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Physical fitness assessment in multiple sclerosis patients: A controlled study

Research in Developmental Disabilities, 10, 35, pages 2527 - 2533



  • Fitness assessment allows to optimize multiple sclerosis rehabilitation protocols.
  • Multiple sclerosis sequentially affects the distal, middle and proximal muscles.
  • Mild degree MS patients and healthy controls showed similar adjustments to exercise.


There is growing evidence to show the effectiveness of physical exercise for multiple sclerosis (MS) patients. Aim of this study was to evaluate aerobic capacity, strength, balance, and the rate of perceived exertion (RPE) after exercise, in ambulatory patients with mild MS and matched control healthy participants. Seventeen MS patients aged 48.09 ± 10.0 years, with mild MS disability (Expanded Disability Status Scale: EDSS 1.5 to 4.5) and 10 healthy sedentary age matched (41.9 ± 11.2 years) subjects volunteered for the study. MS patients underwent medical examination with resting electrocardiogram, arterial blood pressure, EDSS, and Modified Fatigue Impact Scale-MFIS. Both groups also underwent physical assessment with the Berg Balance Scale,test (Berg), Six Minutes Walking Test (6MWT), maximal isometric voluntary contraction (MIVC) of forearm, lower limb, shoulder strength test, and the Borg 10-point scale test. The one-way ANOVA showed significant differences for MFIS (F1.19 = 9.420;p < 0.01), Berg (F1.19 = 13.125;p < 0.01), handgrip MIVC (F1.19 = 4.567;p < 0.05), lower limbs MIVC (F1.19 = 7.429;p < 0.01), and 6MWT (F1.19 = 28.061;p < 0.01) between groups. EDSS, Berg test and Borg scores explained 80% of 6MWT variation. Mild grade EDSS patients exhibited impaired balance, muscle strength, and low self pace-6MWT scores, whereas RPE response after the exercise was similar to that of sedentary individuals. Both groups showed similar global physiological adjustments to exercise.

Keywords: Aerobic capacity, Balance, Strength, Fatigue, Disability.

1. Introduction

Multiple sclerosis (MS) is a chronic autoimmune demyelinating disease of the central nervous system. Evidence indicates that MS is more prevalent in females than males (Ahlgren et al, 2011 and Compston and Coles, 2002). The disease results in an alteration of the myelin, thus reducing the speed of transmission of the nerve impulses, up to conduction block ( Ng, Dao, Miller, Gelinas, & Kent-Brau, 2000 ). This alteration may result in severe symptoms, particularly muscle fatigue and locomotor impairment. Several studies have shown that MS patients have lower values of maximal aerobic power, when compared to healthy adults matched for age and gender and a significant reduction in muscle strength ( Smith, Adeney-Steel, Fulcher, & Longley, 2006 ). Based upon these findings, for many years, patients affected by MS were advised to avoid sessions of exercise and training, since most of them experienced excessive fatigue during and after exercise, coupled with a rise in body temperature ( White, Wilson, Davis, & Petajan, 2000 ). In critical conducting axons, such as those that are demyelinated, impulse conduction may be affected by heating. Raising the body temperature by as little as 0.5 °C may be sufficient to precipitate conduction in critically conducting axons ( Vucic, Burke, & Kiernan, 2010 ).

During the last decade, it has become popular to prescribe physical exercise to MS patients, as long as it is well tolerated and induces relevant improvements in both physical and mental functioning (Dalgas et al, 2008 and White and Dressendorfer, 2004). It is thought that much of the reduced efficiency in MS patients could be the result of increased “inactive life,” secondary to the disease, rather than the impairments caused by the disease per se ( Ng, Miller, Gelinas, & Kent-Braun, 2004 ). Indeed, it is clearly necessary to prescribe and individualize physical exercise in order to achieve significant improvement in quality of life for MS patients and reduce the economic burden. In fact a significant increase in costs is associated with an increase in disease severity as measured by Expanded Disability Status Scale (EDSS) scores. Physical activity is a non-pharmaceutical intervention and act delaying the progression of disease ( Naci, Fleurence, Birt, & Duhig, 2010 ). In light of this, the collection of fitness parameters such as aerobic capacity, strength levels and balance and may represent the basis from which training protocols can be planned. The current standard for testing aerobic capacity is a maximal cardiopulmonary exercise test which determines Maximum oxygen consumption (VO2peak).

VO2peak reflects the maximum capacity of a person to absorb, carry and consume O2( Albouaini, Egred, Alahmar, & Wright, 2007 ). However, VO2peak is a prerogative of specialized laboratory settings with low feasibility. On the contrary, submaximal tests are more functional and have been considered as good predictors of exercise capacity, especially in MS patients who show marked reductions in exercise capacity ( Kuspinar, Andersen, Teng, Asano, & Mayo, 2010 ). Several studies have investigated upper and lower extremity muscle strength in MS subjects, using different methodologies (Citaker et al, 2013 and Kuspinar et al, 2010). Indeed, it is thought that properly designed strength training of the weakest muscle groups should improve MS patients’ management of their everyday activity, whilst simultaneously improving autonomy and reducing the risk of falls ( Cattaneo, Jonsdottir, & Repetti, 2007 ). Changes in balance, coordination, postural control, and gait are other features reported in MS subjects, due to a compromised neural functioning, which leads to both sensory and motor dysfunction ( Coote, Finlayson, & Sosnoff, 2013 ). Proper evaluation of the balance deficit allows for the correct prescription of balance interventions. Over recent years, the quantification of these parameters and the analysis of their correlations have changed the way in which these patients are managed.

