The Effect of a Remote Network Technology Supervised Exercise Program Combined With Drug Treatment for Fibromyalgia: Randomized, Single-Blind, Controlled Trial.
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引用次数: 0
Abstract
Background: Fibromyalgia (FM) is a chronic musculoskeletal pain disorder that is seldom reported in China. Recent studies have focused on nondrug treatments, particularly physical therapy, as an alternative to treatments using medication. With the rise of smartphones and mobile communication, mobile health technology has become a significant area of study.
Objective: This study aims to explore whether using remote network applications to supervise patient exercise, in combination with medication, can improve FM pain. It builds on previous research that focuses on drug treatments and offers insights into individualized exercise therapy for FM.
Methods: The study used a prospective, randomized controlled design with 80 participants, who were divided into 2 groups: supervised and unsupervised. Both groups received a drug regimen: oral pregabalin (75-150 mg twice daily) and duloxetine (30-60 mg once daily). The supervised group followed exercise routines with guidance from web-based rehabilitation therapist via a remote network application, while the unsupervised group exercised without supervision. The study was blinded to the participants. Primary outcomes were pain levels over the past 24 hours as measured by the Brief Pain Inventory (BPI). Secondary outcomes included pain relief, sleep improvement, quality of life, and adverse event occurrences. Observations were made at the start of treatment (T0), 1 month after treatment (T1), and 3 months after treatment (T3).
Results: We recruited 80 participants, evenly divided into 2 groups, from August 2022 to December 2023 at West China Hospital of Sichuan University. Comparisons of the 2 groups were performed using analysis of variance and Bonferroni post hoc analyses (SPSS version 25 for Windows, P<.05 considered as significant). Compared with T0, the Widespread Pain Index (WPI), symptom severity score (SSS), and BPI (pain on average, least pain in past 24 h, pain right now) scores of the 2 groups of patients with fibromyalgia at T1 were significantly lower. Compared with T0, the WPI, SSS, BPI (pain on average, worst pain in past 24 h, least pain in past 24 h, pain right now), and Fibromyalgia Impact Questionnaire scores of the 2 groups of patients at T3 were significantly lower. The WPI, SSS, BPI (pain on average, worst pain in past 24 h, pain right now), and Pittsburgh Sleep Quality Index scores of the 2 groups at T3 were significantly lower than at T1. However, the significance of some of the data did not exist after Bonferroni correction. The changes in scores from T0 to T1 (T1-T0), from T0 to T3 (T3-T0), and from T1 to T3 (T3-T1) in the supervised group were all less statistically significant compared to the unsupervised group.
Conclusions: The study showed that exercise combined with drug therapy can significantly improve the prognosis of FM, including pain relief, better sleep, and better overall quality of life; long-term supervised exercise training is more effective in improving FM symptoms and is safer and more reliable than unsupervised exercise.
背景:纤维肌痛(FM)是一种慢性肌肉骨骼疼痛疾病,在国内报道较少。最近的研究集中在非药物治疗上,特别是物理治疗,作为药物治疗的替代方法。随着智能手机和移动通信的兴起,移动医疗技术已经成为一个重要的研究领域。目的:本研究旨在探讨使用远程网络应用程序监督患者运动,并结合药物治疗是否可以改善FM疼痛。它建立在先前的研究基础上,该研究侧重于药物治疗,并为FM的个性化运动疗法提供了见解。方法:采用前瞻性、随机对照设计,将80例受试者分为监督组和非监督组。两组均接受药物治疗方案:口服普瑞巴林(75-150毫克,每日两次)和度洛西汀(30-60毫克,每日一次)。监督组通过远程网络应用程序在基于网络的康复治疗师的指导下进行锻炼,而非监督组在没有监督的情况下进行锻炼。这项研究对参与者是不公开的。主要结果是通过简短疼痛量表(BPI)测量过去24小时的疼痛水平。次要结局包括疼痛缓解、睡眠改善、生活质量和不良事件发生。分别在治疗开始(T0)、治疗后1个月(T1)和治疗后3个月(T3)进行观察。结果:我们于2022年8月至2023年12月在四川大学华西医院招募了80名参与者,平均分为2组。采用方差分析和Bonferroni post hoc分析(SPSS version 25 for Windows, p)对两组患者进行比较。结论:研究表明,运动联合药物治疗可显著改善FM的预后,包括疼痛缓解、睡眠改善和整体生活质量改善;长期有监督的运动训练在改善FM症状方面更有效,并且比无监督的运动更安全可靠。
期刊介绍:
The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades.
As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor.
Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.