Is the impact of fatigue related to walking capacity and perceived ability in persons with multiple sclerosis? A multicenter study

Accepted Manuscript Is the impact of fatigue related to walking capacity and perceived ability in persons with multiple sclerosis? A multicenter study

U. Dalgas, M. Langeskov-Christensen, A. Skjerbaek, E. Jensen, I. Baert, A. Romberg, C. Santoyo Medina, B. Gebara, B. Maertens de Noordhout, K. Knuts, F. Béthoux, K. Rasova, D. Severijns, B.M. Bibby, A. Kalron, B. Norman, F. Van Geel, I. Wens, P. Feys PII: DOI: Reference:

S0022-510X(18)30084-4 doi:10.1016/j.jns.2018.02.026 JNS 15794

To appear in:

Journal of the Neurological Sciences

Received date: Revised date: Accepted date:

22 November 2017 16 January 2018 15 February 2018

Please cite this article as: U. Dalgas, M. Langeskov-Christensen, A. Skjerbaek, E. Jensen, I. Baert, A. Romberg, C. Santoyo Medina, B. Gebara, B. Maertens de Noordhout, K. Knuts, F. Béthoux, K. Rasova, D. Severijns, B.M. Bibby, A. Kalron, B. Norman, F. Van Geel, I. Wens, P. Feys , Is the impact of fatigue related to walking capacity and perceived ability in persons with multiple sclerosis? A multicenter study. The address for the corresponding author was captured as affiliation for all authors. Please check if appropriate. Jns(2018), doi:10.1016/j.jns.2018.02.026

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Is the impact of fatigue related to walking capacity and perceived ability in persons with multiple sclerosis? A Multicenter Study 1,

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Dalgas U §, Langeskov-Christensen M , Skjerbaek A , Jensen E , Baert I , Romberg A , Santoyo 5

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Medina C , Gebara B , Maertens de Noordhout B , Knuts K , Béthoux F , Rasova K , Severijns D , 13,14

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, Van Geel F , Wens I and Feys P

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Bibby BM , Kalron A , Norman B

Section of Sport Science, Dep. of Public Health, Aarhus University, Denmark

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The Danish MS Hospitals in Ry and Haslev, Denmark

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REVAL Rehabilitation Research Center, BIOMED Biomedical Research Institute, Faculty of Medicine

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and Life Sciences ,Hasselt University, Diepenbeek Belgium 4.

Masku Neurological Rehabilitation Center, Masku Finland

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Hospital de Dia de Barcelona CEMCat, Spain or MS Center of Catalonia (Cemcat)/Vall Hebron

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University Hospital/ Universitat Autònoma de Barcelona (Spain) National MS Center, Melsbroek, Belgium

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Center Neurologique et de Réadaptation Fonctionelle, Fraiture-en-Condroz, Belgium

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Rehabilitation and MS Center Overpelt, Belgium

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The Mellen Center for Multiple Sclerosis Treatment and Research, the Cleveland Clinic, Cleveland, OH, US

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10. Department of Rehabilitation, Third Faculty of Medicine, Charles University and Faculty Hospital Royal

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Vineyard, Czech Republic

11. Section of Biostatistics, Department of Public Health, Aarhus University, Denmark 12. Department of Physical Therapy, School of Health Professions, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel

13. Department of Health and Care Sciences, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway 14. Department of Physiotherapy, Nordland Hospital Trust, Bodø, Norway. §

Corresponding author; (e) [email protected], (t) +45 40123039

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ABSTRACT Background The relationship between fatigue impact and walking capacity and perceived ability in patients with multiple sclerosis (MS) is inconclusive in the existing literature. A better

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understanding might guide new treatment avenues for fatigue and/or walking capacity in patients with MS.

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Objective

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To investigate the relationship between the subjective impact of fatigue and objective walking capacity as well as subjective walking ability in MS patients.

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Methods

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A cross-sectional multicenter study design was applied. Ambulatory MS patients (n=189, age: 47.6±10.5years; gender: 115/74 women/men; Expanded Disability Status Scale

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(EDSS): 4.1±1.8 [range: 0–6.5]) were tested at 11 sites. Objective tests of walking capacity included short walking tests (Timed 25-Foot Walk (T25FW), 10-Metre Walk Test (10mWT)

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at usual and fastest speed and the timed up and go (TUG)), and long walking tests (2- and 6-Minute Walk Tests (MWT). Subjective walking ability was tested applying the Multiple

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Sclerosis Walking Scale-12 (MSWS-12). Fatigue impact was measured by the selfreported modified fatigue impact scale (MFIS) consisting of a total score (MFIS total) and three subscales (MFIS physical, MFIScognitive and MFISpsychosocial). Uni- and multivariate regression analysis were performed to evaluate the relation between walking and fatigue. Results MFIStotal was negatively related with long (6MWT, r=-0.14, p=0.05) and composite (TUG, r=-0.22, p=0.003) walking measures. MFIS physical showed a significant albeit weak relationship to walking speed in all walking capacity tests (r=-0.22 – -0.33, p<0.0001),

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which persisted in the multivariate linear regression analysis. Subjective walking ability (MSWS-12) was related to MFIS total (r=0.49, p<0.0001), as well as to all other subscales of MFIS (r=0.24 – 0.63, p<0.001), showing stronger relationships than objective measures of walking.

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Conclusions The physical impact of fatigue is weakly related to objective walking capacity, while

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general, physical, cognitive and psychosocial fatigue impact are weakly to moderately

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related to subjective walking ability, when analysed in a large heterogeneous sample of

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MS patients.