Our primary objective was to compare aerobic capacity, strength, balance, and the rate of perceived exertion (RPE) after exercise between ambulatory patients with mild MS and matched control healthy participants. The second objective was to study the correlations between fitness and clinical parameters with the goal of sharpening the focus of the rehabilitation protocols used to tackle this disease.

2. Materials and methods

We screened 17 subjects (13 females, 4 males) aged 48.09 ± 10, affected by MS disability (EDSS 1.5 to 4.5). All patients were ambulatory type, whereas one used a cane. Inclusion criteria were: patients with confirmed diagnosis of clinically definite MS. Personal and clinical information such as age, sex, height, weight, duration of the disease and type of MS were determined by examination of medical charts. We also screened subjects’ BMI, heart rate, baseline electrocardiogram (ECG) and blood pressure. Quantification of disability in MS patients was determined by the EDSS ( Sharrack & Hughes, 1996 ). The EDSS measure was administered by a consultant neurologist. No subject had undergone EDSS evaluation previously, and no EDSS score was reported in the medical charts. This basic scale quantifies disability by evaluating and assessing a score in eight neurological functional systems, namely pyramidal, cerebellar, brainstem, sensory, bowel and bladder, visual and cerebral. The EDSS score ranges from 0, which represents absence of clinical impairment to 10, which is the highest grade. An EDSS level of 3 represents a fully ambulatory patient with moderate disability, a score of 6 represents necessity for unilateral assistance with canes, crutches, or braces when required to walk 100 meters, and a score of 8 represents patients restricted to bed or chair or perambulated in a wheelchair.

A total of 10 age and sex matched healthy and sedentary subjects (41.9 ± 11.2 years) were included as a control group. Exclusion criteria for both the study groups included: pregnancy, morbid obesity as defined by BMI of 40 kg/m2or more, cognitive impairment, cardiopulmonary disease, and orthopedic conditions prohibiting participation in safe exercise testing. The subjects’ characteristics are shown in Table 1 .

Table 1 Subjects characteristics (mean ± SD).

  MS patients (n = 17) Control group (n = 10)
  Mean ± SD Mean ± SD
Age (years) 47.8 ± 10.6 41.9 ± 11.3
Years of disease 6.8 ± 5.1
Height (cm) 164.5 ± 10.7 165.7 ± 10.9
Weight (kg) 65.1 ± 15.8 64.9 ± 13.4
Body Mass index (BMI) 24.1 ± 3.3 23.6 ± 4.2

The perceived difficulty in carrying out daily living activities was assessed in all subjects, MS and Controls, using the Modified Fatigue Impact Scale (MFIS; Tellez et al., 2005 ). This approach is based on 21 items derived from interviews concerning how fatigue had impacted their lives over the preceding month. Administration time was approximately 5–10 min for the full-length version. We administered the MFIS once before the testing sessions, and summary scores as well as physical, cognitive and psychosocial subscale scores were calculated.

All examinations and tests were performed in a public rehabilitation facility. The study was designed in agreement with the Declaration of Helsinki, and was approved by the local Ethical Committee. All subjects volunteered for the study and informed written consent was obtained from all participants before the experimental set-up.

2.1. Procedures

All subjects attended two successive fitness evaluation sessions. In the first fitness testing session subjects underwent the Berg Balance Scale ( Berg, Wood-Dauphinee, Williams, & Maki, 1992 ) and Six Minute Walking test (6MWT) whereas in the second session a strength test were performed.

The Berg test consists of a 14 item scale, according to functional tasks deficits. The test duration is approximately 15 min, with 14 balance-related tasks including unsupported sitting, change of position, standing on one foot, standing with eyes closed. The Berg score ranges from 0, representing no balance capacity with high fall risk, to 4 (normal performance), with a maximum score of 56. In order to perform this test, a ruler, two standard chairs (one with arm rests, one without), a footstool or step, and a stopwatch are required.

The Intraclass Correlation Coefficients (ICCs) for test–retest reliability range between 0.85 and 0.96, whilst the validity (r = 0.71) of the Berg scale has been assessed using a population of subjects with MS (Cattaneo et al, 2007 and Cattaneo et al, 2006).

