运动捕捉系统和两块Kistler力板，记录了以患肢为前肢穿越高度为4 cm的障碍物时的标记位置和地面反作用力。计算步态时空参数、关节角度和关节力矩。经过12个月的随访调查，收集参与者跌倒的数据，采用独立样本t检验和二元逻辑回归模型来确定与未来跌倒风险相关的预测因素。结果在随访期间，13名参与者经历了至少一次跌倒，被分为跌倒组；14名参与者没有跌倒，被分为非跌倒组。二元logistic回归分析显示，双支撑期后肢足趾间隙距离和后肢踝关节跖屈峰值力矩是脑卒中患者跌倒风险的有效预测因子（P <； 0.05）。综合这两个因素的回归模型的总体预测正确率为85.2% %。意义：脑卒中患者过障时的步态分析对确定未来跌倒风险具有潜在的临床价值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Association between gait characteristics during obstacle crossing and fall risk in stroke patients: A prospective cohort study

Background

In daily life, stroke patients frequently experience falls during obstacle crossing. Analyzing the gait characteristics of patients in high-risk falling scenarios can help identify and predict fall risks.

Research question

Exploring the predictive power of gait characteristics during obstacle crossing for fall risk in stroke patients.

Methods

Recruitment of 38 stroke patients with unilateral hemiplegia discharged from rehabilitation. A Qualisys motion capture system and two Kistler force plates were used to record the marker positions and the ground reaction forces during crossing an obstacle 4 cm in height with the affected limb as the leading limb. Gait spatio-temporal parameters, joint angles, and joint moments were calculated. Following a 12-month follow-up survey to collect data on falls among participants, independent samples t-test and binary logistic regression models were employed to identify predictors associated with future fall risk.

Results

During the follow-up period, 13 participants experienced at least one fall and were categorized into the fall group; 14 participants did not experience any falls and were categorized into the non-fall group. Binary logistic regression analysis revealed that the toe-clearance distance of the trailing limb, as well as the peak ankle plantarflexion moment of the trailing limb during double support phase, are effective predictors of fall risk in stroke patients (P < 0.05). The overall correct prediction rate of the regression model incorporating both factors was 85.2 %.

Significance

Gait analysis during obstacle crossing holds potential clinical value in identifying future fall risk in stroke patients.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Gait & posture 医学-神经科学

CiteScore

4.70

自引率

12.50%

发文量

616

审稿时长

6 months

期刊介绍： Gait & Posture is a vehicle for the publication of up-to-date basic and clinical research on all aspects of locomotion and balance. The topics covered include: Techniques for the measurement of gait and posture, and the standardization of results presentation; Studies of normal and pathological gait; Treatment of gait and postural abnormalities; Biomechanical and theoretical approaches to gait and posture; Mathematical models of joint and muscle mechanics; Neurological and musculoskeletal function in gait and posture; The evolution of upright posture and bipedal locomotion; Adaptations of carrying loads, walking on uneven surfaces, climbing stairs etc; spinal biomechanics only if they are directly related to gait and/or posture and are of general interest to our readers; The effect of aging and development on gait and posture; Psychological and cultural aspects of gait; Patient education.