Associations between fatigue impact and lifestyle factors in people with multiple sclerosis - The Danish MS hospitals rehabilitation study

Gait and heart rate: do they measure trait or state physical fatigue in people with multiple sclerosis?

BACKGROUND

Trait and state physical fatigue (trait-PF and state-PF) negatively impact many people with multiple sclerosis (pwMS) but are challenging symptoms to measure. In this observational study, we explored the role of specific gait and autonomic nervous system (ANS) measures (i.e., heart rate, HR, r-r interval, R-R, HR variability, HRV) in trait-PF and state-PF.

METHODS

Forty-eight pwMS [42 ± 1.9 years, 65% female, EDSS 2 (IQR: 0-5.5)] completed the Timed Up and Go test (simple and with dual task, TUG-DT) and the 6-min walk test (6MWT). ANS measures were measured via a POLAR H10 strap. Gait was measured using inertial-measurement units (OPALs, APDM Inc). Trait-PF was evaluated via the Modified Fatigue Impact Scale (MFIS) motor component. State-PF was evaluated via a Visual Analog Scale (VAS) scale before and after the completion of the 6MWT. Multiple linear regression models identified trait-PF and state-PF predictors.

RESULTS

Both HR and gait metrics were associated with trait-PF and state-PF. HRV at rest was associated only with state-PF. In models based on the first 3 min of the 6MWT, double support (%) and cadence explained 47% of the trait-PF variance; % change in R-R explained 43% of the state-PF variance. Models based on resting R-R and TUG-DT explained 39% of the state-PF.

DISCUSSION

These findings demonstrate that specific gait measures better capture trait-PF, while ANS metrics better capture state-PF. To capture both physical fatigue aspects, the first 3 min of the 6MWT are sufficient. Alternatively, TUG-DT and ANS rest metrics can be used for state-PF prediction in pwMS when the 6MWT is not feasible.

Going beyond PA: Assessing sensorimotor capacity with wearables in multiple sclerosis-a cross-sectional study

BACKGROUND

Wearable technologies are currently clinically used to assess energy expenditure in a variety of populations, e.g., persons with multiple sclerosis or frail elderly. To date, going beyond physical activity, deriving sensorimotor capacity instead of energy expenditure, is still lacking proof of feasibility.

METHODS

In this study, we read out sensors (accelerometer and gyroscope) of smartwatches in a sample of 90 persons with multiple sclerosis over the course of one day of everyday life in an inpatient setting. We derived a variety of different kinematic parameters, in addition to lab-based tests of sensorimotor performance, to examine their interrelation by principal component, cluster, and regression analyses.

RESULTS

These analyses revealed three components of behavior and sensorimotor capacity, namely clinical characteristics with an emphasis on gait, gait-related physical activity, and upper-limb related physical activity. Further, we were able to derive four clusters with different behavioral/capacity patterns in these dimensions. In a last step, regression analyses revealed that three selected smartwatch derived kinematic parameters were able to partially predict sensorimotor capacity, e.g., grip strength and upper-limb tapping.

CONCLUSIONS

Our analyses revealed that physical activity can significantly differ between persons with comparable clinical characteristics and that assessments of physical activity solely relying on gait can be misleading. Further, we were able to extract parameters that partially go beyond physical activity, with the potential to be used to monitor the course of disease progression and rehabilitation, or to early identify persons at risk or a sub-clinical threshold of disease severity.

Fatigue and health-related quality of life depend on the disability status and clinical course in RRMS

BACKGROUND

Fatigue is a prominent and disabling symptom of multiple sclerosis (MS), impairing quality of life. The disease course of relapsing remitting MS (RRMS) is individual.

OBJECTIVES

We aimed to study the effects of demographic and clinical characteristics, as well as lifestyle risk factors on experienced fatigue and health-related quality of life (HRQoL) among RRMS patients, comparing benign and severe disease types.