Functional aerobic capacity (cardiovascular fitness) was measured by using the 6MWT. This test measures the distance that a patient can quickly walk on a flat, hard surface in a period of 6 min. It evaluates the global and integrated responses of all the systems involved during exercise, including the pulmonary and cardiovascular systems, systemic circulation, peripheral circulation, blood, neuromuscular units, and muscle metabolism. With this said however, it does not provide specific information on the function of each of the different organs and systems involved in exercise or the mechanism of exercise limitation. The self-paced 6MWT assesses the submaximal level of functional capacity, even if it involves a “maximal” request; the subjects are in fact invited to walk as many meters as they can. This test was performed in an enclosed 20 m corridor ( Veloso-Guedes et al., 2011 ). Each meter was marked on the floor and a chair was present every 5 meters. Individuals were instructed to walk, back and forth, exerting maximal effort within the 6-min period at their own pace, but were continuously encouraged during this test ( Broekmans et al., 2013 ). They could rest at any time during the test, but were encouraged to resume walking as soon as they were ready. The 6MVT has high reliability (ICC ranged between 0.80 and 0.90) and moderate validity (r = 0.56 to 0.88; Finch, Brooks, Stratford, & Mayo, 2002 ). Subjective perception of fatigue in this test was evaluated using the Borg 10-item scale ( Borg, 1982 ).

Maximum Isometric Voluntary Contraction (MIVC) was measured for the forearm muscles, shoulders elevators muscles and quadriceps muscles, in order to minimize the testing time ( Gutierrez et al., 2005 ). Grip strength was measured using a programmed handgrip dynamometer (IBX H-101, MD Systems INC., Westerville, OH, USA). Standardized instruction and position were used, whilst 3 consecutive trials for each hand were recorded. Grip strength had excellent reliability with a measurement error of approximately 2 kg ( Schreuders et al., 2003 ).

The MIVC of the knee extensor muscles in both limbs was performed during the leg extension tests. Participants sat on a chair, with arms folded across the chest. A sitting iron support was prepared to adapt the sit to the length of the femur, in order to obtain a standard sit position. The trunk was erected and fastened using two crossing belts. Participants were instructed to exert maximal extension torque and to maintain it for 5 s. For extension the knee angle was positioned at 110° (180° refers to full extension), and the hip angle at 90°. MIVC was calculated as the largest 1-s average reached within any single force recording. A total of 3 attempts were measured for both legs, with 2 min of rest between. Extension isometric torque was measured using a commercially available load cell (AEP elettronica, Italy) connected to a computerized system unit. Under the same sitting position but with arms hanging on their side, MIVC of the shoulder elevators was obtained by pulling a 20 cm iron bar connected in a series with the load cell. A target line was always set on the computer screen at a value 20% higher than the best performance. The participants were able to follow their performance on the computer screen.

3. Calculation

Data were expressed as mean (±SD). Descriptive statistics were used to characterize the participants and verify the distribution of variables. A one-way ANOVA was performed to assess significant differences between MS patients and the control group. If significant main effects were found, a Fisher's LSD post hoc was performed. The relationship between investigated MS patient variables was analyzed using Pearson product-moment correlations (r). Forward stepwise linear regression (R2) was performed to identify the best predictive model of exercise capacity. All statistics were calculated using SPSS (SPSS version 20.0 Chicago). A significance level ofp < 0.05 was adopted.

4. Results

Seventeen patients with MS were evaluated. MS patients and controls were homogeneous at baseline for age and BMI. Of the patients, 10 showed Relapsing Remitting MS (RRMS), 6 had Secondary Progressive Course (SPMS), and 1 had only laboratory diagnosis of MS.

A total of 6 subjects declined to perform the isometric strength tests, whereas 11 patients with MS underwent the strength testing sessions.

Considering each dependent variable, the one-way ANOVA revealed significant differences between the two groups, for systolic blood pressure at baseline (F1.19 = 6.478;p < 0.05), diastolic blood pressure at baseline (F1.19 = 7.372;p < 0.05), MFIS (F1.19 = 9.420;p < 0.01), Berg (F1.19 = 13.125;p < 0.01), handgrip MIVC (F1.19 = 4.567;p < 0.05), lower limb MIVC (F1.19 = 7.429;p < 0.01), and 6MWT (F1.19 = 28.061;p < 0.01). No significant differences between groups were found for heart rate at baseline, heart rate at the end of exercise, delta of heart rate, or systolic and diastolic blood pressure at the end.

Considering the strength tests for only the 11 MS patients who gave consent to perform MIVC, the following results were found: MICV leg extension(right-left)29.2 ± 18.9, MICV leg extension(dominant limb)30.6 ± 19.7 kg, range 4.87–78 kg, delta strength of lower limbs 23 ± 16%, MICV handgrip(right-left)24.2 ± 10.7 kg, MICV handgrip(dominant limb)25.07 ± 12.8 kg, range 4.8–47.37 kg. MICV shoulder elevators(right-left)30.3 ± 17.3 kg, MICV shoulder elevators(dominant limb)32.5 ± 17.3 kg, range 10.5–66.88 kg. In comparison with controls, significant differences were found in handgrip and lower limb strength, whereas no significance was found for shoulder strength. The Fisher's LSD post hoc results are shown in Table 2 .