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Keywords: fatigue, walking capacity, multiple sclerosis

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INTRODUCTION Multiple sclerosis (MS) fatigue is defined as ‘a lack of physical and/or mental energy that is perceived by the individual or the caregiver to interfere with usual and desired activities’ (1). Fatigue is a frequent symptom perceived persistently or sporadically

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by 75% of all people with MS (PwMS) during a 2-year period (2), while 55% describe it as one of their worst symptoms (3). From a pathophysiologic perspective, MS fatigue is

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multifactorial and complex (4). (5)(5)However, a general expression of MS fatigue is

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typically assessed by self-report questionnaires (such as the Modified Fatigue Impact Scale (MFIS)), that often differentiate perceived impact of fatigue in subdomains related to

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physical, cognitive and psychosocial activities, but does not distinguish between primary

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(i.e. mediated by central processes specific to MS) and secondary fatigue (i.e. consequences of sleep problems, medication, deconditioning, depression or psychological

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problems) (6).

Walking impairments are also highly prevalent in MS and up to 68% of the patients

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experience some degree of ambulatory dysfunction (7). Furthermore, both early and longterm diagnosed PwMS perceive walking as their most valuable bodily function (8). Both

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short and long tests have been used to evaluate walking capacity in MS patients, and currently, the 6-Minute Walk Test (6MWT) is considered the gold standard (9). Despite the similarity in the prevalence of fatigue and walking impairment in MS, it is not clear whether a relationship between these two symptoms exists. In case a relationship does exist, fatigue management and treatment may offer a therapeutic target that can also improve mobility. Interestingly, instant energy levels that are changing along the day are not related to walking capacity (10).

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Many studies (11-19) have reported correlation coefficients between fatigue and walking speed in the MS population. Nevertheless, the findings remain inconclusive. Correlation coefficients scores between fatigue and walking speed included non-significant values (11, 13, 16-18, 20-23), weak to moderate negative correlations (r = -0.10 - -0.53)

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(14, 15, 19, 22-29) and weak to moderate positive correlations (r=0.35-0.59) (12, 13). Additionally, no clear pattern was observed between walking speed and the physical

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fatigue domain in the MS sample (15, 20-23, 25). Several reasons may explain the

tests in people with MS.

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discrepancies between the studies examining the relationship between fatigue and walking First, the majority of studies included a small sample size.

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Second, most of the trials did not differentiate between fatigue subdomains (e.g. physical

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and cognitive subdomains) although no consensus on these subdomains exist. An additional limitation of previous studies involved the statistical analysis, where the majority

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of studies did not account for possible confounding factors such as age or gender. Further, some studies determined fatigue as the dependent variable (13, 17, 24), while others

27, 30).

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classified walking capacity as the dependent variable (11, 12, 14-16, 18, 19, 22, 23, 26,

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Therefore, the purpose of this cross-sectional multi-centre study was to investigate the relationship between subjective impact of fatigue and objective walking capacity (time, distance) as well as subjective walking ability in a large cohort of people with MS. In order to

expand the existing knowledge on this topic, the present study applied a

multidimensional fatigue scale and assessed a battery consisting of both objective functional walking capacity measures and subjective walking ability rating. When needed, walking capacity was considered the dependent variable, although the direction of relationship was not known in advance.

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MATERIALS & METHODS The present data were collected during a multi-center study implemented within the RIMS network (a European Network for best Practice and Research in MS Rehabilitation, www.eurims.org). A detailed description of methodology and study design has been

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reported elsewhere (9) and is only summarized below. Of note, other papers have already been published based on data from the present study (9, 23, 31-33). As such, this report to

secondary analyses

on the

relation between generic fatigue impact

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relates

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questionnaires and subjective and objective walking measures.

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Subjects

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A convenience sample of 189 MS patients was recruited at inpatient and outpatient rehabilitation and research centers in Europe (n=10) and the USA (n=1). Participants were

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offered participation when they attended the MS center (in- and outpatients). Participating sites were: REVAL Rehabilitation Research Center, Hasselt (Belgium; n=30 subjects);

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Rehabilitation and MS Center Overpelt, Overpelt (Belgium; n=10); National MS Center, Melsbroek (Belgium; n=17); Centre Neurologique et de Réadaptation Fonctionelle,

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Fraiture-en-Condroz (Belgium; n=16); Department of Rehabilitation, Third Faculty of Medicine, Charles University and Faculty Hospital Royal Vineyard, Prague (Czech Republic; n=35); MS Centers of Haslev and Ry, Haslev and Ry (Denmark; n=27); WestTallinn Central Hospital, Tallinn (Estonia; n=10); Masku Neurological Rehabilitation Center, Masku (Finland; n=19); Hospital de Dia de Barcelona, Barcelona (Spain; n=15); The Mellen Center for MS Treatment and Research, Cleveland (OH, USA; n=10). The study was conducted in accordance with the declaration of Helsinki and approved by the

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Human Ethics Committee of the leading University of Hasselt as well as by the local ethical committees of participating centers. Included subjects had a definite diagnosis of MS according to the McDonald criteria (34), and preservation of at least some ambulatory function (Expanded Disability Status Scale

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[EDSS] ≤ 6.5, as determined by local neurologists) (35). The subjects had not experienced an exacerbation in the month prior to testing, and had no other medical conditions that

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interfered with walking. All participants gave written informed consent.

Experimental design, outcome measures and procedure

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A cross-sectional multi-center study design was applied. To objectively assess walking

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capacity, both short and long walking tests were used. Short tests consisted of the Timed 25-Foot Walk (T25FW) (36), two formats of the 10-Metre Walk Test (10mWT) (37) and the

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Timed Up and Go (TUG) (38). Long tests consisted of the 2-Minute Walk Test (2MWT) (39) and 6MWT (12), with the 2MWT representing the distance covered after the first 2

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minutes, and thus being an integral part, of the 6MWT. Short tests were randomized by means of pre-ordered sealed envelopes and separated by 1-minute rest intervals.

