Multiple Sclerosis Resource Centre

Welcome to the Multiple Sclerosis Resource Centre. This website is intended for international healthcare professionals with an interest in Multiple Sclerosis. By clicking the link below you are declaring and confirming that you are a healthcare professional

You are here

Relationship between muscle strength parameters and functional capacity in persons with mild to moderate degree multiple sclerosis

Multiple Sclerosis and Related Disorders, In Press, Accepted Manuscript, Available online 12 January 2015

Abstract

Background

Maximal muscle strength has been shown to be an important predictor of functional capacity for persons with multiple sclerosis (PwMS). Another muscle strength parameter known to be important for functional capacity in other patient groups is rate of force development (RFD) in knee extensors and flexors. This has not been investigated for PwMS. Thus, the purpose of this study was to investigate the relationship between RFD and maximal muscle strength of knee extensors and flexors and measures of functional capacity in PwMS.

Methods

35 PwMS (Expanded Disability Status Scale 2–4) underwent isokinetic dynamometry to determine RFD and maximal isometric and isokinetic muscle strength for both legs. Furthermore all participants performed timed 25 foot walk tests (T25FWT), two minute walk tests (2MWT), stairclimb tests and 5-time sit-to-stand (5STS) tests to determine functional capacity. Multiple linear regressions were performed to determine which muscle strength parameter would serve as a stronger predictor of walking performance.

Results

Both RFD and maximal muscle strength correlated with functional capacity. Correlations were strongest for knee extensors and flexors of the weaker leg, while no clear ranking of the influence of the knee extensors vs. flexors on walking was evident. Multiple linear regressions showed that maximal isokinetic strength of the weaker leg is a better predictor for T25FWT and 2MWT performance than RFD.

Conclusions

Maximal muscle strength of the weaker leg is the better predictor of walking performance in persons with mild to moderate multiple sclerosis. RFD, although also important for functional capacity, is a less strong predictor. Maximal strength of the knee extensors, rather than the knee flexors, predicted performance in the stairclimb and 5STS tests.

Highlights

 

  • Maximal muscle strength of the weaker leg predicts walking performance.
  • Knee extensor, rather than flexor, predict stairclimb and chair rise performance.
  • No clear preferences for predictive value of knee extensors or flexors were evident.
  • Maximal muscle strength is a superior predictor compared to rate of development.

Keywords: Multiple sclerosis, Muscle strength, Walking speed, Climbing, Sit-to-stand.

1. Introduction

Multiple sclerosis (MS) is a chronic, progressive, auto-immune, and neurodegenerative disease of the central nervous system ( Compston and Coles, 2008 ), with unknown aetiology ( Kantarci, 2008 ). A common symptom of MS is reduced functional capacity ( Savci et al., 2005 ), which manifests itself as reduced walking speed/distance and impaired ability to perform activities of daily living (ADL). For persons with MS (PwMS) walking is perceived as the most important bodily function ( Heesen et al., 2008 ) and walking speed/distance is a significant predictor of perceived difficulties or independence ( Paltamaa et al., 2007 ). Compared to healthy control subjects, many PwMS walk slower in short (Morris et al, 2002 and Thoumie and Mevellec, 2002) and long (Savci et al, 2005 and Schwid et al, 1999) walking tests, when applying both preferred/comfortable (Morris et al, 2002 and Schwid et al, 1999) and maximal walking speed (Savci et al, 2005 and Thoumie and Mevellec, 2002). Furthermore, many PwMS self-report impaired walking capacity ( Larocca, 2011 ) and show progressively reduced walking speed as the disease progresses ( Kempen et al., 2011 ) due to increased spasticity and other indicators of impaired motor control ( Bethoux, 2013 ). PwMS also self-report difficulties in other ADL such as stair case climbing and getting out of a chair (68% and 18% report problems, respectively) ( Larocca, 2011 ). Consequently, it is important to identify and understand modifiable predictors of walking and other ADL, to optimise rehabilitating interventions.

A well-known predictor of walking is lower-body muscle strength which is often impaired in MS patients ( Schwid et al., 1999 ). Also rate of force development (RFD) ( Chen et al., 1987 ) is impaired in PwMS. RFD is another muscle strength parameter that correlate to functional activities such as walking for healthy elderly people ( Holviala et al., 2014 ) and also relate to balance and falls ( Aagaard et al., 2007 ). Moreover, other parameters related to walking performance in PwMS, comprise knee joint muscle strength (Thoumie and Mevellec, 2002, Thoumie et al, 2005, Broekmans et al, 2013, and Yahia et al, 2011), knee joint muscle strength asymmetry ( Sandroff et al., 2013 ), knee extensor power asymmetry ( Chung et al., 2008 ) and ankle dorsiflexor strength ( Wagner et al., 2014 ) and RFD ( Ng et al., 2004 ). Knee extensor and flexor muscle strength of the weaker leg (Thoumie and Mevellec, 2002, Thoumie et al, 2005, and Broekmans et al, 2013) shows a stronger relation to walking performance than that of the stronger leg, with one study, however, reporting inconsistent results ( Yahia et al., 2011 ). Furthermore, knee flexor muscle strength has been suggested to be better related to walking performance than knee extensor muscle strength (Thoumie and Mevellec, 2002, Thoumie et al, 2005, Broekmans et al, 2013, and Yahia et al, 2011). Until now, however, the existing studies have focused on the relationship between functional capacity and maximal muscle strength rather than RFD, despite RFD being shown as an equally important predictor of functional capacity in other functionally impaired groups ( Holviala et al., 2014 ). Consequently, the relationship between functional capacity and knee extensor and flexor RFD remains to be established in PwMS.