Table 2 Significant differences between MS patients, completing physical testing sessions, and Controls, according to ANOVA One-way test (*p < 0.05; **p < 0.01).

Variables MS patients (n.11) Control (n.10) Variance
  Mean ± SD Mean ± SD F p
HR baseline 75.1 ± 5.3 72.8 ± 11.6 0.348 0.562
HR at the end 96.1 ± 2.4 98.0 ± 17.2 0.0538 0.198
Delta HR 21.0 ± 18.9 25.2 ± 15.9 0.300 0.590
Systolic blood pressure at baseline 121.8 ± 13.3 107.0 ± 13.4 6.478 0.020*
Systolic blood pressure at end 145.5 ± 19.8 131.0 ± 17.3 3.145 0.092
Diastolic blood pressure at baseline 80.0 ± 8.9 70.0 ± 7.8 7.372 0.014*
Diastolic blood pressure at baseline 77.3 ± 9.8 72.5 ± 5.9 1.770 0.199
MFIS 29.7 ± 16.7 10.9 ± 10.2 9.420 0.006**
BORG 4.6 ± 1.7 4.4 ± 1.1 0.143 0.709
BERG 45.7 ± 8.9 56.0 ± 0.0 13.125 0.002**
Handgrip test 22.5 ± 11.6 34.3 ± 13.7 4.567 0.045*
Shoulder elevator test 30.3 ± 17.3 40.2 ± 16.2 1.7524 0.202
Leg extension test 29.2 ± 18.9 52.8 ± 19.8 7.429 0.014*
Right leg extension test 27.8 ± 20.7 53.0 ± 19.0 8.373 0.009**
Left leg extension test 26.2 ± 18.2 53.1 ± 21.2 9.821 0.005**
6MW test 384.0 ± 119.6 614.2 ± 70.6 28.061 <0.000**

HR: Heart Rate; EDSS: Expanded Disability Status Scale; 6MWT: Six Minute Walking test; m: meters; Borg: Perceived exertion Borg Scale; MFIS: Multiple Fatigue Impact Scale; Berg: Balance Berg Scale.

Significant and large correlations were found between EDSS and HR at baseline (r = −0.620;p < 0.05), EDSS and 6MWT (r = −0.843;p < 0.01), as well as EDSS and Borg scores (r = 0.609;p < 0.05, and between 6MWT and Borg scores (r = −0.596;p = 0.053), and 6MWT and Berg (r = 0.716;p < 0.05).

Handgrip, shoulder and lower limb MIVC were significantly correlated with each other (p < 0.01), and with the systolic blood pressure at the baseline (r = 0.806;r = 0.728;r = 0.653;p < 0.01, respectively). Results of linear regression analysis revealed a predictive model from the EDSS for Borg scores (R2 = 0.371,R2adj = 0.301;p < 0.05), for HR at baseline (R2 = 0.384,R2adj = 0.316;p < 0.05) and EDSS, for the cardiovascular fitness, assessed by 6MWT (R2 = 0. 711,R2adj = 0.679;p < 0.01); from 6MWT for Berg (R2 = 0.512,R2adj = 0.458;p < 0.05), and for Borg near the significance (R2 = 0.356,R2adj = 0.284;p = 0.053). The Delta MIVC of lower limbs was predictive of reduced balance evaluated by Berg test (R2 = 0.51,R2adj = 0.481;p < 0.05).

The relationship between 6MWT scores and the other variables was further examined by multiple linear regressions, with adjustment for other covariates. EDSS, Berg test and Borg scores explained 80% 6MWT variation (R2 = 0.856,R2adj = 0.795;p < 0.01) whilst EDSS, 6MWT and Berg test 50%-Borg score variation (R2 = 0.657,R2adj = 0.511;p < 0.05). The results are shown in Fig. 1 .


Fig. 1 (A) EDSS and (B) BERG in relation with 6MWT. Data for all MS patients (N = 17).

5. Discussion

There is growing evidence to support the recommendation of physical exercise for MS patients. Individualized exercise prescription represents a basis from which to optimize rehabilitation protocols ( Döring, Pfueller, Paul, & Dörr, 2011 ). Indeed, the collection of fitness parameters including aerobic capacity, strength and balance, as in this study, may represent the basis on which safe training protocols must be planned. MS patients in our study showed marked reductions in exercise capacity and a considerable decrease in muscle strength, especially in forearm muscles and lower extremity extensors when compared with matched control healthy participants. Our results are in agreement with other studies that have demonstrated a decrease in lower extremity strength ( Citaker et al., 2013 ) due to the need for a greater drive to spinal motoneurons in order to produce the same force ( Thoumie, Lamotte, Cantalloube, Faucher, & Amarenco, 2005 ). The strength impairments in our MS patients mainly involved lower limbs compared to the upper limb dysfunction. This result could be due to the lower limb inactivity, compensated by over use of the upper limbs. Our findings showed no different results in shoulder elevators muscles strength between MS patients and controls. Only a few studies have analyzed upper limb muscle strength and shoulder impairment in an MS population, (Guclu-Gunduz et al, 2012 and Lamers et al, 2013). We decided to measure the strength of shoulder elevator muscles as they affect the upper extremity functions that are frequently involved in daily life activity. We may hypothesize that the MS disease first affects the distal and then the middle and proximal muscles. The strength of the lower limbs and walking capacity were significantly correlated with the handgrip values, and, in accordance with Kierkegaard, Einarsson, Gottberg, von Koch, and Holmqvist (2012) , handgrip measures could be good predictors of the disease degree (Ali et al, 2008 and Kuspinar et al, 2010). Our tests revealed differences between the two groups in the handgrip test, thus confirming the presence of impairments of strength in both arms, as also found by Lamers et al. (2013) but in contrast with other authors ( Kos et al., 2007 ).