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Subsequently, the 6MWT was performed after a 5-minute rest period. Subjects were permitted to use habitual assistive devices during testing. All sites utilized the same standardized instruction booklet. The MS Functional Composite guidelines were employed for the T25FW (36). Subjects were instructed ‘to walk at fastest but safe speed’ over a 25-foot (7.62 m) course. A static start was used and timing, by a handheld stopwatch, started when the lead foot crossed the start line and stopped when the lead foot crossed the finish line. The 10mWT was administered twice. Subjects were instructed ‘to walk at usual comfortable speed’ (10mWTu), or ‘at fastest but safe

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speed’(10mWTf) (40). A dynamic start was adopted and time registration occurred over the middle 10 metres of a 14-metre walkway to avoid measuring the acceleration and deceleration phases of gait. Subjects were also instructed to complete the 6MWT ‘at fastest speed, and to cover as much distance as possible’, according to Goldman et al.

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(12). They walked back and forth in a 30-metre hallway turning around cones at each end,

walked per minute and total distance were registered.

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and were notified, without further encouragement, after each minute of the test. Distances

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Subjective walking ability was assessed by the patient-reported MS Walking Scale – 12 (MSWS-12) measuring the impact of MS on walking. The transformed MSWS-12 score

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reflect subjective walking performance as this is a valid and reliable subjective walking

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measure in persons with MS(41). When analysing data, walking was regarded as the dependent variable. Furthermore, fatigue impact was measured by the MFIS(42). Both the

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MFIStotal score and the MFIS physical, MFISpsychosocial, MFIScognitive subscores were used in the analysis. Self-reported outcome measures (MSWS-12 and MFIS) were assessed before

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the walking capacity tests. A MFIS score of ≥38 defines the cut-off for severe MS

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fatigue(6).

Statistical analyses

Walking distances (m) on the long tests were converted to their equivalent walking speeds (m/s), the unit in which short tests are typically expressed. This allow direct c comparisons and were used in all subsequent analyses. Distribution of data was visually checked with box-plots, q-q-plots, histograms and dot-plots, showing that data followed a normal distribution. The main experimental outcomes of this study were the multivariate linear regression analyses using ordinary least squares estimation, evaluating the relationship

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between the impact of fatigue (MFIS total, MFISphysical, MFISpsychosocial and MFIScognitive) and the walking speed according to the gait tests (T25FW, 10mWT, 2MWT, 6MWT and TUG). Potential confounding factors were accounted for including sex, age, weight, and height. Walking measures were considered as the dependent variables. A correlation above 0.90

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was interpreted as very strong, 0.70–0.89 as strong, 0.50–0.69 as moderate, 0.30–0.49 as weak, and less than 0.29 as little, if any, relation(43). Furthermore, to interpret potential

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clinical relevance, the regression coefficients were evaluated. Analyses were performed

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using Stata version 11 (StataCorp LP, Texas, USA) with the level of significance set at

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p≤0.05.

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RESULTS

Table 1 and 2 show patient characteristics and descriptive data on the outcome measures.

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Of note are the broad range of EDSS scores represented and the mix of different disease courses. Also, walking capacity and perceived ability, and fatigue show a great

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heterogeneity in the group. Data from one MFIS questionnaire was incomplete and had to be omitted. Of the remaining 188 patients, a total of 94 patients (50%) had an MFIS score

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equal to or above the cut-off score of 38. Simple linear regression analysis (Model 1) Walking capacity: The simple linear regression analysis (table 3) showed that MFIS total was only associated with the 6MWT and the TUG, explaining 2 and 5%, respectively (see figure 1 and table 3). Although all measures of walking capacity were significantly associated with MFISphysical the r2 values were all under 0.15, indicating little, if any, association (see figure 2). No associations were seen between walking measures and

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MFISpsychosocial and MFIScognitive (with the exception of the TUG that was poorly associated with MFISpsychosocial). Walking ability: The MSWS-12 was significantly associated to both the total and the subscales of the MFIS, showing moderate to weak associations to MFIS physical (r2=0.40)

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and MFIStotal (r2=0.24), respectively (see figure 3).

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Multivariate linear regression analysis (Model 2)

Walking capacity: After adjusting for sex, age, weight and height (tables 4), only the TUG

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showed a weak but significant relationship to the MFIS total score. All walking measures

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were weakly related to MFISphysical. The significant relationship between the TUG and the MFISpsychosocial also remained after adjustment. No other walking measures were

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significantly related to the MFIS psychosocial or the MFIScognitive, though both the 10mWTf and the 10mWTu tended to be. Age was a significant co-variate in all walking measures.

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Walking ability: After adjusting for sex, age, weight and height, MSWS-12 still showed a significant relationship to both the MFIS total and all subscales. Age was a significant co-

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variate in all walking measures.

DISCUSSION

The present study investigated the relationship between walking, assessed simultaneously by diverse capacity tests and a questionnaire, and the self-reported MFIS fatigue questionnaire in a large MS sample covering a broad range of disability (EDSS 1-6.5) and ages (21-70 year). The main finding of the present study was, that self-reported fatigue impact measure do not (MFIS total, MFISpshychosocial, MFIScognitive) or only to a limited extend

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(MFISphysical) explain the variance in walking capacity tests. However, the subjective experience of walking ability limitations (MSWS-12) explains 24 to 40% of the general and physical fatigue impact, respectively.

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Effects on general fatigue A summary of the existing literature (see table 5 in appendix) revealed equivocal results in

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studies that report correlations between fatigue measures and walking speed in patients

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with MS. These discrepancies might be explained by differences in walking tests or the subjective fatigue questionnaires used.