The present study therefore aimed to determine the relationship between functional capacity and knee joint muscle strength parameters in terms of muscle strength and RFD. We hypothesised that knee joint RFD as well as maximal muscle strength would be related to functional capacity. A secondary purpose of the study was to examine if we could reproduce findings from previous studies indicating that knee flexor muscle strength (Thoumie and Mevellec, 2002, Thoumie et al, 2005, Broekmans et al, 2013, and Yahia et al, 2011), and knee joint muscle strength of the weakest leg (Thoumie and Mevellec, 2002, Thoumie et al, 2005, and Broekmans et al, 2013) predict walking performance better than knee extensor muscle strength and knee joint muscle strength of the strongest leg, respectively.

2. Materials and methods

2.1. Subjects

Thirty-five subjects were recruited from the MS Clinic at Aarhus University Hospital and MS Clinic of Southern Jutland. Inclusion criteria were 18–60 years, a definite relapsing-remitting MS diagnosis according to the McDonald criteria ( McDonald et al., 2001 ), Expanded Disability Status Scale (EDSS) 2.0–5.5 (with a ‘pyramidal functions’ subscore ≥2), interferon-based medicine (Avonex, Rebif, Betaferon and Extavia). Exclusion criteria were; co-morbidities preventing participation (cardiovascular disease, metabolic diseases etc.), pregnancy, relapse eight weeks prior to inclusion, systematic resistance training three months prior to inclusion. All participants gave written informed consent, which was approved by the ethics committee of Region Midtjylland (M-20110178) in accordance with the Declaration of Helsinki. The data of the present study is baseline data from a clinical trial designed to investigate the underlying mechanisms possibly explaining the beneficial effects of progressive resistance training for PwMS (ClinicalTrials.gov ID: NCT01518660).

2.2. Demographic measures

EDSS was assessed by trained neurologists. Height was measured and weight was determined using a body composition analyser (Tanita SC220, Tanita, IL, USA). In addition to this, the 12-item MS Walking Scale (MSWS-12) ( Hobart et al., 2003 ) was completed.

2.3. Isokinetic dynamometry

2.3.1. Protocol

Subjects were seated in an isokinetic dynamometer (Humac Norm, CSMi, Stoughton, MA, USA) with a hip angle of 90°. Restraining straps were positioned across the torso, while the arms were crossed over the chest, and the non-working leg was positioned behind a stabilizing bar. The rotational axis of the dynamometer was aligned with the transverse knee-joint axis of the working leg and attached to the lower leg by a length adjustable lever arm three cm proximal to malleolus medialis. After a standardized instruction (to contract as strongly and fast as possible) and two familiarisation attempts, the subjects performed three to five (depending on the consistency of the first trials) isometric maximal voluntary contractions (MVC) for the knee extensors and flexors at a knee angle of 70° and 20°, respectively. The subjects received visual feedback and verbal encouragement during the maximal contractions. Subsequently, two familiarisation trials preceded three to five concentric contractions for both knee extensors and flexors at 60°/s with a range of motion of approximately 100°. All contractions were separated by at least 30 s of rest. Testing of both legs was performed, and the attempt having the highest peak torque for each contraction mode was used for further analysis. Categorisation of stronger and weaker leg was based on the peak torque measurement for each subject individually.

2.3.2. Analysis

All isometric strength data were sampled and exported using TeleMyo Direct Transmission System and MyoResearch Software (Noraxon USA, Scottsdale, AZ, USA). A sampling frequency of 1500 Hz was applied and the final analyses were performed using custom-made software. All torque data were filtered using a Butterworth lowpass filter with a cut-off frequency of 6 Hz, and gravity corrected by subtracting the torque generated by the lower limb based on resting conditions 0.5 s before onset of contraction. Contraction onset was defined as an increase in torque above 7.5 Nm ( Aagaard et al., 2002 ). MVC was defined as the peak torque measurement. Maximal RFD (RFDmax) was defined as the steepest slope between onset and MVC averaged over 10 consecutive samples (6.67 ms). In addition RFD was determined as the average slope from 0 to 200 ms after onset of contraction (RFD@200 ms) ( Aagaard et al., 2002 ).

The isokinetic data were exported from the dynamometer software, and peak torque during knee extension and knee flexion was extracted for both legs. To normalize data, all strength measurements were scaled to body-weight (Aagaard et al, 2007 and Jaric, 2003).