METHODS

Altogether 198 Finnish RRMS patients were recruited for this real-life cross-sectional study. Self-reported questionnaires were used to evaluate fatigue and HRQoL by using Fatigue Scale for Motor and Cognitive Functions and 15D health-related quality of life questionnaires. Patients were categorized into subgroups based on the current disability status measured by the Expanded Disability Status Scale (EDSS) cut-off value of 4.5, and by retrospective clinical course divided into benign and aggressive RRMS.

RESULTS

All in all, 73% of the RRMS patients suffered from fatigue. Lower HRQoL had a strong correlation with more prominent fatigue (r = -0.719). Higher EDSS was associated with more prominent fatigue and lower HRQoL in the whole RRMS cohort. Older age at the disease onset was associated with more prominent fatigue and decreased HRQoL in the groups of aggressive RRMS and EDSS > 4.5. In the groups of EDSS ≤ 4.5 and benign RRMS, a higher number of used disease-modifying treatments (DMTs) was associated with more pronounced fatigue and reduced HRQoL. In addition, higher BMI was associated with lower HRQoL in patients with benign RRMS. Side effects (45 %) and lack of efficacy (26 %) were the most common reasons for discontinuing a DMT. Cessation due to side effects was the only reason that was significantly associated with more prominent fatigue and lower HRQoL. Use of nicotine products, gender, or disease duration were not associated with fatigue or HRQoL.

CONCLUSIONS

Individuals with severe RRMS and higher EDSS scores are more prone to experience fatigue and lower HRQoL. In addition, fatigue and lower HRQoL are more commonly observed among RRMS patients with older age at disease onset and in those with multiple DMT switches.

Validation of the Modified Fatigue Impact Scale in patients with systemic lupus erythematosus

INTRODUCTION

Patients with systemic lupus erythematosus (SLE) experience significant fatigue, a debilitating symptom associated with reduced quality of life. There has not yet been agreed on a simple and reliable method for assessing fatigue in SLE.

OBJECTIVES

To investigate the internal consistency, test-retest reliability and construct validity (convergent and discriminant validity) of the Modified Fatigue Impact Scale (MFIS) in patients with SLE. The secondary objective was to investigate the contribution of disease activity and organ damage to fatigue.

METHODS

Fatigue was assessed using the MFIS in 61 patients with SLE. Internal consistency of MFIS was assessed with Cronbach's alpha (α) and Principal Component Analysis. Test-retest reliability was evaluated using the intraclass correlation coefficient (ICC). Construct validity was studied using Spearman's rank correlation (r_s). Associations between MFIS and disease activity and organ damage were estimated with r_s.

RESULTS

Internal consistency of the MFIS was excellent with Cronbach's α = 0.97 (95% confidence interval (CI): 0.96-0.98) for the complete scale. Test-retest reliability was good with ICC = 0.89 (95% CI: 0.78-0.95, p < 0.001). Construct validity was confirmed by Spearman's correlation (VT-SF36: r_s = -0.73, p < 0.001. MH-SF36: r_s = 0.70, p < 0.001). No significant correlation was found between the MFIS and SLEDAI (r_s = 0.03, p = 0.83). There was a moderate correlation between MFIS and SLICC Damage Index (r_s = 0.43, p < 0.001).

CONCLUSION

The present study found the MFIS to be a reliable and valid instrument for assessing fatigue in SLE. Further investigations are needed to clarify if an association between measured fatigue and disease components exists.

Spatial and temporal distribution of the prevalence of unemployment and early retirement in people with multiple sclerosis: A systematic review with meta-analysis

Background

We aimed to summarise the prevalence of unemployment and early retirement among people with MS and analyze data according to a spatio-temporal perspective.

