Kawagoshi Atsuyoshi, Iwakura Masahiro, Furukawa Yutaka, Sugawara Keiyu, Takahashi Hitomi, Shioya Takanobu
Department of Rehabilitation, Akita City Hospital, Japan.
Department of Physical Therapy, Fukushima Medical University, Japan.
Phys Ther Res. 2022;25(3):143-149. doi: 10.1298/ptr.E10208. Epub 2022 Dec 22.
To develop an equation of the predicted amount of low-intensity physical activity (LPA) by analyzing clinical parameters in patients with chronic obstructive pulmonary disease (COPD).
In this cross-sectional study, we analyzed the assessments of clinical parameters evaluated every 6 months from the start of pulmonary rehabilitation in 53 outpatients with stable COPD (age 77 ± 6 yrs; 46 men; body mass index 21.8 ± 4.1 kg/m; forced expiratory volume in one second 63.0 ± 26.4% pred). An uniaxial accelerometer was used to measure the number of steps and the time spent in LPA of 1.8-2.3 metabolic equivalents during 14 consecutive days. We also evaluated body composition, respiratory function, skeletal muscle strength, inspiratory muscle strength, exercise capacity, and gait speed. Factors associated with the time spent in LPA were examined by multivariate regression analysis. Internal validity between the predicted amount of LPA obtained by the equation and the measured amount was examined by regression analysis.
Multivariate regression analysis revealed that gait speed (β = 0.369, p = 0.007) and maximum inspiratory mouth pressure (PI) (β = 0.329, p = 0.016) were significant influence factors on LPA (R = 0.354, p <0.001). The stepwise regression analysis showed a moderate correlation between the measured amount and predicted amount of LPA calculated by the regression equation (r = 0.609, p <0.001; LPA = 31.909 × gait speed + 0.202 × PI - 20.553).
Gait speed and PI were extracted as influence factors on LPA, suggesting that the regression equation could predict the amount of LPA.
通过分析慢性阻塞性肺疾病(COPD)患者的临床参数,建立低强度体力活动(LPA)预测量的方程。
在这项横断面研究中,我们分析了53例稳定期COPD门诊患者(年龄77±6岁;46例男性;体重指数21.8±4.1kg/m;一秒用力呼气容积为预计值的63.0±26.4%)从肺康复开始每6个月评估一次的临床参数。使用单轴加速度计连续14天测量步数以及1.8 - 2.3代谢当量的低强度体力活动所花费的时间。我们还评估了身体成分、呼吸功能、骨骼肌力量、吸气肌力量、运动能力和步态速度。通过多因素回归分析检查与低强度体力活动所花费时间相关的因素。通过回归分析检验由该方程获得的低强度体力活动预测量与测量量之间的内部效度。
多因素回归分析显示,步态速度(β = 0.369,p = 0.007)和最大吸气口腔压力(PI)(β = 0.329,p = 0.016)是低强度体力活动的显著影响因素(R = 0.354,p <0.001)。逐步回归分析显示,回归方程计算的低强度体力活动测量量与预测量之间存在中度相关性(r = 0.609,p <0.001;低强度体力活动量 = 31.909×步态速度 + 0.202×PI - 20.553)。
步态速度和PI被提取为低强度体力活动的影响因素,表明该回归方程可以预测低强度体力活动量。