Effects of a Telerehabilitation Program in Women with Fibromyalgia at 6-Month Follow-Up: Secondary Analysis of a Randomized Clinical Trial

Effectiveness of telerehabilitation on the International Classification of Functioning, Disability, and Health framework outcomes during the COVID-19 pandemic: A systematic review and meta-analysis of randomized controlled trials

Objective

This study aimed to synthesize and analyze the evidence on the effectiveness of telerehabilitation categorized according to the International Classification of Functioning, Disability, and Health (ICF) outcomes for physical therapy (PT) during the coronavirus disease 2019 (COVID-19) pandemic.

Methods

Studies were identified using the Physiotherapy Evidence Database (PEDro), Scopus, PubMed, EMBASE, and other sources of data. Randomized controlled trials comparing telerehabilitation with the control group (i.e., no treatment/usual care) were included. Standard meta-analysis techniques were applied to assess the effectiveness of telerehabilitation. Outcome measures were categorized according to the domains of the ICF.

Results

Among the 134 studies that met the eligibility criteria, the majority of findings demonstrated significant improvements across all domains of the ICF following telerehabilitation as compared to the control group, regardless of participant groups. Only 9 of 134 studies were included in the meta-analysis. Six studies enrolled individuals with COVID-19 and the remaining three enrolled individuals with knee osteoarthritis (OA) who were unable to access services at the clinic. Compared with the control group, the Borg-Rating-of-Perceived-Exertion scale, as reflected in an impairment domain, was significantly lower in individuals with COVID-19 who received telerehabilitation (3 studies, n = 135; standardized mean difference (SMD) -1.82, 95% CI -2.77 to -0.86). Compared with that in the control group, 30-second sit-to-stand test (3 studies, n = 122; SMD 0.88, 95% CI 0.52-1.25) and 6-minute-walking test (4 studies, n = 221; SMD 0.83, 95% CI 0.42-1.24), as reflected to an activity domain, showed significant improvement in the telerehabilitation group. Conversely, there was no effectiveness of telerehabilitation on an activity domain as measured by the timed up and go test in people with knee OA (3 studies, n = 111; SMD -0.45, 95% CI -1.19 to 0.30).

Conclusion

This study provides evidence supporting the effectiveness of telerehabilitation across all domains of the ICF, with significant improvements observed in the impairment and activity domains for individuals with COVID-19. These improvements are particularly evident in the meta-analysis findings such as perceived exertion, leg strength, and functional capacity.

Digital health interventions for non-older individuals at risk of frailty: A systematic review and meta-analysis

Objective

Frailty is a significant health problem that results in adverse outcomes, reduced quality of life, and increased medical and nursing care costs. This study aimed to review the effect of digital health interventions on improving physical activity, physical function, and social function in non-older individuals at risk of frailty.

Methods

Randomized controlled trials of digital health interventions reporting frailty-related outcomes on physical activity, physical function, and social function in non-older individuals at risk of frailty were collected. The literature was reviewed, and the risk of bias was assessed. Meta-analyses were conducted for each outcome, and the certainty of evidence was assessed using Grading of Recommendations Assessment, Development, and Evaluation.

Results

The review included a total of 63 records. The meta-analysis showed that digital health interventions positively affected the volume of physical activity, daily steps, walking test, walking speed, VO2peak, dynamic gait index, timed up and go test, and MOS 36-Item Short-Form Health Survey Social Functioning. However, no significant effect on the time of physical activity was found. Despite the absence of fatal bias, the overall certainty of the evidence was not high because of the small number of studies and participants included in the analysis.

Conclusions

Digital health interventions can improve physical activity, physical function, and social function in non-older individuals at risk of frailty. However, the evidence had limited certainty, and the evidence supporting the effect of digital health intervention is insufficient. Thus, more studies are needed to clarify the effects of these interventions.

