The Assessment of Fatigue in Rheumatoid Arthritis Patients and Its Impact on Their Quality of Life

Factors influencing fatigue among patients undergoing hemodialysis: a multi-center cross-sectional study

Fatigue has been reported to be the most common symptom experienced by patients receiving hemodialysis (HD) therapy. Fatigue can lead to a reduction in their ability to engage in both routine and self-care activities, which can negatively affect their self-confidence and quality of life. This study aimed to determine the level of fatigue and the factors that affecting its level among patients receiving uHD.

METHODS

A cross-sectional design was utilized to explore the level of fatigue among patients receiving maintenance HD using the Mul-tidimensional Assessment of Fatigue (MAF) scale. Data were collected from four dialysis centers in two Saudi Arabia cities, Hail and Al-Qassim, between January 2022 and October 2022.

RESULTS

The questionnaire was completed by 236 patients. Older patients, male patients, and retired pa-tients reported significantly higher levels of fatigue (p < 0.001). In contrast, marital status, educational level, and financial status did not significantly affect the level of fatigue among patients (p = 0.193, 0.285, and 0.126, respectively). Patients who had seven or more dependents reported more fatigue than those who had lower levels of fatigue or who did not have dependents (p = 0.004). In addition, patients who had a regular exercise regimen reported significantly lower fatigue than those who did not have an exercise regimen (p = 0.011). Multiple linear regression demonstrated that employment status (student), comorbidity condition (one chronic disease), dialysis duration, satisfaction with dialysis time, and dialysis time were found to affect the fatigue scores (R2 = 0.302, p ˂ 0.001).

CONCLUSION

The findings of this study gives a broader understanding of factors influencing fatigue among patients with HD that will help to develop strategies of more focused interventions to reduce fatigue among patients with HD.

Fatigue in rheumatoid arthritis patients: The status, independent risk factors, and consistency of multiple scales

INTRODUCTION

Fatigue is a common symptom that negatively affects the outcomes and functions of rheumatoid arthritis (RA) patients. This study aimed to assess the fatigue by two scales and validate their consistency, also to comprehensively evaluate fatigue-related risk factors in RA patients.

METHODS

In this case-control study, the fatigue of 160 RA patients and 60 healthy controls was evaluated by the Bristol Rheumatoid Arthritis Fatigue Multi-Dimensional Questionnaire (BRAF-MDQ) and the Chinese version of the Brief Fatigue Inventory (BFI-C). The 28-joint disease activity score using erythrocyte sedimentation rate of RA patients was assessed.

RESULTS

The BRAF-MDQ and BFI-C scores were elevated in RA patients versus healthy controls (all p < .001). Interestingly, BRAF-MDQ global fatigue score positively correlated with BFI-C global fatigue score in both RA patients (r = .669, p < .001) and healthy controls (r = .527, p < .001); meanwhile, Kendall's tau-b test showed a high consistency between BRAF-MDQ and BFI-C global fatigue scores in RA patients (W = 0.759, p < .001) and healthy controls (W = 0.933, p < .001). Notably, higher education level (В = -4.547; 95% confidence interval: -7.065, -2.029; p < .001) and swollen joint count (В = 1.965; 95% confidence interval: 1.375, 2.554; p < .001) independently related to BRAF-MDQ global fatigue score; higher education level (В = -0.613; 95% confidence interval: -0.956, -0.269; p = .001) and clinical disease activity index (В = 0.053; 95% confidence interval: 0.005, 0.102; p = .032) independently linked with BFI-C global fatigue score.

CONCLUSION

Fatigue commonly occurs in RA patients, which independently relates to education level and disease activity. Furthermore, BRAF-MDQ and BFI-C scales exhibit a high consistency in assessing fatigue.

2023 EULAR recommendations for the management of fatigue in people with inflammatory rheumatic and musculoskeletal diseases

OBJECTIVES

Fatigue is prevalent in people with inflammatory rheumatic and musculoskeletal diseases (I-RMDs) and recognised as one of the most challenging symptoms to manage. The existence of multiple factors associated with driving and maintaining fatigue, and the evidence about what improves fatigue has led to a multifaceted approach to its management. However, there are no recommendations for fatigue management in people with I-RMDs. This lack of guidance is challenging for those living with fatigue and health professionals delivering clinical care. Therefore, our aim was to develop EULAR recommendations for the management of fatigue in people with I-RMDs.