2.4. Functional tests

Walking performance was measured as both a short and a long walking test. The short walking test was the timed 25 foot walk test (T25FWT) ( Rudick et al., 2002 ), executed with a static start where the subjects were instructed to walk as fast as possible on a 25 foot track marked by two cones. Time to walk the distance was measured by the assessor using a handheld electronic stopwatch. The test was performed twice, and the best trial was used for further analyses. The long walking test was the two-minute walk test (2MWT) as recommended by Gijbels et al. (2012) . The subjects were instructed to walk as far as possible for two minutes back and forth a 30 m track marked by cones at each end. Subjects were informed when 60, 30 and 10 s remained, and there was a countdown from 3 s until the subjects were stopped and total distance was measured.

The 5-time sit-to-stand test (5STS) was performed twice after standardized instructions and a demonstration in accordance with Moller et al. (2012) . Performance was timed by the assessor using a handheld electronic stopwatch, and the best trial was used for further analyses.

An ascending stair climb test was performed twice, and the best trial was used for further analyses. Subjects were instructed to ascend 22 steps (17 cm height, 29 cm depth) with a 180° separating swing half-way as fast as possible, taking one step at a time without using the rail.

2.5. Statistical analysis

One subject was excluded from all analysis because of inability to perform the isokinetic muscle testing. This left 34 subjects for the final analyses.

All variables were tested for normal distribution by visual inspection of histograms and QQ-plots. After testing for equal variance, a paired Student׳st-test was applied to check for difference in muscle strength parameters between the stronger and weaker leg. Visual inspection of linear relationship was conducted prior to calculating Pearson correlation coefficients between functional performance and muscle strength variables. To compare correlations between walking performance and (1) weakest vs. strongest leg, (2) knee extensor vs. flexor, (3) Isokinetic peak torque vs. MVC, (4) RFDmax vs. RFD@200 ms Pitman׳s test was applied. Pitman׳s test calculates the correlation between the sum and the difference of the residuals from two linear regressions. Using the maximal strength and RFD variable strongest correlated with walking performance, multiple linear regressions including these were performed to determine which one, if any, is the better predictor of walking performance. The multiple linear regressions included age and height as covariates.

All statistical analyses were performed using Stata (Version 11.0, StataCorp, TX, USA). The level of statistical significance was set top≤0.05.

3. Results

3.1. Subject characteristics, functional capacity and muscle strength

Patient characteristics and baseline data are presented in Table 1 . Table 2 presents maximal strength and RFD in knee extensors and flexors for both the strongest and weakest leg. For all strength and RFD parameters the strongest leg was higher than the weakest leg.

Table 1 Patient characteristics and functional performance.

  Mean±SD Range
Characteristics
Age (years) 43.3±8.2 25–58
Height (cm) 170.3±8.6 156–191
Weight (kg) 75.6±12.6 55–101
Gender F/M (n) 26/8
EDSS (a.u.) 2.9±0.7 2–4
 
Functional performance
T25FWT (m/s) 1.72±0.31 1.13–2.38
2MWT (m/s) 1.64±0.33 1.09–2.80
5STS (s) 9.48±2.70 5.2–16.1
Stairclimb (s) 10.64±3.60 6.5–20.7
MSWS-12 (a.u.) 25.5±10.0 12–55

Abbreviations: a.u.=arbitrary units.

Table 2 Muscle strength measures for stronger vs. weaker leg.

  Knee extensors Knee flexors
Stronger leg Weaker leg p-Value Stronger leg Weaker leg p-Value
Isokinetic peak torque (N m/kg) 1.85±0.41 1.66±0.39 <0.001 0.87±0.25 0.73±0.24 <0.001
MVC (N m/kg) 2.30±0.53 1.99±0.49 <0.001 0.97±0.29 0.81±0.29 <0.001
RFDmax (N m/kg/s) 13.43±3.46 12.65±3.32 0.04 8.42±1.35 8.09±1.38 0.009
RFD@200ms (N m/kg/s) 7.35±2.49 6.56±2.20 0.006 2.98±0.99 2.39±0.92 0.006

Values are presented as Mean±SD.p-Value designates if a difference exists between the stronger vs. weaker leg, as judged by a pairwise two-tailedt-test.

3.2. Correlations between muscle strength parameters and functional performance

Table 3 presents Pearson correlation coefficients between muscle strength measures of both knee extensors and knee flexors from the stronger and weaker leg and functional performance measures and MSWS-12. The T25FWT and 2MWT correlate with all muscle strength parameters of the weaker leg, and most of the parameters from the stronger leg. The 5STS and stairclimb test primarily correlate with maximal muscle strength of the knee extensors of the weaker leg. The MSWS-12 correlates with one of 16 muscle strength measures.

Table 3 Pearson correlation coefficients between maximal muscle strength measures and measures of functional performance.