Disease Phenotypes in Refractory Musculoskeletal Pain Syndromes Identified by Unsupervised Machine Learning

OBJECTIVE

Overlapping chronic pain syndromes, including fibromyalgia, are heterogeneous and often treatment-resistant entities carrying significant socioeconomic burdens. Individualized treatment approaches from both a somatic and psychological side are necessary to improve patient care. The objective of this study was to identify and visualize patient clusters in refractory musculoskeletal pain syndromes through an extensive set of clinical variables, including immunologic, psychosomatic, wearable, and sleep biomarkers.

METHODS

Data were collected during a multimodal pain program involving 202 patients. Seventy-eight percent of the patients fulfilled the criteria for fibromyalgia, 77% had a concomitant psychiatric-mediated disorder, and 22% a concomitant rheumatic immune-mediated disorder. Five patient phenotypes were identified by hierarchical agglomerative clustering as a form of unsupervised learning, and a predictive model for the Brief Pain Inventory (BPI) response was generated. Based on the clustering data, digital personas were created with DALL-E (OpenAI).

RESULTS

The most relevant distinguishing factors among clusters were living alone, body mass index, peripheral joint pain, alexithymia, psychiatric comorbidity, childhood pain, neuroleptic or benzodiazepine medication, and response to virtual reality. Having an immune-mediated disorder was not discriminatory. Three of five clusters responded to the multimodal treatment in terms of pain (BPI intensity), one cluster responded in terms of functional improvement (BPI interference), and one cluster notably responded to the virtual reality intervention. The independent predictive model confirmed strong opioids, trazodone, neuroleptic treatment, and living alone as the most important negative predictive factors for reduced pain after the program.

CONCLUSION

Our model identified and visualized clinically relevant chronic musculoskeletal pain subtypes and predicted their response to multimodal treatment. Such digital personas and avatars may play a future role in the design of personalized therapeutic modalities and clinical trials.

Generative AI-based knowledge graphs for the illustration and development of mHealth self-management content

Background

Digital therapeutics (DTx) in the form of mobile health (mHealth) self-management programs have demonstrated effectiveness in reducing disease activity across various diseases, including fibromyalgia and arthritis. However, the content of online self-management programs varies widely, making them difficult to compare.

Aim

This study aims to employ generative artificial intelligence (AI)-based knowledge graphs and network analysis to categorize and structure mHealth content at the example of a fibromyalgia self-management program.

Methods

A multimodal mHealth online self-management program targeting fibromyalgia and post-viral fibromyalgia-like syndromes was developed. In addition to general content, the program was customized to address specific features and digital personas identified through hierarchical agglomerative clustering applied to a cohort of 202 patients with chronic musculoskeletal pain syndromes undergoing multimodal assessment. Text files consisting of 22,150 words divided into 24 modules were used as the input data. Two generative AI web applications, ChatGPT-4 (OpenAI) and Infranodus (Nodus Labs), were used to create knowledge graphs and perform text network analysis, including 3D visualization. A sentiment analysis of 129 patient feedback entries was performed.

Results

The ChatGPT-generated knowledge graph model provided a simple visual overview with five primary edges: "Mental health challenges", "Stress and its impact", "Immune system function", "Long COVID and fibromyalgia" and "Pain management and therapeutic approaches". The 3D visualization provided a more complex knowledge graph, with the term "pain" appearing as the central edge, closely connecting with "sleep", "body", and "stress". Topical cluster analysis identified categories such as "chronic pain management", "sleep hygiene", "immune system function", "cognitive therapy", "healthy eating", "emotional development", "fibromyalgia causes", and "deep relaxation". Gap analysis highlighted missing links, such as between "negative behavior" and "systemic inflammation". Retro-engineering of the self-management program showed significant conceptual similarities between the knowledge graph and the original text analysis. Sentiment analysis of free text patient comments revealed that most relevant topics were addressed by the online program, with the exception of social contacts.

Conclusion

Generative AI tools for text network analysis can effectively structure and illustrate DTx content. Knowledge graphs are valuable for increasing the transparency of self-management programs, developing new conceptual frameworks, and incorporating feedback loops.

Exploring Biopsychosocial Stress Markers in Women With Fibromyalgia

BACKGROUND

Identification of fibromyalgia has been a challenge for healthcare professionals due to the lack of a clinical biomarker. A well-supported integrative hypothesis holds that this condition is a chronic pain problem partly caused by long-term dysregulation of stress response. Therefore, stress assessment from a biopsychosocial perspective may be a useful approach to recognizing fibromyalgia.

