PDF(Pubmed)
Abstract：
BACKGROUND: Accelerometer-derived physical activity (PA) from cardiac devices are available via remote monitoring platforms yet rarely reviewed in clinical practice. We aimed to investigate the association between PA and clinical measures of frailty and physical functioning.
METHODS: The PATTErn study (A study of Physical Activity paTTerns and major health Events in older people with implantable cardiac devices) enrolled participants aged 60 + undergoing remote cardiac monitoring. Frailty was measured using the Fried criteria and gait speed (m/s), and physical functioning by NYHA class and SF-36 physical functioning score. Activity was reported as mean time active/day across 30-days prior to enrolment (30-day PA). Multivariable regression methods were utilised to estimate associations between PA and frailty/functioning (OR = odds ratio, β = beta coefficient, CI = confidence intervals).
RESULTS: Data were available for 140 participants (median age 73, 70.7% male). Median 30-day PA across the analysis cohort was 134.9 min/day (IQR 60.8-195.9). PA was not significantly associated with Fried frailty status on multivariate analysis, however was associated with gait speed (β = 0.04, 95% CI 0.01-0.07, p = 0.01) and measures of physical functioning (NYHA class: OR 0.73, 95% CI 0.57-0.92, p = 0.01, SF-36 physical functioning: β = 4.60, 95% CI 1.38-7.83, p = 0.005).
CONCLUSIONS: PA from cardiac devices was associated with physical functioning and gait speed. This highlights the importance of reviewing remote monitoring PA data to identify patients who could benefit from existing interventions. Further research should investigate how to embed this into clinical pathways.
METHODS: The PATTErn study (A study of Physical Activity paTTerns and major health Events in older people with implantable cardiac devices) enrolled participants aged 60 + undergoing remote cardiac monitoring. Frailty was measured using the Fried criteria and gait speed (m/s), and physical functioning by NYHA class and SF-36 physical functioning score. Activity was reported as mean time active/day across 30-days prior to enrolment (30-day PA). Multivariable regression methods were utilised to estimate associations between PA and frailty/functioning (OR = odds ratio, β = beta coefficient, CI = confidence intervals).
RESULTS: Data were available for 140 participants (median age 73, 70.7% male). Median 30-day PA across the analysis cohort was 134.9 min/day (IQR 60.8-195.9). PA was not significantly associated with Fried frailty status on multivariate analysis, however was associated with gait speed (β = 0.04, 95% CI 0.01-0.07, p = 0.01) and measures of physical functioning (NYHA class: OR 0.73, 95% CI 0.57-0.92, p = 0.01, SF-36 physical functioning: β = 4.60, 95% CI 1.38-7.83, p = 0.005).
CONCLUSIONS: PA from cardiac devices was associated with physical functioning and gait speed. This highlights the importance of reviewing remote monitoring PA data to identify patients who could benefit from existing interventions. Further research should investigate how to embed this into clinical pathways.
摘要：
背景：来自心脏设备的加速度计衍生的身体活动（PA）可通过远程监测平台获得，但在临床实践中很少进行审查。我们旨在调查PA与虚弱和身体功能的临床测量之间的关联。
方法：PATTErn研究（一项关于使用植入式心脏装置的老年人的体力活动和重大健康事件的研究）招募了60岁以上接受远程心脏监测的参与者。使用Fried标准和步态速度（m/s）测量虚弱，和身体功能按NYHA等级和SF-36身体功能评分。活动报告为在登记前30天的平均活动时间/天(30天PA)。多变量回归方法被用来估计PA和虚弱/功能之间的关联(OR=优势比，β=β系数，CI=置信区间)。
结果：可获得140名参与者的数据（中位年龄73岁，70.7%男性）。分析队列中30天PA的中位数为134.9分钟/天（IQR60.8-195.9）。在多变量分析中，PA与Fried虚弱状态没有显着相关，然而，与步态速度（β=0.04，95％CI0.01-0.07，p=0.01）和身体功能测量（NYHA等级：OR0.73，95％CI0.57-0.92，p=0.01，SF-36身体功能：β=4.60，95％CI1.38-7.83，p=0.005）相关。
结论：来自心脏装置的PA与身体功能和步态速度相关。这突出了审查远程监测PA数据以确定可以从现有干预措施中受益的患者的重要性。进一步的研究应该研究如何将其嵌入临床路径。
方法：PATTErn研究（一项关于使用植入式心脏装置的老年人的体力活动和重大健康事件的研究）招募了60岁以上接受远程心脏监测的参与者。使用Fried标准和步态速度（m/s）测量虚弱，和身体功能按NYHA等级和SF-36身体功能评分。活动报告为在登记前30天的平均活动时间/天(30天PA)。多变量回归方法被用来估计PA和虚弱/功能之间的关联(OR=优势比，β=β系数，CI=置信区间)。
结果：可获得140名参与者的数据（中位年龄73岁，70.7%男性）。分析队列中30天PA的中位数为134.9分钟/天（IQR60.8-195.9）。在多变量分析中，PA与Fried虚弱状态没有显着相关，然而，与步态速度（β=0.04，95％CI0.01-0.07，p=0.01）和身体功能测量（NYHA等级：OR0.73，95％CI0.57-0.92，p=0.01，SF-36身体功能：β=4.60，95％CI1.38-7.83，p=0.005）相关。
结论：来自心脏装置的PA与身体功能和步态速度相关。这突出了审查远程监测PA数据以确定可以从现有干预措施中受益的患者的重要性。进一步的研究应该研究如何将其嵌入临床路径。