  Stronger leg Weaker leg
T25FWT 2MWT 5STS Stairclimb MSWS-12 T25FWT 2MWT 5STS Stairclimb MSWS-12
Knee extensors
Isokinetic PT 0.45 lowastlowast 0.45 lowastlowast −0.28 −0.29 −0.13 0.61 lowastlowastlowast 0.65 lowastlowastlowast −0.41 lowast −0.54 lowastlowastlowast −0.28
MVC 0.41 lowast 0.38 lowast −0.24 −0.19 −0.03 0.48 lowastlowast 0.55 lowastlowastlowast −0.35 lowast −0.37 lowast −0.14
RFDmax 0.43 lowast 0.33 −0.25 −0.20 −0.19 0.49 lowast 0.44 lowast −0.25 −0.34 −0.30
RFD@200ms 0.43 lowast 0.33 −0.16 −0.22 −0.24 0.56 lowastlowastlowast 0.55 lowastlowastlowast −0.32 −0.38 lowast −0.33
 
Knee flexors
Isokinetic PT 0.58 lowastlowastlowast 0.57 lowastlowastlowast −0.37 lowast −0.37 lowast −0.31 0.64 lowastlowastlowast 0.65 lowastlowastlowast −0.42 lowast −0.51 lowastlowast −0.26
MVC 0.42 lowast 0.40 lowast −0.27 −0.23 −0.25 0.40 lowast 0.38 lowast −0.22 −0.23 −0.22
RFDmax 0.26 0.21 −0.11 −0.08 −0.11 0.35 lowast 0.34 lowast −0.17 −0.19 −0.10
RFD@200ms 0.42 lowast 0.35 lowast −0.28 −0.27 −0.35 lowast 0.51 lowastlowast 0.54 lowastlowast −0.23 −0.37 lowast −0.25

lowast p<0.05.

lowastlowast p<0.01.

lowastlowastlowast p<0.001.

Values represent Pearson correlation coefficients between the given variables. Asterisks indicate level of significance of correlation.Abbreviations: PT=peak torque.

3.3. Comparing correlations for walking performance and (1) weaker vs. stronger leg, (2) knee extensors vs. flexors, (3) maximal strength vs. RFD

Table 4 presents comparisons of correlations between muscle strength parameters of knee extensors and flexors and walking performance (T25FWT and 2MWT) for the stronger vs. weaker leg. All the comparisons demonstrate stronger correlations for the weaker leg compared to the stronger leg.

Table 4 Pitman test for comparison of correlations between muscle strength measures and walking performance for stronger vs. weaker leg.

  Stronger vs. weaker leg
T25FWT 2MWT
Knee extensors
Isokinetic PT lowastlowastlowast W>S lowastlowastlowast W>S
MVC   lowastlowastlowast W>S
RFDmax   lowast W>S
RFD@200ms lowast W>S lowastlowastlowast W>S
 
Knee flexors
Isokinetic PT    
MVC    
RFDmax lowastlowast W>S lowastlowastlowast W>S
RFD@200ms   lowastlowast W>S

lowast p<0.05.

lowastlowast p<0.01.

lowastlowastlowast p<0.001.

Asterisks indicate level of significance from Pitman test comparing correlations between strongest and weakest leg.Abbreviations: PT=peak torque; W=weaker leg; S=stronger leg.

Table 5 presents comparisons of the correlations between muscle strength measures of the weaker and stronger leg and walking performance for knee extensors vs. flexors. For the stronger leg isokinetic peak torque showed a stronger correlation in the knee flexors. For the weakest leg, however, MVC showed a stronger correlation to the 2MWT for the knee extensors than for the knee flexors. When RFD parameters differed between the muscle groups, the knee extensors showed a stronger correlation to walking performance than knee flexors.

Table 5 Pitman test for comparison of correlations between muscle strength measures and walking performance for knee extensors and knee flexors.

  Knee extensors vs. flexors
T25FWT 2MWT
Strongest leg
Isokinetic PT lowast KF>KE lowast KF>KE
MVC    
RFDmax lowastlowast KE>KF lowastlowast KE>KF a
RFD@200ms    
 
Weakest leg
Isokinetic PT    
MVC   lowastlowast KE>KF
RFDmax lowast KE>KF  
RFD@200ms    

lowast p<0.05.

lowastlowast p<0.01.

a Based on two non-significant correlations.

Asterisks indicate level of significance from Pitman test comparing correlations between knee extensors and flexors.Abbreviations: PT=peak torque; KE=knee extensor; KF=knee flexor.

Pitman tests comparing correlations between walking performance and isokinetic peak torque and MVC were done for the weakest knee extensors and knee flexors. All tests revealed stronger correlations for isokinetic peak torque (p<0.05). Finally, three out of four Pitman tests revealed that RFD@200 ms was stronger correlated (p<0.05) to walking performance than RFDmax in the weakest knee extensors and flexors.

3.4. Multiple linear regressions

Table 6 presents results from the multiple linear regressions between walking performance and both isokinetic peak torque and RFD@200 ms. In three out of four regression models only the coefficients for maximal strength remained significant.

Table 6 Multiple linear regression comparing walking performance for strength and RFD variables for the weaker leg adjusted for age and height.