PURPOSE

A cross-sectional case-control study was conducted to explore stress markers from a multidimensional perspective, including heart rate variability (as a biomarker of stress) as well as psychological distress and social stress.

METHODS

Forty-seven women with fibromyalgia were recruited from support groups and another 47 were recruited as matched pain-free controls. Comparison and discriminant function analyses were performed.

RESULTS

The data support the goodness of biopsychosocial stress markers in women with fibromyalgia, resulting in the identification of between 70% and 74.5% of fibromyalgia cases (sensitivity) and 85%-87% pain-free controls (specificity), with medium-high levels of fit (λ = 0.58 and λ = 0.59; p < .00). Women with fibromyalgia were characterized by high levels of psychological distress, social stress (disorder levels), and autonomic dysregulation. Although distress and social stress had a greater weight in discriminant functions, dysregulation in terms of low parasympathetic activity and high sympathetic activity at rest was also relevant.

CONCLUSIONS

A biopsychosocial approach to stress with an objective biomarker such as heart rate variability may be a useful tool to identify and manage FM.

Evidence-based position paper on Physical and Rehabilitation Medicine (PRM) professional practice on telerehabilitation. The European PRM position (UEMS PRM Section)

INTRODUCTION

The evidence on the utility and effectiveness of rehabilitation interventions delivered via telerehabilitation is growing rapidly. Telerehabilitation is expected to have a key role in rehabilitation in the future.

AIM

The aim of this evidence-based position paper (EBPP) is to improve PRM physicians' professional practice in telerehabilitation to be delivered to improve functioning and to reduce activity limitations and/or participation restrictions in individuals with a variety of disabling health conditions.

METHODS

To produce recommendations for PRM physicians on telerehabilitation, a systematic review of the literature and a consensus procedure by means of a Delphi process have been performed involving the delegates of all European countries represented in the UEMS PRM Section.

RESULTS

The systematic literature review is reported together with the 32 recommendations resulting from the Delphi procedure.

CONCLUSIONS

It is recommended that PRM physicians deliver rehabilitation services remotely, via digital means or using communication technologies to eligible individuals, whenever required and feasible in a variety of health conditions in favor of the patient and his/her family, based on evidence of effectiveness and in compliance with relevant regulations. This EBPP represents the official position of the European Union through the UEMS PRM Section and designates the professional role of PRM physicians in telerehabilitation.

Effectiveness of aquatic training based on aerobic and strengthening exercises in patients with fibromyalgia: systematic review with meta-analysis

BACKGROUND AND PURPOSE

fibromyalgia is a chronic condition causing widespread pain, fatigue, limited physical function, and reduced quality of life. Aquatic training is recommended as a first-line non-pharmacological treatment. This study aims to evaluate the effectiveness of aquatic training based on aerobic and strengthening exercises in improving symptoms in women with fibromyalgia.

MATERIAL AND METHODS

a systematic review with meta-analysis was conducted by searching the PubMed, Scopus, Cochrane Library and Web of Science databases. Randomized clinical trials that compared aquatic therapy with either a control group or a land-based exercise group were included. Study quality was assessed using the PEDro scale, the risk of bias was evaluated using the Cochrane Risk of Bias Tool, and the certainty of the evidence was assessed the GRADE guidelines.

RESULTS

six randomized clinical trials comprising 9 publications showed that aquatic therapy had statistically significant benefits compared to no intervention, including pain, fatigue, fibromyalgia impact, depression, physical function, and mental health in the short term. In the medium term, improvements were observed in fibromyalgia impact, physical function, and mental health. However, aquatic therapy was not found to be superior to land-based exercise.

CONCLUSION

low to very low certainty of evidence suggested that aquatic training may reduce pain, fibromyalgia impact, fatigue and depression and improve physical function and mental health in patients with fibromyalgia. Further studies should investigate the medium and long-term effects of aquatic training using larger sample sizes.