METHODS

A multidisciplinary taskforce comprising 26 members from 14 European countries was convened, and two systematic reviews were conducted. The taskforce developed the recommendations based on the systematic review of evidence supplemented with taskforce members' experience of fatigue in I-RMDs.

RESULTS

Four overarching principles (OAPs) and four recommendations were developed. OAPs include health professionals' awareness that fatigue encompasses multiple biological, psychological and social factors which should inform clinical care. Fatigue should be monitored and assessed, and people with I-RMDs should be offered management options. Recommendations include offering tailored physical activity and/or tailored psychoeducational interventions and/or, if clinically indicated, immunomodulatory treatment initiation or change. Patient-centred fatigue management should consider the individual's needs and preferences, their clinical disease activity, comorbidities and other psychosocial and contextual factors through shared decision-making.

CONCLUSIONS

These 2023 EULAR recommendations provide consensus and up-to-date guidance on fatigue management in people with I-RMDs.

Self-regulation of effort for a better health-related quality of life: a multidimensional activity pacing model for chronic pain and fatigue management

PURPOSE

To propose a comprehensive multidimensional model of activity pacing that improves health-related quality of life and promotes sustained physical activity engagement among adults with chronic conditions.

MATERIALS AND METHODS

A narrative review was conducted to examine the existing literature on activity pacing, health-related quality of life, pain and fatigue management, and physical activity promotion in chronic conditions.

RESULTS

The literature revealed a lack of a cohesive approach towards a multidimensional model for using activity pacing to improve health-related quality of life. A comprehensive multidimensional model of activity pacing was proposed, emphasizing the importance of considering all aspects of pacing for sustained physical activity engagement and improved health-related quality of life. The model incorporates elements such as rest breaks, self-regulatory skills, environmental factors, and effective coping strategies for depression/anxiety. It takes into account physical, psychological, and environmental factors, all of which contribute significantly to the enhancement of health-related quality of life, physical function, and overall well-being, reflecting a holistic approach.

CONCLUSIONS

The model offers guidance to researchers and clinicians in effectively educating patients on activity pacing acquisition and in developing effective interventions to enhance physical activity engagement and health outcomes among adults with chronic conditions. Additionally, it serves as a tool towards facilitating discussions on sustained physical activity and a healthy lifestyle for patients, which can eventually lead to improved quality of life.

Virtual Reality Meditation for Fatigue in Persons With Rheumatoid Arthritis: Mixed Methods Pilot Study

BACKGROUND

Effective symptom management is crucial to enhancing the quality of life for individuals with chronic diseases. Health care has changed markedly over the past decade as immersive, stand-alone, and wearable technologies including virtual reality have become available. One chronic pain population that could benefit from such an intervention is individuals with rheumatoid arthritis (RA). Recent pharmacologic advances in the management of RA have led to a decrease in inflammatory symptoms (eg, chronic pain) or even disease remission, yet up to 70% of patients with RA still suffer from fatigue. While VR-delivered behavior, meditation, and biofeedback programs show promise for pain and anxiety management, there is little information on the use of virtual reality meditation (VRM) for fatigue management among individuals with RA.

OBJECTIVE

This study aims to (1) examine the feasibility of implementing a study protocol that uses VRM, (2) determine the acceptability of using VRM for fatigue management in an outpatient population, and (3) identify barriers and contextual factors that might impact VRM use for fatigue management in outpatients with RA.

METHODS

We used a convergent, mixed methods design and enrolled adults aged 18 years or older with a clinical diagnosis of RA. Patient-Reported Outcome Measure Information System (PROMIS) measures of fatigue, depression, anxiety, pain behavior, and physical function were assessed alongside the brief mood introspection scale at baseline and weekly for 4 weeks. VRM use across the 4-week study period was automatically stored on headsets and later extracted for analysis. Semistructured interview questions focused on feedback regarding the participant's experience with RA, previous experience of fatigue, strategies participants use for fatigue management, and the participant's experience using VRM and recommendations for future use.

RESULTS

A total of 13 participants completed this study. Most participants completed all study surveys and measures (11/13, 84% and 13/13, 100%, respectively) and were active participants in interviews at the beginning and end of the program. Participants used VRM an average of 8.9 (SD 8.5) times over the course of the 4-week program. Most participants enjoyed VRM, found it relaxing, or recommended its use (12/13, 92%), but 8 (62%) noted barriers and conceptual factors that impacted VRM use. On average, participants saw decreases in PROMIS fatigue (-6.4, SD 5.1), depression (-5.6, SD 5.7), anxiety (-4.5, SD 6), and pain behavior (-3.9, SD 5.3), and improvements in PROMIS physical function (1.5, SD 2.7) and Brief Mood Introspection Scale mood (5.3, SD 6.7) over the course of this 4-week study.