In this study, special emphasis was placed on the standardization of muscle strength assessment so as to ensure that all participants had the same torque angles and sitting position. The isometric testing technique was chosen for its relatively simple execution and for its data standardization (Guerra et al, 2013 and Surakka et al, 2004). A special chair with a “variable length” seat, adjustable to each femur length, and with variable femur-tibia angle, was used by the authors. This meant that each subject performed the exercises with the same biomechanical constraints, as was proposed in a previous study ( Surakka et al., 2004 ).

Our patients showed balance disorders, which were significantly correlated to the increasing EDSS levels (Citaker et al, 2013 and Van Emmerik et al, 2010). Considering that muscle strength is one of the main determinants of maintaining balance ( Nilsagård, Lundholm, Denison, & Gunnarsson, 2009 ), strength deficiency, especially in lower extremity muscles, leads to balance problems for MS patients (Citaker et al, 2013 and Yahia et al, 2011). In this study the different degree of weakness between the right and left side was significantly predictive of reduced balance, as demonstrated by Chung, Remelius, Van Emmerik, and Kent-Braun (2008) . A significant decrease in the regulation of standing balance is one of the factors most commonly involved in falls, along with walking aid use and lower mobility status ( Orr et al., 2010 ). Moreover, previous studies have suggested that fatigue can lead to increased probability of falls and that MFIS is a significant predictor of falls ( Finlayson, Peterson, & Cho, 2006 ). According to Coote et al. (2013) , these findings suggest that walking endurance, included in the MS patient exercise program, contributes to a reduction in fatigue impact ( Stroud & Minahan, 2009 ), and should improve balance whilst also reducing the number of falls. Functional walking capacity was measured by sub maximal 6MWT, although it showed a weak correlation with VO2peak ( Kuspinar et al., 2010 ). Nevertheless, we preferred to use self-paced 6MWT for MS patients, rather than the modified 6MWT, which maximizes effort and speed ( Goldman, Marrie, & Cohen, 2008 ). This was done in order to avoid excessive fatigue and worsening symptom perception. Despite having a mild level of EDSS, global functional exercise capacity and sub-maximal resistance of limb muscles, assessed with 6MWT, were significantly lower in MS patients than the controls ( Kuspinar et al., 2010 ). Neurological and orthopedic diseases determine a mechanical inefficiency which increases the metabolic energy cost of walking and consequently fatigue and poor exercise tolerance ( Franceschini et al., 2010 ). In this study, EDSS, Borg and Berg accounted for 80% of 6MWT, and this high correlation means that we can consider walking capacity as the global major indicator of MS impaired autonomy, in accordance with previous studies (Garrett et al, 2013 and Kuspinar et al, 2010).

No significant differences were found between the two groups in terms of resting and recovery HR ( Hansen, Wensa, Dendalea, & Eijndea, 2013 ) and blood pressure at the end of aerobic exercise (6MWT). This was probably due to similar energy cost of exercise of mild MS patients and able-bodied subjects, as reported in a previous study by Morrison et al. (2008) . It should be argued that both groups showed similar global physiopathological adjustments. MS patients showed changes in the first 20 s of exercise-onset (HR), which was significantly smaller than the matched controls ( Hansen et al., 2013 ). In contrast, at the end of the aerobic exercise, the HR cardiac regulation was not different between groups, as in our study. A coordinated interaction of parasymphathetic re-activation and sympathetic withdrawal was noted during recovery from exercise, as demonstrated by Borresen and Lambert (2008) , whilst the magnitude of HR change during recovery may provide a quantifiable measure of disturbance in autonomic control in response to exercise ( Goldsmith, Bloomfield, & Rosenwinkel, 2000 ). The substantial similarity, noted between the two groups in HR and pressure at the end of the exercise, was facilitated by the accurate enrollment of the two groups, and was similar for sedentary level of activity. No warning instability of symptoms or inappropriate sweating was detected ( White et al., 2000 ).