  T25FWT 2MWT
Coefficient SE p-Value Coefficient SE p-Value
Knee extensors
Isokinetic PT 0.318 0.18 0.085 0.497 0.18 0.012
RFD@200ms 0.033 0.03 0.312 0.031 0.03 0.352
Age −0.005 0.01 0.423 0.000 0.01 0.994
Height −0.001 0.01 0.851 −0.006 0.01 0.355
 
Knee flexors
Isokinetic PT 0.741 0.27 0.010 0.826 0.29 0.008
RFD@200ms 0.007 0.07 0.922 0.036 0.08 0.631
Age −0.010 0.01 0.080 −0.006 0.01 0.278
Height −0.001 0.01 0.898 −0.005 0.01 0.468

Abbreviations: PT=peak torque. SE = standard error.

4. Discussion

The main finding of the present study was that, although significant correlations were found to exist between measures of RFD and walking performance, maximal strength was found to be a better predictor of walking performance than RFD. Our findings confirm, previous reports (Thoumie and Mevellec, 2002, Thoumie et al, 2005, and Broekmans et al, 2013), that muscle strength of the weaker leg comprise the better predictor. Furthermore, we found that knee extensor and knee flexor strength provide equally valid predictors of walking performance. Finally, we observed that the 5STS and Stairclimb tests primarily correlated with the maximal muscle strength parameters of the weaker knee extensors muscles rather than RFD and knee flexor muscle strength parameters. Collectively, our findings elucidate the important role maximal muscle strength may play in the ability to perform ADL for mildly to moderately impaired PwMS.

4.1. Rate of force development and functional performance

The present study expands the current literature regarding RFD and MS. Chen et al. (1987) examined knee-joint RFD in PwMS and control subjects. They found that strength was 43% and 47% lower for PwMS in the knee-extensors and knee-flexors, respectively and that the reduced RFD reflected both decreased maximal torque and prolonged time to develop maximal torque. Ng et al. (2004) examined ankle dorsiflexor RFD of a target submaximal force normalised to the rate of tetanic force generation (tetanic force is peak force produced by a 50-Hz stimulation) in PwMS and healthy control subjects and found that RFD was 21% lower in PwMS. Ankle dorsiflexor RFD correlated with the time to walk 25 feet (r=−0.58). Furthermore, in that study, the authors observed no difference in the rate of tetanic force development (a peripheral measure of muscle function) between PwMS and healthy control subjects, suggesting that the slower RFD of the ankle dorsiflexor muscles in PwMS was the result of central alterations in motor function ( Ng et al., 2004 ). Holviala et al. (2014) reported that a strength training intervention improved walking time and leg extension RFD in otherwise healthy aging women and men. Their results showed that both walking time and dynamic balance correlated with isometric leg extension RFD. Wang et al. (2010) were able to increase leg press strength, RFD and walking performance in patients with peripheral arterial disease with strength training. They suggest that increased RFD leads to longer atonic periods between contractions and enhanced muscle perfusion. Compared to untrained, elderly men (mean age=70.5) ( Aagaard et al., 2007 ) the markedly younger (age=43.3) subjects in this study had almost identical RFD@200 ms values for the strongest knee extensor muscles (7.35 Nm/kg/s vs. 7.23 Nm/kg/s). Since RFD declines with increasing age ( Hakkinen et al., 1995 ), this suggests that the subjects from the present study do not have the same capacity to rapidly develop torque in the knee-joint muscles as their healthy, age-matched peers. Our multiple linear regression analyses shows that when the walking speed of our subjects is explained by maximal dynamic knee joint muscle strength, knee-joint muscle RFD adds no additional significant information to this explanation. However, RFD may still be an important muscle strength parameter in order to maintain or even improve walking performance for PwMS, since it relates to central motor function ( Ng et al., 2004 ). In accordance, increased RFD positively affects the ability to rapidly modulate torque across a joint ( Ng et al., 2004 ) and may improve balance ( Holviala et al., 2014 ) as well as muscle perfusion ( Wang et al., 2010 ).

4.2. Weaker vs. stronger leg

Our current findings as well as those of several previous studies (Thoumie and Mevellec, 2002, Thoumie et al, 2005, and Broekmans et al, 2013) concur with some ( Flansbjer et al., 2006 ), but not all ( Kim and Eng, 2003 ), studies of stroke patients, in the conclusion that muscle strength parameters of the weaker leg provide better predictors of walking performance than those of the stronger leg. In addition to this, knee-joint muscle strength and leg power asymmetry has been correlated to walking performance in PwMS (Sandroff et al, 2013 and Chung et al, 2008). This suggests that for PwMS, knee joint muscle strength parameters of the weaker leg, to a high extent, limits walking performance. It has been suggested that weaker muscle strength in one leg leads to a state of increased muscle fatigue that negatively affects overall endurance ( Flansbjer et al., 2006 ), which may negatively affect walking performance. Unilateral resistance training has led to improved muscle strength in stroke patients (Lee et al, 2010 and Ouellette et al, 2004) and PwMS ( Broekmans et al., 2011 ), but the unilateral training programme applied in a study by Broekmans et al. Broekmans et al. (2011) did not improve performance in functional mobility tests in PwMS. On the contrary, the resistance training regimen applied by Dalgas et al. (2009) , combining bilateral and unilateral lower extremity exercises, improved functional capacity in PwMS. Thus, specific recommendations regarding unilateral resistance training programs primarily focusing on improving strength selectively of the weaker leg cannot be deduced from these longitudinal studies.

