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RFD appears crucial for counteracting unexpected perturbations and avoiding falling.
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RFD is preferentially impaired in persons with MS and is associated with falls.
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RFD may be a helpful tool in identifying persons with MS at future risk of falling.
Abstract
Background
Falls as well as fall-related injuries (e.g., bone fractures) are common in persons with multiple sclerosis (pwMS). Whilst some studies have identified lower extremity maximal muscle strength (Fmax) as one among several risk factors, no previous studies have investigated the association between rate of force development (RFD; ability to generate a rapid rise in muscle force) and falls in pwMS. Not only is RFD substantially compromised (and more so than Fmax) in pwMS, studies involving other neurodegenerative populations have shown that RFD – to a greater extent than Fmax – is crucial for counteracting unexpected perturbations and avoiding falling.
Objective
To explore whether knee extensor RFD (and Fmax) can discriminate fallers from non-fallers in pwMS.
Methods
Knee extensor neuromuscular function (comprising RFD50ms and RFD200ms (force developed in the interval 0–50 ms and 0–200 ms, respectively) as well as Fmax) of the weaker leg was assessed by isokinetic dynamometry. Falls were determined by 1-year patient recall, with pwMS subsequently being classified as non-fallers (0 falls), fallers (1–2 falls), or recurrent fallers (≥3 falls).
Results
A total of n=53 pwMS were enrolled in the study, with n=24 classified as non-fallers (63% females, 48 years, EDSS 2.2), n=16 as fallers (88% females, 57 years, EDSS 3.3), and n=13 as recurrent fallers (46% females, 60 years, EDSS 4.2). Compared with non-fallers, neuromuscular function was reduced in both fallers (RFD50 -4.42 [-7.47;-1.37] Nm.s−1.kg−1, -48%; RFD200 -1.45 [-2.98;0.07] Nm.s−1.kg−1, -24%; Fmax -0.42 [-0.81;-0.03] Nm.kg−1, -21%) and recurrent fallers (RFD50 -5.69 [-8.94;-2.43] Nm.s−1.kg−1, -62%; RFD200 -2.26 [-3.89;-0.63] Nm.s−1.kg−1, -38%; Fmax -0.38 [-0.80;0.03] Nm.kg−1, -19%). Across all participants, associations were observed between RFD50ms and falls (rs = -0.46 [-0.67;-0.24], between RFD200ms and falls (rs = -0.34 [-0.59;-0.09]), and between Fmax and falls (rs = -0.24 [-0.48;0.01]).
Conclusion
In this exploratory study, knee extensor neuromuscular function was able to discriminate fallers from non-fallers in pwMS, with RFD being superior to Fmax. Routine assessment of lower extremity neuromuscular function (RFD50ms in particular) may be a helpful tool in identifying pwMS at future risk of falling.
Brain lesions and brain atrophy are hallmarks of multiple sclerosis (MS), potentially leading to a wide range of symptoms, including physical impairments (
). This has been verified by numerous studies comparing persons with MS (pwMS) and healthy controls (HC), revealing substantial reductions in muscle strength (Fmax; ability to generate maximal force) yet preferentially in muscle power and rate of force development (RFD; ability to generate a rapid rise in force) of the lower extremities (
). In other neurodegenerative populations, this is explained by RFD being attributed to neurological factors such as motor unit recruitment and discharge rate mainly, with Fmax being attributed to both neurological factors and muscular factors such as muscle size, fiber type composition, muscle contractile properties, and musculotendinous stiffness (
You are as fast as your motor neurons: speed of recruitment and maximal discharge of motor neurons determine the maximal rate of force development in humans.
). From a physical functional perspective, it is thus important to understand the implications of MS-induced reductions in RFD compared to that of Fmax.
A potential consequence of the physical/neuromuscular functional impairments observed in pwMS is an elevated risk of falling. More than 50% of pwMS report to have fallen within the past 3-to-6 months (
), including impaired walking capacity, use of walking aids, impaired balance / increased postural sway, increased stepping reacting time, fatigue, urinary disorders, impaired cognitive function, and reduced lower extremity Fmax. Regarding lower extremity Fmax, equivocal findings however exist. Two studies have reported that lower extremity Fmax is associated with falls in pwMS (reduced leg Fmax more frequent in fallers compared to non-fallers (
)). Importantly, in other neurodegenerative populations, it has been argued that RFD – to a greater extent than Fmax – is crucial for tasks requiring fast limb or body movement thereby counteracting unexpected perturbations and avoiding falling (
). The distinction between RFD and Fmax is thus highly important, especially since the former outcome is preferentially affected compared to the latter (as mentioned above) (
). Nevertheless, no previous studies have so far explored the link between lower extremity RFD (alongside Fmax) and falls in pwMS.
Therefore, the aim of this exploratory study was to investigate whether knee extensor RFD (and Fmax) can discriminate fallers from non-fallers in pwMS. We hypothesized that RFD would be preferentially impaired and show a stronger association with falls compared to Fmax in pwMS.
