Ganbat Uyanga, Feldman Boris, Arishenkoff Shane, Meneilly Graydon S, Madden Kenneth M
Department of Medicine, Division of Geriatric Medicine, University of British Columbia Vancouver, BC CAN.
Department of Medicine, General Internal Medicine, University of British Columbia Vancouver, BC CAN.
POCUS J. 2024 Nov 15;9(2):117-124. doi: 10.24908/pocus.v9i2.17659. eCollection 2024.
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. 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. 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=0.16, P < 0.000), average stride length (R=0.142, P < 0.000), and average stride velocity (R=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. 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.
步态参数和肌肉减少症均可预测老年人的跌倒风险。我们的目的是评估通过床旁超声(POCUS)快速、易于获取的大腿前侧肌肉测量指标是否与标准步态测量指标显著相关。所有受试者均来自某学术中心的门诊老年医学诊所。使用便携式超声设备测量股四头肌厚度。患者穿着舒适的步行鞋行走6分钟,测量步态变量。主要反应变量为步态变量,预测变量为年龄、生物性别、体重指数和肌肉厚度。进行单变量和多变量回归分析。总共从老年医学诊所招募了150名参与者(65名女性,84名男性)。对149名参与者测量了肌肉厚度,平均值(标准差)为1.91(0.52)(中位数1.82厘米,范围0.96至3.68厘米)。对步态参数与年龄进行单变量分析显示,与步态速度(R = 0.16,P < 0.000)、平均步幅长度(R = 0.142,P < 0.000)和平均步幅速度(R = 0.182,P < 0.000)存在统计学显著相关性。在所有步态变量中,平均摆动时间(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,年龄是单变量分析中所有显著步态变量的显著独立变量。POCUS显示与平均摆动时间、平均站立时间和步时变异性存在显著关联。尽管还需要开展更多工作,但POCUS有潜力成为一种用于步态评估的快速筛查工具。