4.3. Knee extensors vs. flexors

In line with previous studies (Thoumie and Mevellec, 2002, Thoumie et al, 2005, and Yahia et al, 2011) we observed that isokinetic knee-flexor muscle strength comprised the strongest predictor of walking performance, but we did not observe this pattern in isometric knee-joint muscle strength and RFD. Thoumie et al. (2005) suggest that, for PwMS with a low level of motor command impairment, the decrease in knee flexor strength is the main parameter of gait velocity reduction. Our study of PwMS with relatively mild impairment was not able to clearly support this suggestion. Broekmans et al. (2013) suggested that some of the subjects in their study might have shown poor knee flexion during the swing phase of walking. This may help explain the strong correlations between knee flexor muscle strength and walking performance found in previous studies. A study applying high quality 3D kinematic observations is warranted in order to better determine the importance of both knee flexors and extensors during walking in PwMS.

4.4. Walking speed vs. sit-to-stand and stairclimb

In this study we attempted to correlate muscle strength parameters to functional tests of walking performance, but also other common tasks of daily living, such as the stairclimb test and the 5STS test. Our results from the weaker leg indicate that generally seen only the maximal strength of the knee extensors correlate with the Stairclimb and 5STS tests, whereas neither RFD measures nor knee flexor strength seems to be of importance. Likely, the movements involved in these two tests are less reliant on knee flexor strength.

4.5. Limitations and implications for future research

One limitation of the present study is the relatively small sample size. Additionally, the subjects included in the current investigation only represent a select group of relapsing remitting MS patients with relatively mild impairment (2.0≤EDSS≤4.0) all having impaired pyramidal function. Therefore, our findings may not be extended to other less or more severely impaired PwMS, or other sub-types of the disease. An additional limitation in the present study relates to the lack of measurement of spasticity which is an important aspect of walking disability in MS (Bethoux, 2013 and Sosnoff et al, 2011) and might have influenced of measurements of various muscle strength parameters. The application of a cross-sectional study design limits the ability to interpret cause and effect. Also, the high number of statistical tests applied in this study increases the risk of statistical type 1 errors. Walking performance relies on a synergy of several joints, thus as the present study only provided observations of muscle strength parameters of the knee joint, the results must be carefully interpreted. Future cross-sectional studies should include larger samples of patients with a broad range of ambulatory dysfunctions, and randomized controlled trials should be conducted to determine if increased strength (and perhaps RFD) leads to improved walking performance ( Kjolhede et al., 2012 ). Also muscle strength testing of the ankle and hip joint combined with 3D kinematic measurements could be of interest for future studies. The 6 min walk test (6 MWT) is among the most commonly used long walking test. Yet, we have applied the 2 MWT, although it could be speculated that PwMS who are susceptible to fatigue, might perform poorer in an even longer lasting test. However, a recent multicentre study demonstrated that for both mild and moderate MS groups, corresponding to our population, the 2MWT correlated highly with the 6 MWT (the regression coefficient of 0.95) and that the 2MWT could predict performance in the 6MWT within 5% ( Gijbels et al., 2012 ).

4.6. Clinical implications

The present findings are of relevance for physiotherapists and other experts involved in specialized rehabilitation of PwMS. The results of the current study demonstrate the superior importance of muscle strength compared to RFD of the knee extensors and flexors on walking performance, which is of importance when determining variables of resistance training programs such as intensity. Of particular importance for rehabilitation specialists is the finding, that even for people with relatively mild functional disabilities, the weakest leg constitutes a highly important factor for walking performance. We thus recommend that rehabilitation specialist attempts to identify unilateral deficits early in MS, and attempt to address these deficits in tailored resistance training programs.

5. Conclusions

Both maximal muscle strength and RFD of the knee joint are related to performance in mildly to moderately impaired PwMS. However, when predicting walking performance maximal muscle strength was observed to be superior to RFD. Knee joint muscle strength parameters of the weaker leg seem to predict functional performance better than those of the stronger leg, but no systematic preference for knee extensor vs. knee flexor muscle strength parameters was evident from this study. Lastly, we observed that it was primarily the maximal muscle strength of the weaker knee extensors that correlated with other daily activities such as climbing stairs and rising from a chair.

Conflict of interest and role of funding source

TK has received research support and/or travel grants from Biogen Idec, The Augustinus Foundation and Horse-trader Ole Jacobsens Memorial Grant. ES, TP, UD have received research support and travel grants from Biogen Idec, Merck Serono and Bayer Schering and travel grants from Sanofi Aventis. All authors declare no conflict of interest.

Acknowledgements

Cuno Rasmussen is thanked for his engineering assistance in the development of custom-made software to analyse data from the isokinetic dynamometer. Bo Martin Bibby is thanked for statistical assistance in analysing and interpreting results.

