Fatigue in multiple sclerosis: A UK MS-register based study

Harriet Moore; Krishnan Padmakumari Sivaraman Nair; Kathleen Baster; Rod Middleton; David Paling; Basil Sharrack

doi:10.1016/j.msard.2022.103954

Fatigue in multiple sclerosis: A UK MS-register based study

Mult Scler Relat Disord. 2022 Aug:64:103954. doi: 10.1016/j.msard.2022.103954. Epub 2022 Jun 7.

Authors

Harriet Moore¹, Krishnan Padmakumari Sivaraman Nair², Kathleen Baster³, Rod Middleton⁴, David Paling¹, Basil Sharrack¹

Affiliations

¹ Neurology, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust and The University of Sheffield, Glossop Road, Sheffield S10 2JF, United Kingdom.
² Neurology, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust and The University of Sheffield, Glossop Road, Sheffield S10 2JF, United Kingdom. Electronic address: siva.nair@nhs.net.
³ Statistical Services Unit, The University of Sheffield, United Kingdom.
⁴ Health Data Science, Swansea University, United Kingdom.

PMID: 35716477
DOI: 10.1016/j.msard.2022.103954

Abstract

Background: Fatigue is a widely experienced, incapacitating symptom of MS. It hinders daily functioning and has deleterious effects on quality of life. The UK MS Register is an online registry of over 20,000 participants with MS. The aim of this study was to estimate the prevalence, predictors, and impact of fatigue on people with MS using data from the UKMS register.

Methods: All participants who completed the Fatigue Severity Scale (FSS), WebEDSS, Hospital Anxiety and Depression Scale (HADS) within 28 days of each other were selected from the UK MS Register. Data on age, gender, duration and type of MS, use of disease modifying drugs and comorbidities were obtained from the UKMS register. We categorised people with FSS score of 5 or more as with fatigue and those with scores of 4 or less as without fatigue. Descriptive statistics and logistical and multiple regressions were used to explore predictors of fatigue and the effect of fatigue on mobility (MS Walking Scale), physical and psychological aspects of life (MS Impact Scale) and quality of life (European Quality of Life 5D-3 L).

Results: Amongst the 20,946 participants of the UK MS registry, 4620 completed FSS. Out of these, 775 (mean age= 54.71 years, SD= 10.90; mean duration of MS diagnosis =13.21 years, SD=9.75) had completed the FSS, Web EDSS and Hospital Anxiety and Depression Scale within 28 days of each other. 427 (55.1%) of pwMS had a FSS score >5 consistent with clinical fatigue. Logistic regression analysis showed that depression (p=<0.001), duration of MS (p = 0.017), secondary progressive MS (p = 0.001) and EDSS (p=<0.001) predicted fatigue. FSS scores had a significant negative impact on both psychological (p > 0.001) and physical (p > 0.001) domains of the MS Impact scale, MS walking scale (p = 0.003) and EQoL (p = 0.005).

Conclusions: Fatigue was a common symptom amongst people with MS. Depression, longer duration of MS, secondary progressive MS, and high EDSS predicted fatigue. Fatigue had an adverse effect on physical activities, mobility, psychological wellbeing, and quality of life of people with MS.

Keywords: Depression; Fatigue; Mobility; Multiple sclerosis; Quality of life.

MeSH terms

Comorbidity
Fatigue / diagnosis
Fatigue / epidemiology
Fatigue / etiology
Humans
Middle Aged
Multiple Sclerosis* / complications
Multiple Sclerosis* / diagnosis
Multiple Sclerosis* / epidemiology
Quality of Life
United Kingdom / epidemiology