In this study, the MS population reported to perceive high fatigue in daily life over the preceding month. Our data showed that the MFIS mean value of MS patients was significantly greater than controls, due not only to the disease processes but also to sleep disturbances, depression, pain and medication use ( Stroud & Minahan, 2009 ). The Borg RPE rating was administered to assess the effort sense after aerobic exercise. It is well known the MS exercise intolerance is due to peripheral factors such as low muscle strength and oxidative capacity, and central factors such as dysfunction of the nervous system ( Steens, Heersema, Maurits, Renken, & Zijdewind, 2012 ). Despite higher baseline MFIS scores, no significant differences between MS patients and controls were found in the Borg 10-point scale results. Considering that resting and recovery HR ( Hansen et al., 2013 ) and blood pressure at the end of aerobic exercise (6MWT) were similar between groups, Borg RPE ratings gave the same results. As Morrison et al. (2008) showed, the symptomatic fatigue, assessed by the MFIS, is not linked to the effort sense perceived after the physical exercise.

The quantitative protocol used in this study reveals information that would not be available through a standard neurological examination, and allows for the prescription of focused rehabilitation protocols. Analysis of the correlations between functional capacities and impairments helps to follow this purpose, in fact the correlations between physical and neurological impairment are consistent with previous results (Motl et al, 2009, Orr et al, 2010, and Yahia et al, 2011).

Considering the MS patients only, two models of linear regression were performed; one with EDSS as the only predictor variable, and another multiple regression. The disability level (EDSS) alone explained 71% of the decrease in functional walking capacity, measured by a self-paced 6MW, 38% of the HR increase and 37% of the fatigue perception (MFIS). EDSS, when combined with the Berg test, and 6MWT, explained 50% of MFIS. It may be argued that a training program based on balance, and aerobic capacity improvement, should contrast the fatigue perception in mild–moderate MS patients. Improved cardiovascular health at any level and general strength may enhance the overall rehabilitation outcome of many individuals affected by this disease.

6. Conclusion

Muscle weakness and fatigue contribute to a reduction in daily activity in persons with MS. Inactivity further compromises muscle function, ambulatory ability, and physical fitness. We hope that this study will assist MS rehabilitation professionals in reversing MS patient sedentary lifestyle and prescribing individualized training following a well-standardized comprehensive fitness assessment. The results of the present study demonstrated the feasibility of this fitness evaluation protocol in determining whether individualized non-pharmacological physical intervention can be prescribed.

There were certain limitations in our study which must be addressed. The first limitation was the modest 27-participant sample. The limitation of the MS patient number was dependent on the difficulty in recruiting patients with the desire to be engaged in physical exercise.

The second limitation was that MS patients in this study were affected by mild disability, and as such our results might not apply to patients with more severe degrees of the disease. Finally, only the knee extensors were tested to evaluate the lower limb strength. Core and hip muscles, which may affect balance and walking, were not evaluated in this study. Further studies are needed with a larger sample, more severe grade of MS to confirm the validity and compliance of this physical fitness assessment.


No financial support was received for the study.