References

  • Aagaard et al., 2002 P. Aagaard, E.B. Simonsen, J.L. Andersen, P. Magnusson, P. Dyhre-Poulsen. Increased rate of force development and neural drive of human skeletal muscle following resistance training. J Appl Physiol. 2002;93:1318-1326
  • Aagaard et al., 2007 P. Aagaard, P.S. Magnusson, B. Larsson, M. Kjaer, P. Krustrup. Mechanical muscle function, morphology, and fiber type in lifelong trained elderly. Med Sci Sports Exerc. 2007;39:1989-1996 Crossref
  • Bethoux, 2013 F. Bethoux. Gait disorders in multiple sclerosis. in: Continuum. 19 (, 2013) 1007-1022 Crossref
  • Broekmans et al., 2011 T. Broekmans, M. Roelants, P. Feys, G. Alders, D. Gijbels, I. Hanssen, et al. Effects of long-term resistance training and simultaneous electro-stimulation on muscle strength and functional mobility in multiple sclerosis. Mult Scler. 2011;17:468-477 Crossref
  • Broekmans et al., 2013 T. Broekmans, D. Gijbels, B.O. Eijnde, G. Alders, I. Lamers, M. Roelants, et al. The relationship between upper leg muscle strength and walking capacity in persons with multiple sclerosis. Mult Scler. 2013;19:112-119 Crossref
  • Chen et al., 1987 W.Y. Chen, F.M. Pierson, C.N. Burnett. Force-time measurements of knee muscle functions of subjects with multiple sclerosis. Phys Ther. 1987;67:934-940
  • Chung et al., 2008 L.H. Chung, J.G. Remelius, R.E. Van Emmerik, J.A. Kent-Braun. Leg power asymmetry and postural control in women with multiple sclerosis. Med Sci Sports Exerc. 2008;40:1717-1724 Crossref
  • Compston and Coles, 2008 A Compston, A. Coles. Multiple sclerosis. Lancet. 2008;372:1502-1517 Crossref
  • Dalgas et al., 2009 U. Dalgas, E. Stenager, J. Jakobsen, T. Petersen, H.J. Hansen, C. Knudsen, et al. Resistance training improves muscle strength and functional capacity in multiple sclerosis. Neurology. 2009;73:1478-1484 Crossref
  • Flansbjer et al., 2006 U.B. Flansbjer, D. Downham, J. Lexell. Knee muscle strength, gait performance, and perceived participation after stroke. Arch Phys Med Rehab. 2006;87:974-980 Crossref
  • Gijbels et al., 2012 D. Gijbels, U. Dalgas, A. Romberg, V. de Groot, F. Bethoux, C. Vaney, et al. Which walking capacity tests to use in multiple sclerosis? A multicentre study providing the basis for a core set. Mult Scler. 2012;18:364-371 Crossref
  • Hakkinen et al., 1995 K. Hakkinen, U.M. Pastinen, R. Karsikas, V. Linnamo. Neuromuscular performance in voluntary bilateral and unilateral contraction and during electrical stimulation in men at different ages. Eur J Appl Physiol Occup Physiol. 1995;70:518-527 Crossref
  • Heesen et al., 2008 C. Heesen, J. Bohm, C. Reich, J. Kasper, M. Goebel, S.M. Gold. Patient perception of bodily functions in multiple sclerosis: gait and visual function are the most valuable. Mult Scler. 2008;14:988-991 Crossref
  • Hobart et al., 2003 J.C. Hobart, A. Riazi, D.L. Lamping, R. Fitzpatrick, A.J. Thompson. Measuring the impact of MS on walking ability: the 12-Item MS Walking Scale (MSWS-12). Neurology. 2003;60:31-36 Crossref
  • Holviala et al., 2014 J. Holviala, A. Hakkinen, M. Alen, J. Sallinen, W. Kraemer, K. Hakkinen. Effects of prolonged and maintenance strength training on force production, walking, and balance in aging women and men. Scand J Med Sci Sports. 2014;24:224-233 Crossref
  • Jaric, 2003 S. Jaric. Role of body size in the relation between muscle strength and movement performance. Exerc Sport Sci Rev. 2003;31:8-12 Crossref
  • Kantarci, 2008 O.H. Kantarci. Genetics and natural history of multiple sclerosis. Semin Neurol. 2008;28:7-16
  • Kempen et al., 2011 J.C. Kempen, V. de Groot, D.L. Knol, C.H. Polman, G.J. Lankhorst, H. Beckerman. Community walking can be assessed using a 10-metre timed walk test. Mult Scler. 2011;17:980-990 Crossref
  • Kim and Eng, 2003 C.M. Kim, J.J. Eng. The relationship of lower-extremity muscle torque to locomotor performance in people with stroke. Phys Ther. 2003;83:49-57
  • Kjolhede et al., 2012 T. Kjolhede, K. Vissing, U. Dalgas. Multiple sclerosis and progressive resistance training: a systematic review. Mult Scler. 2012;18:1215-1228 Crossref
  • Larocca, 2011 N.G. Larocca. Impact of walking impairment in multiple sclerosis: perspectives of patients and care partners. Patient. 2011;4:189-201
