Personalized smart voice-based electronic prescription for remote at-home feedback management in cardiovascular disease rehabilitation: a multi-center randomized controlled trial

Frontiers in Public Health

Public Health

Xiao-Ling Shou¹  Jing Yan²  Ju-Fei Wang³  Bei-Li Feng⁴  Li-Ping Xia⁵  Xiao-Jun Ji⁶  Yan Sun⁷  Hua-Xian Chen⁸  Li-Yue Zhu⁹  Yin-Hua Zhu⁹  Mei-Li Zhu^1,10 

[1] Cardiac Rehabilitation Department of Zhejiang Hospital, Hangzhou, China;Dean Office of Zhejiang Hospital, Hangzhou, China;Department of Cardiology, Medical Community of People’s Hospital of Fenghua District, Ningbo, China;Department of Cardiology, Ningbo No.2 Hospital (HWaMei Hospital, University of Chinese Academy of Sciences), Ningbo, China;Department of Cardiology, Shangyu People’s Hospital, Shaoxing, China;Department of Cardiology, Wenzhou Central Hospital, Wenzhou, China;Department of Cardiology, Zhejiang Rongjun Hospital, Jiaxing, China;Department of Rehabilitation Medicine, Xiangyang No.1 People’s Hospital, Xiangyang, China;Rehabilitation Center of Zhejiang Hospital, Hangzhou, China;Rehabilitation Medicine Department of the First People’s Hospital of Yongkang, Jinhua, China;

关键词: cardiorespiratory function;    cardiovascular disease;    health-related physical fitness;    personalized electronic prescription;    remote at-home cardiac rehabilitation;    risk factors;   

DOI  :  10.3389/fpubh.2023.1113403

 received in 2022-12-01, accepted in 2023-04-18,  发布年份 2023

来源: Frontiers

【 摘 要 】

ObjectiveTo investigate the quality and efficacy of remote at-home rehabilitation for patients with cardiovascular disease (CVD) using personalized smart voice-based electronic prescription, and further explore the standardized health management mode of remote family cardiac rehabilitation. Trial design: A multicenter, randomized (1:1), non-blind, parallel controlled study.MethodsA total of 171 patients with CVD who were admitted to 18 medical institutions in China from April 2021 to October 2022 were randomly divided into a treatment group (86 cases) and a control group (85 cases) in a non-blinded experiment, based on the sequence of enrollment. The control group received routine at-home rehabilitation training, and the treatment group received remote feedback-based at-home cardiac rehabilitation management based on routine at-home rehabilitation training. The primary outcome was the difference in VO2peak (mL/min/kg) after 12 weeks. A linear mixed model was developed with follow-up as the dependent variable. Age and baseline data were utilized as covariates, whereas hospital and patient characteristics were adjusted as random-effect variables. As the linear mixed model can accommodate missing data under the assumption of random missing data, there was no substitute missing value for quantitative data.ResultsA total of 171 participants, with 86 in the experimental group and 85 in the control group, were included in the main analysis. The analysis, which used linear mixing model, revealed significant differences in cardiopulmonary function indexes (VO2/kg peak, VO2peak, AT, METs, and maximum resistance) at different follow-up time (0, 4, and 12 weeks) in the experimental group (p < 0.05). In the control group, there was no significant difference in cardiopulmonary values at different follow-up time (0, 4, and 12 weeks; p > 0.05). VO2/kg peak (LS mean 1.49, 95%CI 0.09–2.89, p = 0.037) and other indicators of cardiopulmonary function (p < 0.05) were significantly different between the experimental group and the control group at week 12. The results were comparable in the complete case analysis.ConclusionThe remote home cardiac rehabilitation management mode using personalized smart voice-based electronic prescription provides several benefits to patients, including improvements in muscle strength, endurance, cardiopulmonary function, and aerobic metabolism. It also helps reduce risk factors for cardiovascular disease and enhances patients’ self-management abilities and treatment compliance.Clinical trial registration: http://www.chictr.org.cn, identifier ChiCTR2100044063.

【 授权许可】

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Copyright © 2023 Zhu, Xia, Yan, Shou, Zhu, Sun, Wang, Ji, Zhu, Feng and Chen.