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Only seven studies have applied the MFIS scale and are, therefore, directly comparable to

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the present study. Goldman et al. (12) reported moderate positive correlations between the 6MWT and both MFIS total (r=0.59) and MFIS physical (r=0.66) in 40 MS patients with an EDSS of 0-6.5. This finding differs markedly from the present study where weak negative

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correlations between the 6MWT and both MFIS total (r=-0.14) and MFIS physical (r=-0.30) were

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found. One possible explanation may relate to the time of completion of the MFIS scale. In the Goldman et al. study this was done in-between several 6MWT´s, while it was completed before the 6MWT in the present study. Therefore, in the Goldman et al. study,

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those patients covering the longest distance during the 6MWT may have felt more fatigue impact while filling in the MFIS questionnaire, which, in turn, could have biased the results. In accordance to the present study results, Hebert and Corboy (25) reported a moderate negative correlation between the 6MWT and MFIS physical (r=-0.53) in a small MS-sample (n=17). Furthermore, they found a moderate negative correlation between the 6MWT and MFISpsychosocial (r=-0.51), but no significant relationships with the MFIS tot and MFIScognitive. For the short walking tests, Huisinga et al. (13) also reported a non-significant correlation between the MFIS total and the 10mWT performed at usual speed in patients with an EDSS

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range of 1.5-6.0 (n=32), while Nogueira et al. (27) reported a significant negative correlation between the MFIS total and a 10mWT performed at comfortable speed (r=-0,42) in patients with a mean EDSS of 2.7±2 (n=120). Except for the lower mean EDSS and age in the study by Nogeira et al., no clear differences could be located, explaining the

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discrepancy between our findings and the findings of Nogeira et al.. Kalron et al. (29) observed a significant weak negative correlation (r=-0.34) between MFIS total and

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comfortable walking velocity measured on a treadmill in 124 PwMS. Interestingly, a sub-

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group analysis revealed that this correlation was only significant (r=-0.24) for non-fatigued

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PwMS (MFIS total <38). (11)

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Effects on physical fatigue

When summarising the existing studies, most studies report weak to moderate negative

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correlations between subjective physical fatigue impact and walking measures (15, 20-23, 25). Only the study by Goldman et al. shows a moderate positive correlation (12). Furthermore, most

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However, most of these studies included only small sample sizes.

studies have only evaluated the relationship between fatigue impact and walking as a

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secondary outcome measure. Nonetheless, the univariate regression analysis from the present study confirms the general pattern seen in the literature by showing significant weak to moderate negative correlations between all included walking measures and physical fatigue impact. This contrasts the observed correlations between walking measures and general fatigue. From the multivariate regression analyses it is clear that age is a covariate affecting both general fatigue impact, physical fatigue impact and walking, suggesting that the reported relationship in many existing studies may be biased by age. Additionally, it can be argued that the TUG is not a true walking measure since it

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includes also elements of balance and muscle strength and, therefore, can be regarded as a more composite measure than those assessing straight walking (38). Taken together, there are some evidence supporting the view that the subjective perception of physical fatigue impact, but not the general perception of impact of fatigue,

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show a weak, but significant, negative relationship to walking speed in patients with MS. The underlying pathophysiology contributing to this relationship is unclear but, likely,

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consist of a multitude of different mechanisms, such as altered corticospinal output during

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fatiguing muscular activity, altered functional corticomuscular coherence, higher levels of cortical activation for a given muscle force output, and/or reduced muscle oxidative

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capacity (44).

Objective vs. subjective walking measures

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The present study is one of the first to provide data on the relationship between subjective walking ability and MS fatigue impact. The MSWS-12 was related to the general subjective

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impact of fatigue as well as to all subscales of fatigue, showing a stronger relationship than all objective measures of walking capacity. This may be explained by the fact that the

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MSWS-12 include miscellaneous elements of walking ability, such as concentration and mental efforts that are stronger associated to subjective fatigue compared to objective walking speed and distance. Another explanation could be that the momentary mental/cognitive condition of the participant during the filling of questionnaires influences the answers to the MFIS and MSWS-12 in the same direction, despite both questionnaires asking questions related to the prior two-four week period. However, this is not fully supported by the weak relationship between MFIS cognitive and MSWS-12 (table 3). As such,

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future research linking more complex tasks than straight walking, such as dual tasking (e.g. walking and talking) to fatigue, are warranted.

Direction of causality

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Based on the present cross-sectional study the direction of causality in the observed relationships cannot be elucidated. Moreover, the variation in walking tests that is

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explained by subjective fatigue impact, is very limited. It remains unclear whether physical

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fatigue affects walking, vice versa or whether a bidirectional relationship exist. In the present study walking was regarded as the dependent variable, but conflicting opinions on

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whether walking or fatigue is the dependent variable have been reported. A few

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longitudinal studies have evaluated the direction of causality, but the results are inconsistent Smedal et al. (17) examined whether a 4-week inpatient physiotherapy

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program aiming at improving physical function would also influence fatigue as measured by the FSS. However, they found no relationship between walking and fatigue changes

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following the intervention. Other studies showed improved walking ability without any concomitant reduction in fatigue impact or severity (assessed by MFIS or FSS,

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respectively) following 3-12 weeks of treadmill training or homebased walking exercise (45-48); . In contrast, Dalgas et al. (20, 21) showed that 12 weeks of intensive resistance training improved both walking and severity and impact of fatigue (both MFIS and FSS was assessed), while Dodd et al. (49) found that resistance training reduced fatigue impact (MFIS) without influencing walking. Taken together, the majority of longitudinal studies suggest that interventions improving walking do not necessarily improve the impact of fatigue or fatigue severity. Most studies, however, were small, applying non-clinically

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fatigued patients as well as unidimensional fatigue severity scales not evaluating physical fatigue impact, suggesting that future studies are warranted.

Limitations

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The present study should be viewed in the light of certain limitations. The cross-sectional design does not allow conclusions on the direction of causality. Also, the multicenter

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design implicates multiple assessors, which could have introduced systematic differences

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between centers despite our attempts to standardize all testing procedures. Furthermore, generalizability of our data could be compromised since all participants were enrolled to an

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MS center, and since there are differences in the national code of practice on referral to

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these centers. Also, addition of a fatigue severity scale such as the FSS would have strengthened the design. Finally, the applied questionnaires are not all validated in the

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different languages. However, the MFIS is validated in four different languages (50) and care was taken when translating both the MFIS and the MSWS-12 by using a strict back-

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Conclusions

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forward translation procedure.

Subjective physical fatigue impact is weakly related to objective walking capacity, while general, physical, cognitive and psychosocial fatigue impact are weakly to moderately related to subjective walking ability, when analysed in a large heterogeneous sample of MS patients.