  • Ahlgren et al., 2011 C. Ahlgren, A. Odén, J. Lycke. High nationwide prevalence of multiple sclerosis in Sweden. Multiple Sclerosis Journal. 2011;17:901-908
  • Albouaini et al., 2007 K. Albouaini, M. Egred, A. Alahmar, D.J. Wright. Cardiopulmonary exercise testing and its application. Heart. 2007;83:675-682
  • Ali et al., 2008 N.A. Ali, J.M. O’Brien, S. Hoffmann, G. Phillips, A. Garland, J.C. Finley, et al. Acquired weakness, handgrip strength, and mortality in critically ill patients. American Journal of Respiratory and Critical Care Medicine. 2008;178:261-268
  • Berg et al., 1992 K. Berg, S. Wood-Dauphinee, J.I. Williams, B. Maki. Measuring balance in the elderly: Validation of an instrument. Canadian Journal of Public health. 1992;83:7-11
  • Borg, 1982 G. Borg. Psychosocial bases of perceived exertion. Medicine & Science in Sports & Exercise. 1982;14:377-381
  • Borresen and Lambert, 2008 J. Borresen, M.I. Lambert. Autonomic control of heart rate during and after exercise. Measurements and implications for monitoring training status. Sports Medicine. 2008;38:633-646
  • 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. Multiple Sclerosis. 2013;19:112-119
  • Cattaneo et al., 2006 D. Cattaneo, A. Regola, M. Meotti. Validity of six balance disorders scales in persons with multiple sclerosis. Disability and Rehabilitation. 2006;28:789-795
  • Cattaneo et al., 2007 D. Cattaneo, J. Jonsdottir, S. Repetti. Reliability of four scales on balance disorders in persons with multiple sclerosis. Disability and Rehabilitation. 2007;29:1920-1925
  • 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. Medicine & Science in Sports & Exercise. 2008;40:1717-1724
  • Citaker et al., 2013 S. Citaker, A. Guclu-Gunduz, G. Yazici, D. Bayraktar, B. Nazliel, C. Irkec. Relationship between lower extremity isometric muscle strength and standing balance in patients with multiple sclerosis. NeuroRehabilitation. 2013;33:293-298
  • Compston and Coles, 2002 A. Compston, A. Coles. Multiple sclerosis. Lancet. 2002;359:1221-1231
  • Coote et al., 2013 S. Coote, M. Finlayson, J.J. Sosnoff. Level of mobility limitations and falls status in persons with multiple sclerosis. Archives of Physical Medicine Rehabilitation. 2013;95:862-866
  • Dalgas et al., 2008 U. Dalgas, E. Stenager, T. Ingemann-Hansen. Multiple sclerosis and physical exercise: Recommendations for the application of resistance, endurance and combined training. Multiple Sclerosis. 2008;14:35-53
  • Döring et al., 2011 A. Döring, C.F. Pfueller, F. Paul, J. Dörr. Exercise in multiple sclerosis – An integral component of disease management. The EPMA Journal. 2011;3:2
  • Finch et al., 2002 E. Finch, D. Brooks, P.W. Stratford, N.E. Mayo. Physical rehabilitation outcome measures: A guide to enhanced clinical decision making. (Lippincott Williams & Wilkins, Ontario, 2002)
  • Finlayson et al., 2006 M.L. Finlayson, E.W. Peterson, C.C. Cho. Risk factors for falling among people aged 45 to 90 years with multiple sclerosis. Archives of Physical Medicine Rehabilitation. 2006;87:1274-1279
  • Franceschini et al., 2010 M. Franceschini, A. Rampello, F. Bovolenta, M. Aiello, P. Tzani, A. Chetta. Cost of walking, exertional dyspnoea and fatigue in individuals with multiple sclerosis not requiring assistive devices. Journal of Rehabilitation Medicine. 2010;42:719-723
  • Garrett et al., 2013 M. Garrett, N. Hogan, A. Larkin, J. Saunders, P. Jakeman, S. Coote. Exercise in the community for people with multiple sclerosis – A follow-up of people with minimal gait impairment. Multiple Sclerosis. 2013;19:790-798
  • Goldman et al., 2008 M.D. Goldman, R.A. Marrie, J.A. Cohen. Evaluation of the six-minute walk in multiple sclerosis subjects and healthy controls. Multiple Sclerosis. 2008;14:383-390
  • Goldsmith et al., 2000 R.L. Goldsmith, D.M. Bloomfield, E.T. Rosenwinkel. Exercise and autonomic function. Coronary Artery Disease. 2000;11:129-135
  • Guclu-Gunduz et al., 2012 A. Guclu-Gunduz, S. Citaker, B. Nazlielb, C. Irkecb. Upper extremity function and its relation with hand sensation and upper extremity strength in patients with multiple sclerosis. NeuroRehabilitation. 2012;30:369-374
  • Guerra et al., 2013 E. Guerra, F. Quaranta, F. Sperandii, P. Borrione, E. Ciminelli, L. Calo’, et al. Physiological and metabolic evaluation in the study of a functional model of rugby. Medicina Dello Sport. 2013;66:307-313
  • Gutierrez et al., 2005 G.M. Gutierrez, J.W. Chow, M.D. Tillman, S.C. McCoy, V. Castellano, L.J. White. Resistance training improves gait kinematics in persons with multiple sclerosis. Archives of Physical Medicine Rehabilitation. 2005;86:1824-1829
  • Hansen et al., 2013 D. Hansen, I. Wensa, P. Dendalea, B.O. Eijndea. Exercise-onset heart rate increase is slowed in multiple sclerosis patients: Does a disturbed cardiac autonomic control affect exercise tolerance?. NeuroRehabilitation. 2013;33:139-146
  • Kierkegaard et al., 2012 M. Kierkegaard, U. Einarsson, K. Gottberg, L. von Koch, L.W. Holmqvist. The relationship between walking, manual dexterity, cognition and activity/participation in persons with multiple sclerosis. Multiple Sclerosis. 2012;18:639-646