2. Methods
The present exploratory study contains cross-sectional data examining the association between lower extremity neuromuscular function and falls in n=53 pwMS. Further details on study design, sample size calculation (based upon differences in age-related impairments of dynamic knee extensor muscle strength in HC compared to pwMS), participants, and methods can be found in previously published articles examining the effects of aging on lower extremity neuromuscular function and physical function in pwMS (
Recruitment of pwMS was carried out in collaboration with The Danish MS Society (“Scleroseforeningen”) using their website and local events. Interested and eligible pwMS underwent neurological examination at the MS clinic they were affiliated with, and data on MS type, EDSS (Expanded Disability Status Scale), time since diagnosis, and current disease-modifying drugs were collected. Inclusion criteria: 18 years or older, definite MS diagnosis according to the McDonald criteria (
), EDSS score ≤ 6.5 corresponding to preserved walking capacity yet with constant bilateral assistance (canes, crutches, braces) required to walk about 20 m without resting, able to independently attend the laboratory for testing. Exclusion criteria: relapse within the prior two months, serious medical comorbidities affecting the nervous and/or muscular system (e.g., neuropathy), current pregnancy, pacemaker user, blood pressure >160/100 mmHg on the day of testing, regular participation in moderate-to-high intensity structured exercise (≥ 3 sessions per week, ≥30 min per session) during the past 6 months. Of note, no inclusion or exclusion criteria related to falls were applied, ensuring a representative selection of ambulatory pwMS regarding the aim(s) of the present study. All participants were reimbursed for their travel costs, but no other compensation was offered. All participants provided written informed consent prior to enrolment, and the study was conducted in accordance with the Declaration of Helsinki and was approved by the Local Ethics Committee of Region Midtjylland (1–10–72–206–17).
), maximum voluntary knee extensor (KE) isometric contractions (Fmax) of the self-reported weaker leg were carried out using an isokinetic dynamometer (Humac NORM, CSMi, MA, USA). Participants were seated in an upright position adjusted to individual anatomical dimensions, with a hip joint angle of 85° and a knee joint angle of 70° (0° being fully extended). Participants performed 2 submaximal trials (approx. 50 and 80%, respectively, of maximal effort), and 3 Fmax trials interspersed by 1 min rest periods. Participants were instructed to contract as fast and forcefully as possible and maintain maximal force exertion for approximately 3 s. Participants were provided with real-time visual feedback along with strong verbal support.
Force was sampled using TeleMyo Direct Transmission System and MyoResearch Software (Noraxon, Scottsdale, AZ, USA) at 1500 Hz. Subsequent analyses including 6 Hz low-pass filtering were performed using custom-made software (MathWorks, MatLab 2017, MA, USA). RFD was derived as the average tangential slope of the ascending force–time curve calculated in the interval 0–50 ms (RFD50ms, early phase RFD) and 0–200 ms (RFD200ms, late phase RFD) relative to the onset of contraction. Fmax was determined as the highest force value attained. RFD and Fmax are presented as values normalized to body mass (Nm.s−1.kg−1 and Nm.kg−1, respectively), thus reflecting how well an individual would cope with whole body movement tasks. Trials with initial countermovement (identified by a visible drop in the force response) were discarded, and a new trial was performed. All force trials were gravity corrected.
Objectively assessed physiological, physical, and cognitive function along with patient-reported outcomes during the first 2 years of Alemtuzumab treatment in multiple sclerosis: a prospective observational study.
), three objective tests were used. The 2-minute walk test (2MWT; presented in m) was assessed on a 30-meter track, to evaluate walking endurance. Participants were instructed to walk as far a distance as possible. The timed 25 ft walk test (T25FWT; presented in m.s−1 as well as in s enabling comparison to previously published data) was assessed on a 25-feet track (corresponding to 7.62 m), to evaluate simple short distance walking involving horizontal propulsion/acceleration. Participants were instructed to walk as fast as possible yet safely, and the best of two trials was selected for further analysis. The six spot step test (SSST; presented as #.s−1 representing number of SSST that can be completed per second as well as in s enabling comparison to previously published data) was assessed on a specially designed 5 meter track with 5 wooden blocks (placed 1 meter apart in the x-y plane), to evaluate complex short distance walking involving coordination and dynamic balance. Participants were instructed to walk as fast as possible yet safely, and the average of four trials (two with left foot only, two with right foot only) was used for further analysis.
2.4 Falls
Patient-reported retrospective total number of falls during the past 12 months was registered. A fall was defined as “an unexpected event in which participants come to rest on the ground, floor or lower level” (
). Participants were classified as non-fallers (0 falls), fallers (1–2 falls), and recurrent fallers (≥ 3 falls). In addition, data across non-fallers (0 falls) and fallers in general (≥ 1 falls) are presented in the Supplementary Table.
