Faculdade de Educação Física, Universidade de Brasilia (UnB), Brasília, Brazil; Rede SARAH de Hospitais de Reabilitação, Brasília, Brazil.
Rede SARAH de Hospitais de Reabilitação, Brasília, Brazil.
Braz J Phys Ther. 2021 Sep-Oct;25(5):610-616. doi: 10.1016/j.bjpt.2021.03.002. Epub 2021 Mar 26.
Adequate muscle strength is essential for walking performance in individuals with stroke.
To investigate the accuracy of different forms of muscle knee extension strength analysis to identify high or low walking performance in individuals with chronic stroke.
Twenty-eight participants with a chronic stroke for more than six months participated. Independence for walking was judged by measurement of walking performance assessed for comfortable walking speed (CWS), maximum walking speed (MWS), and the Six Minute Walk Test (6MWT). Peak knee extension torque of the paretic side, non-paretic side, sum of the sides (SS), and difference in the sides (DS) was assessed during concentric movements using an isokinetic dynamometer.
The equation with greatest predictive capacity for CWS and MWS included the DS as the main predictor (R of 0.65 and 0.71, respectively, p < 0.05). The variable with the greatest predictive capacity for 6MWT was time since injury (R of 0.68, p < 0.05). The highest percentile for CWS in the receiver operating characteristic curve of DS was 25 Nm/kg (cut-off: -12.75 for CWS of 0.498 m/s). The 75th percentile of the 6MWT (324.3 m) was used as the cut-off for the SS (2.1 Nm/kg). The area under the curve for CWS was 0.76 (p < 0.05) on the DS and 0.75 (p < 0.05) for 6MWT on the SS.
The models of muscle knee extension strength analysis using the SS and DS presented moderate accuracy to identify walking performance in individuals with chronic stroke.
足够的肌肉力量对于脑卒中患者的步行表现至关重要。
研究不同形式的肌肉膝关节伸展力量分析在识别慢性脑卒中患者高或低步行表现的准确性。
28 名患有慢性脑卒中超过 6 个月的参与者参与了研究。通过测量步行表现评估步行能力,包括舒适步行速度(CWS)、最大步行速度(MWS)和 6 分钟步行测试(6MWT)。使用等速测力仪在向心运动中评估患侧、非患侧、双侧总和(SS)和双侧差值(DS)的峰值膝关节伸展扭矩。
对于 CWS 和 MWS 具有最大预测能力的方程包括 DS 作为主要预测因子(分别为 R 的 0.65 和 0.71,p<0.05)。对于 6MWT 具有最大预测能力的变量是受伤时间(R 的 0.68,p<0.05)。DS 的 CWS 受试者工作特征曲线的最高百分位数为 25 Nm/kg(截断值:CWS 为 0.498 m/s 的-12.75)。6MWT 的第 75 百分位数(324.3 m)被用作 SS 的截断值(2.1 Nm/kg)。DS 上的 CWS 的曲线下面积为 0.76(p<0.05),SS 上的 6MWT 为 0.75(p<0.05)。
使用 SS 和 DS 的肌肉膝关节伸展力量分析模型对于识别慢性脑卒中患者的步行表现具有中等准确性。