Methods

We undertook a systematic search of PubMed/MEDLINE, Scopus, SciVerse ScienceDirect, and Web of Science. We included any peer-reviewed original article reporting the prevalence of unemployment and early retirement in the working-age population with MS. We excluded articles off-topic, with other study designs, whose study sample were unlikely to be representative of the MS population and in case of unavailability of the full text or essential information. A random-effects meta-analysis was used to measure overall prevalence estimates of unemployment and early retirement. We used meta-regression and subgroup analysis to evaluate potential moderators of prevalence estimates and the leave-one-out method for sensitivity analyses.

Results

Our research identified 153 studies across 29 countries encompassing 188436 subjects with MS. The pooled overall effect size for unemployment and early retirement was 35.6% (95% CI 32.8–38.4; I² = 99.31) and 17.2% (95% CI 14.6–20.2; I² = 99.13), respectively. The prevalence of unemployment varied according to the year of publication (p < 0.001) and there was a statistically significant decrease in the prevalence of unemployment over time (p = 0.042). Regarding early retirement, only seven (31.8%) estimates obtained from studies that were published before 2010 were below the overall effect size in comparison to 27 (60.0%) estimates extracted from data published between 2010 and 2021 (p = 0.039). There was a significant difference in prevalence according to countries (p < 0.001). Psychiatric illness was an important clinical feature responsible for patients leaving the workforce in regions with a high MS prevalence.

Conclusions

Unemployment and early retirement due to MS remain highly prevalent, despite a slight decline in the last decade. The prevalence of unemployment and early retirement varies globally.

Current perspectives on the diagnosis and management of fatigue in multiple sclerosis

INTRODUCTION

Fatigue is a common and debilitating symptom among multiple sclerosis (MS) patients with a prevalence up to 81% and with a considerable impact on quality of life. However, its subjective nature makes it difficult to define and quantify in clinical practice. Research aimed at a more precise definition and knowledge of this construct is thus continuously growing.

AREAS COVERED

This review summarizes the most relevant updates available on PubMed up to July 1^st 2022 regarding: the assessment methods that aim to measure the concept of fatigue (as opposed to fatigability), the possible treatment pathways currently available to clinicians, interconnection with the pathophysiological substrates and with the common comorbidities of MS, such as depression and mood disorders.

EXPERT OPINION

The in-depth study of fatigue can help to better understand its actual impact on MS patients and can stimulate clinicians towards a more valid approach, through a targeted analysis of this symptom. Considering fatigue from a multidimensional perspective allows the use of patient-tailored methods for its identification and subsequent treatment by different professional figures. Better identification of methods and treatment pathways would reduce the extremely negative impact of fatigue on MS patients' quality of life.

Fatigue in multiple sclerosis is associated with socioeconomic factors

OBJECTIVES

Fatigue is one of the leading causes of reduced quality of life and inability to work in people with multiple sclerosis (pwMS). Currently, no treatment effectively ameliorates fatigue. We still know little about what causes fatigue and which factors may contribute to fatigue. Knowledge about socioeconomic factors' role in fatigue might help us recognize strategies for the management of fatigue. Our aim was to explore whether socioeconomic factors are associated with the presence or level of perceived fatigue.

METHODS

This is a cross-sectional study of the MS population in three Norwegian counties. We used the Fatigue Scale for Motor and Cognitive Functions to assess self-reported fatigue, and obtained socioeconomic data from Statistics Norway and questionnaires. To assess self-reported anxiety and depression, we employed the Hospital Anxiety and Depression Scale. Clinical data were gathered from the hospital record system.

RESULTS

The response rate was 64% (1599/2512). Seventy percent of the respondents were female, and the mean age was 52 years. Higher levels of education were associated with lower levels of fatigue. Receiving a disability pension, being divorced and having children were all factors associated with higher levels of fatigue, as were low parental education, low income, current smoking, and autoimmune comorbidities. We found a higher prevalence of anxiety and depression in pwMS with fatigue compared to those without fatigue CONCLUSION: Female sex, high level of disability, anxiety, depression and socioeconomic factors were independently associated with fatigue in contemporary patients with MS. These factors should be considered when devising management strategies.