  • Kos et al., 2007 D. Kos, G. Nagels, M.B. D’Hooghe, W. Duquet, S. Ilsbroukx, S. Delbeke, et al. Measuring activity patterns using actigraphy in multiple sclerosis. Chronobiology International. 2007;24:345-356
  • Kuspinar et al., 2010 A. Kuspinar, R.E. Andersen, S.Y. Teng, M. Asano, N.E. Mayo. Predicting exercise capacity through submaximal fitness tests in persons with multiple sclerosis. Archives of Physical Medicine Rehabilitation. 2010;91:1410-1417
  • Lamers et al., 2013 I. Lamers, A.A. Timmermans, L. Kerkhofs, D. Severijns, B. Van Wijmeersch, P. Feys. Self-reported use of the upper limbs related to clinical tests in persons with multiple sclerosis. Disability Rehabilitation. 2013;35:2016-2020
  • Morrison et al., 2008 E.H. Morrison, D.M. Cooper, L.J. White, J. Larson, S.Y. Leu, F. Zaldivar, et al. Ratings of perceived exertion during aerobic exercise in multiple sclerosis. Archives of Physical Medicine Rehabilitation. 2008;89:1570-1574
  • Motl et al., 2009 R.W. Motl, E. McAuley, E.M. Snook, R.C. Gliottoni. Physical activity and quality of life in multiple sclerosis: Intermediary roles of disability, fatigue, mood, pain, self-efficacy and social support. Psychological Health Medicine. 2009;14:111-124
  • Naci et al., 2010 H. Naci, R. Fleurence, J. Birt, A. Duhig. Economic burden of multiple sclerosis: A systematic review of the literature. Pharmaco Economic. 2010;28:363-379
  • Ng et al., 2000 A.V. Ng, H.T. Dao, R.G. Miller, D.F. Gelinas, J.A. Kent-Brau. Blunted pressor and intramuscular metabolic responses to voluntary isometric exercise in multiple sclerosis. Journal of Applied Physiology. 2000;88:871-880
  • 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
  • Nilsagård et al., 2009 Y. Nilsagård, C. Lundholm, E. Denison, L.G. Gunnarsson. Predicting accidental falls in people with multiple sclerosis: A longitudinal study. Clinical Rehabilitation. 2009;23:259-269
  • Orr et al., 2010 J. Orr, T. Dowd, J.K. Rush, J. Hsu, J. Ficke, K. Kirk. The effect of immobilization devices and left-foot adapter on brake-response time. Journal of Bone Joint Surgery American. 2010;92:2871-2877
  • Schreuders et al., 2003 T.A. Schreuders, M.E. Roebroeck, J. Goumans, J.F. van Nieuwenhuijzen, T.H. Stijnen, H.J. Stam. Measurement error in grip and pinch force measurements in patients with hand injuries. Physical Therapy. 2003;83:806-815
  • Sharrack and Hughes, 1996 B. Sharrack, R.A. Hughes. Clinical scales for multiple sclerosis. Journal of the Neurological Science. 1996;135:1-9
  • Smith et al., 2006 R.M. Smith, M. Adeney-Steel, G. Fulcher, W.A. Longley. Symptom change with exercise is a temporary phenomenon for people with multiple sclerosis. Archives of Physical Medicine Rehabilitation. 2006;87:723-727
  • Steens et al., 2012 A. Steens, D.J. Heersema, N.M. Maurits, R.J. Renken, I. Zijdewind. Mechanisms underlying muscle fatigue differ between multiple sclerosis patients and controls: a combined electrophysiological and neuroimaging study. Neuroimage. 2012;59:3110-3118
  • Stroud and Minahan, 2009 N.M. Stroud, C.L. Minahan. The impact of regular physical activity on fatigue, depression and quality of life in persons with multiple sclerosis. Health and Quality of Life Outcomes. 2009;20:57-68
  • Surakka et al., 2004 J. Surakka, A. Romberg, J. Ruutiainen, A. Virtanen, S. Aunola, K. Mäentaka. Assessment of muscle strength and motor fatigue with a knee dynamometer in subjects with multiple sclerosis: A new fatigue index. Clinical Rehabilitation. 2004;18:652-659
  • Tellez et al., 2005 N. Tellez, J. Rio, M. Tintore, C. Nos, L. Galan, X. Montalban. Does the modified Fatigue Impact Scale offer a more comprehensive assessment of fatigue in MS?. Multiple Sclerosis. 2005;11:198-202
  • 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. Multiple Sclerosis. 2005;11:485-491
  • Van Emmerik et al., 2010 R.E. Van Emmerik, J.G. Remelius, M.B. Johnson, L.H. Chung, J.A. Kent-Braun. Postural control in women with multiple sclerosis: Effects of task, vision and symptomatic fatigue. Gait & Posture. 2010;32:608-614
  • Veloso-Guedes et al., 2011 C.A. Veloso-Guedes, S.T. Rosalen, C.M. Thobias, R.M. Andreotti, F.D. Galhardo, A.M. Oliveira da Silva, et al. Validation of 20-meter corridor for the 6-minute walk test in men on liver transplantation waiting list. Transplantation Proceedings. 2011;43:1322-1324
  • Vucic et al., 2010 S. Vucic, D. Burke, M.C. Kiernan. Fatigue in Multiple Sclerosis: mechanism and management. Clinical Neurophysiology. 2010;121:809-817
  • White et al., 2000 A.T. White, T.E. Wilson, S.L. Davis, J.H. Petajan. Effect of precooling on physical performance in multiple sclerosis. Multiple Sclerosis. 2000;6:176-180
  • White and Dressendorfer, 2004 L.J. White, R.H. Dressendorfer. Exercise and multiple sclerosis. Sports Medicine. 2004;34:1077-1100
  • Yahia et al., 2011 A. Yahia, S. Ghroubi, C. Mhiri, M.H. Elleuch. Relationship between muscular strength, gait and postural parameters in multiple sclerosis. Annals of Physical Rehabilitation Medicine. 2011;54:144-155


a Department of Health, Movement and Human Sciences University of Rome “Foro Italico”, Piazza Lauro de Bosis 15, Rome, Italy

b Department of Medicine and Health Sciences, University of Molise, V. De Sanctis, Campobasso, Italy

lowast Corresponding author. Tel.: +39 06 36733338; fax: +39 06 36733344.