  • Lee et al., 2010 M.J. Lee, S.L. Kilbreath, M.F. Singh, B. Zeman, G.M. Davis. Effect of progressive resistance training on muscle performance after chronic stroke. Med Sci Sports Exerc. 2010;42:23-34 Crossref
  • McDonald et al., 2001 W.I. McDonald, A. Compston, G. Edan, D. Goodkin, H.P. Hartung, F.D. Lublin, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol. 2001;50:121-127 Crossref
  • Moller et al., 2012 A.B. Moller, B.M. Bibby, A.G. Skjerbaek, E. Jensen, H. Sorensen, E. Stenager, et al. Validity and variability of the 5-repetition sit-to-stand test in patients with multiple sclerosis. Disabil Rehabil. 2012;34:2251-2258 Crossref
  • Morris et al., 2002 M.E. Morris, C. Cantwell, L. Vowels, K. Dodd. Changes in gait and fatigue from morning to afternoon in people with multiple sclerosis. J Neurol Neurosurg Psychiatry. 2002;72:361-365 Crossref
  • Ng et al., 2004 A.V. Ng, R.G. Miller, D. Gelinas, J.A. Kent-Braun. Functional relationships of central and peripheral muscle alterations in multiple sclerosis. Muscle Nerve. 2004;29:843-852 Crossref
  • Ouellette et al., 2004 M.M. Ouellette, N.K. LeBrasseur, J.F. Bean, E. Phillips, J. Stein, W.R. Frontera, et al. High-intensity resistance training improves muscle strength, self-reported function, and disability in long-term stroke survivors. Stroke. 2004;35:1404-1409 Crossref
  • Paltamaa et al., 2007 J. Paltamaa, T. Sarasoja, E. Leskinen, J. Wikstrom, E. Malkia. Measures of physical functioning predict self-reported performance in self-care, mobility, and domestic life in ambulatory persons with multiple sclerosis. Arch Phys Med Rehabil. 2007;88:1649-1657 Crossref
  • Rudick et al., 2002 R.A. Rudick, G. Cutter, S. Reingold. The multiple sclerosis functional composite: a new clinical outcome measure for multiple sderosis trials. Mult Scler. 2002;8:359-365 Crossref
  • Sandroff et al., 2013 B.M. Sandroff, J.J. Sosnoff, R.W. Motl. Physical fitness, walking performance, and gait in multiple sclerosis. J Neurol Sci. 2013;328:70-76 Crossref
  • Savci et al., 2005 S. Savci, D. Inal-Ince, H. Arikan, A. Guclu-Gunduz, N. Cetisli-Korkmaz, K. Armutlu, et al. Six-minute walk distance as a measure of functional exercise capacity in multiple sclerosis. Disabil Rehabil. 2005;27:1365-1371 Crossref
  • Schwid et al., 1999 S.R. Schwid, C.A. Thornton, S. Pandya, K.L. Manzur, M. Sanjak, M.D. Petrie, et al. Quantitative assessment of motor fatigue and strength in MS. Neurology. 1999;53:743-750
  • Sosnoff et al., 2011 J.J. Sosnoff, E. Gappmaier, A. Frame, R.W. Motl. Influence of spasticity on mobility and balance in persons with multiple sclerosis. J Neurol Phys Ther. 2011;35:129-132 Crossref
  • Thoumie and Mevellec, 2002 P. Thoumie, E. Mevellec. Relation between walking speed and muscle strength is affected by somatosensory loss in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2002;73:313-315 Crossref
  • Thoumie et al., 2005 P. Thoumie, D. Lamotte, S. Cantalloube, M. Faucher, G. Amarenco. Motor determinants of gait in 100 ambulatory patients with multiple sclerosis. Mult Scler. 2005;11:485-491 Crossref
  • Wagner et al., 2014 J.M. Wagner, T.R. Kremer, L.R. Van Dillen, R.T. Naismith. Plantarflexor weakness negatively impacts walking in persons with multiple sclerosis more than plantarflexor spasticity. Arch Phys Med Rehabil. 2014;95:1358-1365
  • Wang et al., 2010 E. Wang, J. Helgerud, H. Loe, K. Indseth, N. Kaehler, J. Hoff. Maximal strength training improves walking performance in peripheral arterial disease patients. Scand J Med Sci Sports. 2010;20:764-770 Crossref
  • Yahia et al., 2011 A. Yahia, S. Ghroubi, C. Mhiri, M.H. Elleuch. Relationship between muscular strength, gait and postural parameters in multiple sclerosis. Ann Phys Rehabil Med. 2011;54:144-155 Crossref

Footnotes

a Section of Sport Science, Department of Public Health, Aarhus University, Aarhus, Denmark

b Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark

c MS-clinic of Southern Jutland (Sønderborg, Esbjerg, Vejle), Sygehus Sønderjylland, Sønderborg, Denmark

d MS Clinic, Department of Neurology, Aarhus University Hospital, Aarhus, Denmark

lowast Correspondence to: Section of Sport Science, Dalgas Avenue 4, 8000 Aarhus C, Denmark. Tel.: +45 87168163.