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Figure Legends Figure 1: Simple linear regression, showing the relationship between MFIS total and a) TUG and b) 6MWT. Figure 2: Simple linear regression, showing the relationship between MFIS Physical and a)

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6MWT, b) 2MWT, c) TUG, d) 10mWTf, e) 10mWTu and f) T25FW. Figure 3: Simple linear regression, showing the relationship between MSWS and a)

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MFIStotal and b) MFIS Physical.

ACKNOWLEDGEMENTS

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All data-collecting centers (REVAL Rehabilitation Research Center, Hasselt (Belgium;

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n=30 subjects); Rehabilitation and MS Center Overpelt, Overpelt (Belgium; n=10); National MS Center, Melsbroek (Belgium; n=17); Centre Neurologique et de Réadaptation

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Fonctionelle, Fraiture-en-Condroz (Belgium; n=16); Department of Rehabilitation, Third Faculty of Medicine, Charles University and Faculty Hospital Royal Vineyard (Czech

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Republic; n=35); MS Centers of Haslev and Ry, Haslev and Ry (Denmark; n=27); WestTallinn Central Hospital, Tallinn (Estonia; n=10); Masku Neurological Rehabilitation

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Center, Masku (Finland; n=19); Hospital de Dia de Barcelona, Barcelona (Spain; n=15); The Mellen Center for MS Treatment and Research, Cleveland (OH, USA; n=10)) are thanked for their effort. Heiko Maamâgi is acknowledged for his effort during the datacollection process. Domien Gijbels, who coordinated most of the data collection, is acknowledged for his effort during the study. The Research Foundation Flanders is thanked for their Research Grant to PF, the Belgian Charcot Foundation for Equipment Grants. KR thanks for grant support 260388/SVV/2017 and Progress Q35. Finally, the

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RIMS

network

(www.eurims.org)

is

acknowledged

for facilitating

inter European

consultation and testing.

DISCLOSURES

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UD has received research support, travel grants and/or teaching honorary from Biogen Idec, Merck Serono and Sanofi Aventis and is the principal investigator in a study

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(ACTIMS) sponsored by Biogen Idec. PF has received a honorarium for consulting

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European advisory board meetings of BIOGEN, and project support from NOVARTIS.

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Author contribution:

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Conception or design of the work: PF, AR and UD

Data collection: UD, AS, EJ, AR, CMS, BG, BMdN, KK, FB, KR and PF

Interpretation of data: All

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Data-analysis: UD, MLC, PF, IW, BMB and IB

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Drafting the work and/or revising it: UD, MLC, IB, IW and PF Final approval of the version to be published: All

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Agreement to be accountable for all aspects of the work: All

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Reference list

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1. Multiple Sclerosis Council for Clinical Practice Guidelines. Fatigue and multiple sclerosis: evidence-based management strategies for fatigue in multiple sclerosis. Paralyzed Veterans of America. 1998:1-33. 2. Lerdal A, Celius EG, Krupp L, Dahl AA. A prospective study of patterns of fatigue in multiple sclerosis. Eur J Neurol. 2007;14(12):1338-43. 3. Fisk JD, Pontefract A, Ritvo PG, Archibald CJ, Murray TJ. The impact of fatigue on patients with multiple sclerosis. Can J Neurol Sci. 1994;21(1):9-14. 4. MacAllister WS, Krupp LB. Multiple sclerosis-related fatigue. Phys Med Rehabil Clin N Am. 2005;16(2):483-502. 5. Kos D, Kerckhofs E, Nagels G, D'Hooghe M B, Ilsbroukx S. Origin of fatigue in multiple sclerosis: review of the literature. Neurorehabil Neural Repair. 2008;22(1):91-100. 6. Flachenecker P, Kumpfel T, Kallmann B, Gottschalk M, Grauer O, Rieckmann P, et al. Fatigue in multiple sclerosis: a comparison of different rating scales and correlation to clinical parameters. Mult Scler. 2002;8(6):523-6. 7. Hobart J, Lamping D, Fitzpatrick R, Riazi A, Thompson A. The Multiple Sclerosis Impact Scale (MSIS-29): a new patient-based outcome measure. Brain. 2001;124(Pt 5):962-73. 8. Heesen C, Bohm J, Reich C, Kasper J, Goebel M, Gold SM. Patient perception of bodily functions in multiple sclerosis: gait and visual function are the most valuable. Mult Scler. 2008;14(7):988-91. 9. Gijbels D, Dalgas U, Romberg A, de G, V, Bethoux F, Vaney C, et al. Which walking capacity tests to use in multiple sclerosis? A multicentre study providing the basis for a core set. Mult Scler. 2012;18(3):364-71. 10. Feys P, Gijbels D, Romberg A, Santoyo C, Gebara B, Maertens de NB, et al. Effect of time of day on walking capacity and self-reported fatigue in persons with multiple sclerosis: a multi-center trial. Mult Scler. 2012;18(3):351-7. 11. Chetta A, Rampello A, Marangio E, Merlini S, Dazzi F, Aiello M, et al. Cardiorespiratory response to walk in multiple sclerosis patients. Respir Med. 2004;98(6):522-9. 12. Goldman MD, Marrie RA, Cohen JA. Evaluation of the six-minute walk in multiple sclerosis subjects and healthy controls. Mult Scler. 2008;14(3):383-90. 13. Huisinga JM, Filipi ML, Schmid KK, Stergiou N. Is there a relationship between fatigue questionnaires and gait mechanics in persons with multiple sclerosis? Arch Phys Med Rehabil. 2011;92(10):1594-601. 14. Motl RW, Balantrapu S, Pilutti L, Dlugonski D, Suh Y, Sandroff BM, et al. Symptomatic correlates of six-minute walk performance in persons with multiple sclerosis. Eur J Phys Rehabil Med. 2012. 15. Sacco R, Bussman R, Oesch P, Kesselring J, Beer S. Assessment of gait parameters and fatigue in MS patients during inpatient rehabilitation: a pilot trial. J Neurol. 2011;258(5):88994. 16. Savci S, Inal-Inc, Arikan H, Guclu-Gunduz A, Cetisli-Korkmaz N, Armutlu K, et al. Six-minute walk distance as a measure of functional exercise capacity in multiple sclerosis. Disabil Rehabil. 2005;27(22):1365-71. 17. Smedal T, Beiske AG, Glad SB, Myhr KM, Aarseth JH, Svensson E, et al. Fatigue in multiple sclerosis: associations with health-related quality of life and physical performance. Eur J Neurol. 2011;18(1):114-20.

