Uyanga Ganbat, Boris Feldman, Shane Arishenkoff, Graydon S Meneilly, Kenneth M Madden
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Univariate and multivariate regression analyses were performed. <b>Results:</b> A total of 150 participants were recruited from geriatric medicine clinics (65 women, 84 men). Muscle thickness was measured in 149 participants, and the mean (SD) was 1.91 (0.52) (median 1.82 cm, 0.96 to 3.68 cm). Univariate analysis of gait parameters with age showed a statistically significant correlation with gait speed (R<sup>2</sup>=0.16, P < 0.000), average stride length (R<sup>2</sup>=0.142, P < 0.000), and average stride velocity (R<sup>2</sup>=0.182, P < 0.000). Among all the gait variables, average swing time (P = 0.010) and average stance time (P = 0.010) were correlated significantly with muscle thickness. For multivariate analysis with age and gait variables, age was a significant independent variable for all gait variables that were significant in univariate analysis. <b>Conclusion:</b> POCUS showed a significant association with average swing time, average stance time, and step time variability. 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引用次数: 0
摘要
背景:步态参数和肌肉减少症都能预测老年人跌倒的风险。我们的目的是评估通过点护理超声(POCUS)快速,易于获得的大腿前肌测量是否与标准步态测量显着相关。方法:所有受试者均来自某学术中心老年医学门诊。用便携式超声仪测量股四头肌厚度。步态变量由患者穿着舒适的步行鞋步行6分钟来测量。主要反应变量为步态变量,预测变量为年龄、生理性别、体重指数和肌肉厚度。进行单因素和多因素回归分析。结果:共从老年医学诊所招募了150名参与者(65名女性,84名男性)。149名参与者测量了肌肉厚度,平均(SD)为1.91(0.52)(中位数为1.82厘米,0.96至3.68厘米)。步态参数随年龄的单因素分析显示,步态速度(R2=0.16, P < 0.000)、平均步幅(R2=0.142, P < 0.000)、平均步幅速度(R2=0.182, P < 0.000)具有统计学意义。在所有步态变量中,平均摇摆时间(P = 0.010)和平均站立时间(P = 0.010)与肌肉厚度显著相关。对于年龄和步态变量的多变量分析,年龄是所有单变量分析中显著的步态变量的显著自变量。结论:POCUS与平均摆动时间、平均站姿时间和步长变异性有显著相关性。虽然需要做更多的工作,POCUS有潜力成为步态评估的快速筛查工具。
Association Between Standard Gait Measures and Anterior Quadriceps Muscle Thickness as Measured by Point of Care Ultrasound (POCUS).
Background: Gait parameters and sarcopenia both predict falls risk among older adults. Our objective was to evaluate whether fast, easy-to-obtain measures of anterior thigh muscle by point of care ultrasound (POCUS) are significantly associated with standard gait measures. Methods: All subjects were referred from ambulatory geriatric medicine clinics at an academic center. Quadriceps muscle thickness was measured by a portable ultrasound device. Gait variables were measured by the patient in comfortable walking shoes walking for six minutes. The primary response variables were gait variables, and the predictor variables were age, biological sex, body mass index, and muscle thickness. Univariate and multivariate regression analyses were performed. Results: A total of 150 participants were recruited from geriatric medicine clinics (65 women, 84 men). Muscle thickness was measured in 149 participants, and the mean (SD) was 1.91 (0.52) (median 1.82 cm, 0.96 to 3.68 cm). Univariate analysis of gait parameters with age showed a statistically significant correlation with gait speed (R2=0.16, P < 0.000), average stride length (R2=0.142, P < 0.000), and average stride velocity (R2=0.182, P < 0.000). Among all the gait variables, average swing time (P = 0.010) and average stance time (P = 0.010) were correlated significantly with muscle thickness. For multivariate analysis with age and gait variables, age was a significant independent variable for all gait variables that were significant in univariate analysis. Conclusion: POCUS showed a significant association with average swing time, average stance time, and step time variability. Although more work needs to be done, POCUS has the potential to be a rapid screening tool for gait assessment.