CONCLUSIONS

While this study's implementation was feasible, VRM's acceptability as an adjunctive modality for symptom management in RA is contingent on effectively overcoming barriers to use and thoughtfully addressing the contextual factors of those with RA to ensure successful intervention deployment.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04804462; https://classic.clinicaltrials.gov/ct2/show/NCT04804462.

RANet: a custom CNN model and quanvolutional neural network for the automated detection of rheumatoid arthritis in hand thermal images

Rheumatoid arthritis is an autoimmune disease which affects the small joints. Early prediction of RA is necessary for the treatment and management of the disease. The current work presents a deep learning and quantum computing-based automated diagnostic approach for RA in hand thermal imaging. The study's goals are (i) to develop a custom RANet model and compare its performance with the pretrained models and quanvolutional neural network (QNN) to distinguish between the healthy subjects and RA patients, (ii) To validate the performance of the custom model using feature selection method and classification using machine learning (ML) classifiers. The present study developed a custom RANet model and employed pre-trained models such as ResNet101V2, InceptionResNetV2, and DenseNet201 to classify the RA patients and normal subjects. The deep features extracted from the RA Net model are fed into the ML classifiers after the feature selection process. The RANet model, RA Net+ SVM, and QNN model produced an accuracy of 95%, 97% and 93.33% respectively in the classification of healthy groups and RA patients. The developed RANet and QNN models based on thermal imaging could be employed as an accurate automated diagnostic tool to differentiate between the RA and control groups.

Predicting physical activity and sarcopenia-related health outcomes in women with rheumatoid arthritis: A test of the self-determination theory

AIM

This study aimed to examine a hypothetical model of physical activity (PA) and health outcomes related to sarcopenia in women with rheumatoid arthritis (RA) based on self-determination theory.

DESIGN

Cross-sectional study.

METHODS

This study included 214 women diagnosed with RA from the outpatient rheumatology department of a university-affiliated hospital in South Korea. Data were collected from September 2019 to August 2020 through structured questionnaires and anthropometric measurements and analysed using path analysis to test the hypothesized model. The primary health outcomes were perceived health status and sarcopenia-related health (thigh circumference, handgrip strength and sarcopenia risk).

RESULTS

The final model's fit indices were adequate. Physical activity was directly affected by motivation for PA, while depression, self-efficacy for PA, health care provider's autonomy support and basic psychological needs satisfaction indirectly affected PA. Physical activity directly affected perceived health status and thigh circumference, while perceived sarcopenia risk and handgrip strength were directly affected by disease activity and age.

PATIENT OR PUBLIC CONTRIBUTION

Patients were involved in a questionnaire-based survey.

Polymorphisms in microRNA binding site of SET8 regulate the risk of rheumatoid arthritis

Rheumatoid arthritis (RA) is a complex, heterogeneous, progressive and long-term autoimmune disease characterized by symmetrical joint inflammation and bone erosion. The etiology of RA is unclear, but its pathogenesis is associated with oxidative stress and inflammatory cytokines. Single nucleotide polymorphisms (SNPs) in the microRNA (miRNA)-binding sites modify the development of rheumatic disease by regulating the expression of target genes. The present study investigated whether SNPs in the miRNA binding site in the 3' untranslated region (3'-UTR) of SET domain containing (lysine methyltransferase) 8 (SET8) and Keratin 81 (KRT81), namely rs16917496 and rs3660, respectively, were associated with the occurrence of RA. The polymerase chain reaction-ligase detection reaction assay showed that the distribution frequencies of the CC genotype (P=0.025) of SNP rs16917496 in SET8 were significantly higher in patients with RA than in healthy controls, which indicated that the CC genotype was associated with an increased risk of RA. SET8 expression in the blood samples of CC genotype carriers was lower than that of TT genotype carriers. Moreover, the CC genotype carriers exhibited higher reactive oxygen species (ROS) levels (1011.500±536.426 vs. 548.616±190.508, P=0.032) and lower interleukin-10 (IL-10) levels (P<0.001). The present study demonstrated that SNP rs16917496 in the 3'-UTR of SET8 was a predictor of RA risk and may regulate RA development by mediating expression of SET8, thereby regulating the levels of ROS and IL-10.