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18. Wetzel JL, Fry DK, Pfalzer LA. Six-minute walk test for persons with mild or moderate disability from multiple sclerosis: performance and explanatory factors. Physiother Can. 2011;63(2):166-80. 19. Motl RW, Sandroff BM, Suh Y, Sosnoff JJ. Energy Cost of Walking and Its Association With Gait Parameters, Daily Activity, and Fatigue in Persons With Mild Multiple Sclerosis. Neurorehabil Neural Repair. 2012. 20. Dalgas U, Stenager E, Jakobsen J, Petersen T, Hansen H, Knudsen C, et al. Resistance training improves muscle strength and functional capacity in multiple sclerosis. Neurology. 2009;73:1478-84. 21. Dalgas U, Stenager E, Jakobsen J, Petersen T, Hansen H, Knudsen C, et al. Fatigue, mood and quality of life improve in MS patients after progressive resistance training. Mult Scler. 2010;16(4):480-90. 22. Andreasen A, Jakobsen J, Petersen T, Andersen H. Fatigued patients with multiple sclerosis have impaired central muscle activation. Mult Scler. 2009;15(7):818-27. 23. Dalgas U, Kjolhede T, Gijbels D, Romberg A, Santoyo C, Noordhout BM, et al. Aerobic intensity and pacing pattern during the six-minute walk-test in patients with multiple sclerosis. J Rehabil Med. 2014. 24. Kempen JC, de G, V, Knol DL, Lankhorst GJ, Beckerman H. Self-reported fatigue and energy cost during walking are not related in patients with multiple sclerosis. Arch Phys Med Rehabil. 2012;93(5):889-95. 25. Hebert JR, Corboy JR. The association between multiple sclerosis-related fatigue and balance as a function of central sensory integration. Gait Posture. 2013;38(1):37-42. 26. Burschka JM, Keune PM, Menge U, Hofstadt-van OU, Oschmann P, Hoos O. An exploration of impaired walking dynamics and fatigue in multiple sclerosis. BMC Neurol. 2012;12:161. 27. Nogueira LA, Dos Santos LT, Sabino PG, Alvarenga RM, Santos Thuler LC. Factors for lower walking speed in persons with multiple sclerosis. Mult Scler Int. 2013;2013:875648. 28. Sandroff BM, Klaren RE, Pilutti LA, Motl RW. Oxygen cost of walking in persons with multiple sclerosis: disability matters, but why? Mult Scler Int. 2014;2014:162765. 29. Kalron A. Association between perceived fatigue and gait parameters measured by an instrumented treadmill in people with multiple sclerosis: a cross-sectional study. J Neuroeng Rehabil. 2015;12(1):34. 30. Franceschini M, Rampello A, Bovolenta F, Aiello M, Tzani P, Chetta A. Cost of walking, exertional dyspnoea and fatigue in individuals with multiple sclerosis not requiring assistive devices. J Rehabil Med. 2010;42(8):719-23. 31. Feys P, Bibby B, Romberg A, Santoyo C, Gebara B, de Noordhout BM, et al. Withinday variability on short and long walking tests in persons with multiple sclerosis. J Neurol Sci. 2014. 32. Feys P, Bibby BM, Baert I, Dalgas U. Walking capacity and ability are more impaired in progressive compared to relapsing type of multiple sclerosis. Eur J Phys Rehabil Med. 2014. 33. Langeskov-Christensen D, Feys P, Baert I, Riemenschneider M, Stenager E, Dalgas U. Performed and perceived walking ability in relation to the Expanded Disability Status Scale in persons with multiple sclerosis. J Neurol Sci. 2017;382:131-6. 34. McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, Lublin FD, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol. 2001;50(1):121-7. 35. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33(11):1444-52.

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36. Cutter GR, Baier ML, Rudick RA, Cookfair DL, Fischer JS, Petkau J, et al. Development of a multiple sclerosis functional composite as a clinical trial outcome measure. Brain. 1999;122 ( Pt 5):871-82. 37. Paltamaa J, West H, Sarasoja T, Wikstrom J, Malkia E. Reliability of physical functioning measures in ambulatory subjects with MS. Physiother Res Int. 2005;10(2):93-109. 38. Podsiadlo D, Richardson S. The timed "Up & Go": a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991;39(2):142-8. 39. Gijbels D, Eijnde BO, Feys P. Comparison of the 2- and 6-minute walk test in multiple sclerosis. Mult Scler. 2011;17(10):1269-72. 40. Graham JE, Ostir GV, Fisher SR, Ottenbacher KJ. Assessing walking speed in clinical research: a systematic review. J Eval Clin Pract. 2008;14(4):552-62. 41. Hobart JC, Riazi A, Lamping DL, Fitzpatrick R, Thompson AJ. Measuring the impact of MS on walking ability: the 12-Item MS Walking Scale (MSWS-12). Neurology. 2003;60(1):316. 42. Multiple Sclerosis Council for Clinical Practice Guidelines. Fatigue and multiple sclerosis: evidence-based management strategies for fatigue in multiple sclerosis. Washington, DC: Paralyzed Veterans of America; 1998. 43. McDowell I. Measuring health: a guide to rating scales and questionnaires. 3rd ed. New York: Oxford University Press; 2006. 44. Dawes H, Collett J, Meaney A, Duda J, Sackley C, Wade D, et al. Delayed recovery of leg fatigue symptoms following a maximal exercise session in people with multiple sclerosis. Neurorehabil Neural Repair. 2014;28(2):139-48. 45. Newman MA, Dawes H, van den BM, Wade DT, Burridge J, Izadi H. Can aerobic treadmill training reduce the effort of walking and fatigue in people with multiple sclerosis: a pilot study. Mult Scler. 2007;13(1):113-9. 46. Kileff J, Ashburn A. A pilot study of the effect of aerobic exercise on people with moderate disability multiple sclerosis. Clin Rehabil. 2005;19(2):165-9. 47. Geddes EL, Costello E, Raivel K, Wilson R. The effects of a twelve-week home walking program on cardiovascular parameters and fatigue perception of individuals with multiple sclerosis: a pilot study. Cardiopulm Phys Ther J. 2009;20(1):5-12. 48. Dettmers C, Sulzmann M, Ruchay-Plossl A, Gutler R, Vieten M. Endurance exercise improves walking distance in MS patients with fatigue. Acta Neurol Scand. 2009. 49. Dodd K, Taylor N, Shields N, Prasad D, McDonald E, Gillon A. Progressive resistance training did not improve walking but can improve muscle performance, quality of life and fatigue in adults with multiple sclerosis: a randomized controlled trial. Mult Scler. 2011;17(11):1362-74. 50. Kos D, Kerckhofs E, Carrea I, Verza R, Ramos M, Jansa J. Evaluation of the Modified Fatigue Impact Scale in four different European countries. Mult Scler. 2005;11(1):76-80.

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Table 1: Patient characteristics of the total sample (n=189) Mean 47.6±10.5 170.0±8.6 73.3±16.2 74/115 101/63/25 4.1±1.8 11.3±7.8 59/130

Range (21-70) (153-196) (40-127)

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Variable Age (years) Height (cm) Weight (kg) Sex (men/women) Type of MS (RR, SP, PP) EDSS (a.u.) Time since diagnosis (years) Self-reported habitual use of walking aid (y/n)

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Values are mean ± SD (range), or number of subjects. PP: primary progressive; RR: relapsing–remitting; SP: secondary progressive. a.u.: Arbitrary unit

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Table 2: Fatigue and walking measures for the total sample Distance, time or fatigue score

Range

Velocity (m/s)

Range

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Long walking tests 6MWT (m) 386±158 (28-702) 1.07±0.44 (0.08±1.95) 2MWT (m) 134±53 (14-240) 1.12±0.44 (0.12-2.0) Short walking tests TUG (s) 12.2±9.4 (4.1-70.6) 0.67±0.31 (0.08-1.46) T25FW (s) 8.2±8.1 (3.2-82.1) 1.25±0.51 (0.12-2.38) 10mWTf (s) 9.2±6.9 (3.7-53.4) 1.38±0.52 (0.14-2.70) 10mWTu (s) 11.5±8.1 (4.5-67.1) 1.07±0.39 (0.13-2.22) Subjective walking MSWStransformed 52.7±27.6 (0-97.9) N/A N/A Fatigue* MFIStotal 38.7±16.5 (2-78) N/A N/A MFISphysical 19.0±8.0 (0-35) N/A N/A MFISpsychosocial 3.5±2.2 (0-8) N/A N/A MFIScognitive 16.2±8.8 (0-35) N/A N/A Values are mean ± SD and range, n=189. N/A: Not applicable; T25FW: Timed 25 foot walk; 10mWTf: 10 meter walk test at fastest speed; 10mWTu: 10 meter walk test at usual speed; TUG: Timed up and go, 2MWT: 2 minute walk test; 6MWT: 6 minute walk test; MFIS: modified fatigue impact scale. *n=188

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Table 3: Coefficients from the simple unadjusted regression analysis (model 1) on MFIS total, MFISphysical, MFISpsychosocial and MFIScognitive MFIStotal Coef f icient R2

p-value

(sem)

MFISphysical Coef f icient R2

p-value

(sem)

MFISpsychosocial Coef f icient R2 p-value (sem)

Coef f icient

MFIScognitive R2 p-

(sem)

value

-0.004 (0.002)

0.02

0.050*

-0.02 (0.004)

0.09

<0.0001*

-0.03 (0.02)

0.02

0.055

0.002 (0.004)

0.001

0.60

2MWT

-0.004 (0.002)

0.02

0.066

-0.02 (0.004)

0.09

<0.0001*

-0.03 (0.02)

0.02

0.073

0.002 (0.004)

0.002

0.57

10mWTf

-0.003 (0.002)

0.01

0.23

-0.02 (0.005)

0.07

0.0004*

-0.02 (0.02)

0.008

0.24

0.005 (0.004)

0.008

0.22

10mWTu

-0.002 (0.002)

0.007

0.26

-0.01 (0.003)

0.06

0.001*

-0.02 (0.01)

0.007

0.25

0.004 (0.003)

0.009

0.21

T25FW

-0.003 (0.002)

0.01

0.21

-0.02 (0.004)

0.05

0.001*

-0.03 (0.02)

0.13

0.004 (0.004)

0.005

0.34

TUG

-0.004 (0.001)

0.05

0.003*

-0.01 (0.003)

0.11

<0.0001*

MSWS

0.8 (0.1)

0.24

<0.0001*

2.2 (0.2)

0.40

<0.0001*

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0.01

-0.03 (0.01)

0.03

0.01*

-0.002 (0.003)

0.004

0.41

5.4 (0.8)

0.19

<0.0001*

0.8 (0.2)

0.06

0.001*

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Table 4: Coefficients from the multivariate regression analysis adjusting for sex, age, weight and height (model 2) on MFIStotal, MFISphysical, MFISpsychosocial and MFIScognitive MFIStotal Coef f icient (sem)

p-value

MFISphysical Coef f icient (sem) p-value

MFISpsychosocial Coef f icient (sem) pvalue

MFIScognitive Coef f icient (sem)

p-value

-0.003 (0.002) 0.02 (0.09) -0.01 (0.003) 0.001 (0.002) -0.001 (0.005)

0.20 0.85 <0.001* 0.63 0.87

-0.01 (0.004) 0.04 (0.08) -0.01 (0.003) 0.001 (0.002) -0.0001 (0.005)

0.001* 0.63 <0.001* 0.51 0.87

-0.02 (0.01) 0.01 (0.09) -0.01 (0.003) 0.0009 (0.002) -0.001 (0.005)

0.10 0.88 <0.001* 0.66 0.83

0.004 (0.004) -0.002 (0.09) -0.02 (0.003) 0.001 (0.002) -0.0004 (0.005)

0.29 0.98 <0.001* 0.71 0.94

2MWT MFIS Sex Age Weight Height

-0.002 (0.002) 0.04 (0.09) -0.01 (0.003) 0.001 (0.002) -0.0001 (0.005)

0.21 0.64 <0.001* 0.53 0.98

-0.01 (0.004) 0.07 (0.08) -0.01 (0.003) 0.002 (0.002) -0.0002 (0.005)

<0.001* 0.43 <0.001* 0.42 0.97

-0.02 (0.01) 0.04 (0.09) -0.01 (0.003) 0.001 (0.002) -0.0003 (0.004)

0.13 0.67 <0.001* 0.55 0.95

0.004 (0.004) 0.02 (0.09) -0.02 (0.003) 0.001 (0.002) 0.0004 (0.005)

0.28 0.80 <0.001* 0.60 0.94

10mWTf MFIS Sex Age Weight Height

-0.001 (0.002) -0.007 (0.1) -0.01 (0.004) 0.002 (0.002) 0.002 (0.006)

0.63 0.94 <0.001* 0.41 0.71

-0.01 (0.005) 0.01 (0.1) -0.01 (0.004) 0.002 (0.002) 0.002 (0.006)

<0.004* 0.88 <0.001* 0.34 0.79

-0.01 (0.02) -0.007 (0.1) -0.01 (0.004) 0.002 (0.002) 0.002 (0.006)

0.39 0.94 <0.001* 0.42 0.73

0.008 (0.004) -0.03 (0.1) -0.02 (0.004) 0.002 (0.002) 0.003 (0.006)

0.054 0.80 <0.001* 0.46 0.64

10mWTu MFIS Sex Age Weight Height

-0.001 (0.002) 0.02 (0.08) -0.01 (0.003) 0.001 (0.002) 0.002 (0.004)

0.63 0.74 <0.001* 0.57 0.69

-0.01 (0.003) 0.04 (0.07) -0.01 (0.002) 0.001 (0.002) 0.001 (0.004)

0.005* 0.58 <0.001* 0.48 0.76

-0.01 (0.01) 0.02 (0.08) -0.01 (0.003) 0.001 (0.002) 0.002 (0.004)

0.36 0.74 <0.001* 0.58 0.72

0.006 (0.003) 0.01 (0.003) -0.01 (0.003) 0.0009 (0.002) 0.002 (0.004)

0.06 0.88 <0.001* 0.62 0.62

T25FW MFIS Sex Age Weight Height

-0.001 (0.002) 0.02 (0.1) -0.02 (0.003) 0.003 (0.002) 0.001 (0.006)

0.56 0.86 <0.001* 0.27 0.93

-0.01 (0.004) 0.03 (0.09) -0.01 (0.003) 0.002 (0.002) -0.00002 (0.01)

0.009* 0.71 <0.001* 0.22 0.99

-0.02 (0.02) 0.02 (0.1) -0.02 (0.003) 0.003 (0.002) 0.0002 (0.006)

0.20 0.86 <0.001* 0.28 0.98

0.007 (0.004) 0.0007 (0.1) -0.02 (0.003) 0.002 (0.002) 0.001 (0.006)

0.11 0.99 <0.001* 0.31 0.86

TUG MFIS Sex Age Weight Height

-0.003 (0.001) -0.02 (0.06) -0.01 (0.001) -0.0001 (0.001) 00001 (0.003)

0.03* 0.71 <0.001* 0.96 0.98

-0.01 (0.003) -0.01 (0.05) -0.01 (0.002) 0.00007 (0.001) -0.0001 (0.003)

<0.001* 0.83 <0.001* 0.96 0.97

-0.02 (0.009) -0.03 (0.06) -0.01 (0.002) -0.0002 (0.001) -0.00007 (0.003)

0.02* 0.65 <0.001* 0.89 0.98

MSWS MFIS Sex Age Weight Height

0.7 (0.1) 6.8 (4.6) 0.8 (0.2) -0.04 (0.1) 0.4 (0.3)

2.0 (0.2) 5.8 (4.1) 0.7 (0.1) -0.06 (0.1) 0.4 (0.2)

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<0.001* 0.14 <0.001* 0.73 0.18

<0.001* 0.16 <0.001* 0.57 0.11

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6MWT MFIS Sex Age Weight Height

5.2 (0.8) 8.3 (4.7) 0.9 (0.2) -0.006 (0.1) 0.4 (0.3)

<0.001* 0.08 <0.001* 0.96 0.16

-0.00009 (0.002) -0.03 (0.06) -0.01 (0.002) -0.0002 (0.001) 0.0004 (0.003)

0.6 (0.2) 8.7 (5.1) 0.9 (0.2) -0.02 (0.1) 0.3 (0.3)

0.97 0.58 <0.001* 0.89 0.90

0.005* 0.09 <0.001* 0.88 0.32

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Highlights  Impaired walking and/or fatigue are prevalent in about 2/3 of all persons with multiple sclerosis but it is not clear how they are related.  General fatigue impact is not related to most walking outcomes.  The physical impact of fatigue is weakly related to objective walking capacity, while general, physical, cognitive and psychosocial fatigue impact are weakly to moderately related to subjective walking ability, when analysed in a large heterogeneous sample of MS patients.