2.5 Other potential risk factors for falls
For transparency and acknowledgement of other potential risk factors for falls, those evaluated in the present study are also presented. The 21-item modified fatigue impact scale (MFIS) was used to assess the total, physical, and cognitive impact of fatigue (
). Each of the 21 items of the MFIS were scored 0–4 for each, providing a total score ranging from 0 to 84 (higher scores, greater fatigue impact). The 7-item falls efficacy scale-international (FES-I) was used to assess fear of falling (
). Lastly, we calculated the T25FWT:SSST ratio, with lower values in this ratio (i.e., preferential impairments in SSST compared to that of T25FWT) representing specific alterations in balance/coordination.
2.6 Statistical analysis
Statistical analyses were performed using linear mixed model in STATA (IC 16, StataCorp, College Station, TX, USA). Data on all participant characteristics, neuromuscular function outcomes, and physical function outcomes followed a normal distribution. Number of falls did not follow a normal distribution. Participant ID was set as a random effect and falls group (non-fallers, fallers, recurrent fallers) as fixed effects. Our main analyses focused on differences between neuromuscular function outcomes across falls groups. In addition, we adjusted for the two common confounding variables sex and age. Associations were carried out between neuromuscular function outcomes and number of falls (spearman's rank correlation; confidence interval derived from 1000 bootstrap replications) as well as falls groups (Pearson's correlation; confidence interval derived from Fisher's transformation).
To accentuate differences between falls groups, percentage deficits were calculated as individual values for each pwMS expressed in relation to the mean of non-fallers across RFD50ms, RFD200ms, and Fmax.
3. Results
3.1 Participant characteristics
More than half of the enrolled pwMS had experienced falls in the preceding year (non-fallers [0 falls] 45%, fallers [1–2 falls] 30%, recurrent fallers [3+ falls; range 3–20 falls] 25%). Proportion of females tended to differ across groups with 88% in the non-fallers, 63% in the fallers, and 46% in the recurrent fallers (Table 1). Also, increases in age, EDSS, and FES-I along with decreases in walking capacity (6MWT, T25FWT, SSST), and balance/coordination (T25FWT:SSST ratio) were observed across non-fallers, fallers, and recurrent fallers (Table 1). Overall, these observed differences (disregarding age), remained after adjusting for age and sex (data not shown). Summarized data across non-fallers and fallers in general (i.e., regardless of number of falls) are presented in the Supplementary Table.
Table 1Participant characteristics.
EDSS = Expanded Disability Status Scale. 6MWT = 6-minute walk test. T25FWT = timed 25-foot walk test. SSST = six spot step test. Statistical level of significance set at p<0.05 (trends p<0.10, shown in italic): a = different from non-fallers, b = different from fallers. n.r. = not reported. Data is shown as proportion (%) or as mean ± SD.
3.2 Rate of force development and maximal muscle strength
As shown in Table 2, RFD50ms, RFD200ms, and to some extent Fmax differed across non-fallers, fallers, and recurrent fallers (predominantly between non-fallers and fallers / recurrent fallers). When compared to non-fallers, lower absolute values were observed for fallers and recurrent fallers in RFD50ms (-4.42 [-7.47;-1.37] Nm.s−1.kg−1, p<0.01; -5.69 [-8.94;-2.43] Nm.s−1.kg−1, p<0.01; respectively), RFD200ms -1.45 [-2.98;0.07] Nm.s−1.kg−1, p=0.062; -2.26 [-3.89;-0.63] Nm.s−1.kg−1, p<0.01; respectively), and Fmax -0.42 [−0.81;-0.03] Nm.kg−1,p=0.034; -0.38 [-0.80;0.03] Nm.kg−1,p=0.069; respectively). Overall, the observed differences in RFD50ms and in RFD200ms (but not in Fmax) remained after adjusting for age and sex (data not shown). Summarized data across non-fallers and fallers in general (i.e., regardless of number of falls) are presented in the Supplementary Table.
Table 2Neuromuscular function.
Non-fallers
Fallers
Recurrent fallers
Group differences
(0 Falls)
(1–2 Falls)
(3+ Falls)
RFD50ms (Nm.s−1.kg−1)
9.18 ± 6.46
4.76 ± 3.63
a
3.49 ± 2.50
a
<0.001
RFD200ms (Nm.s−1.kg−1)
5.97 ± 3.09
4.52 ± 1.99
a
3.71 ± 1.58
a
0.016
Fmax (Nm.kg−1)
2.03 ± 0.78
1.62 ± 0.50
a
1.65 ± 0.49
a
0.057
RFD = rate of force development. Fmax = maximal muscle strength. Statistical level of significance set at p<0.05 (trends p<0.10, shown in italic): a = different from non-fallers. Data is shown as mean ± SD.
When compared to non-fallers, marked deficits were observed for fallers as well as for recurrent fallers in RFD50ms (-48 [-67;-29]% and -62 [-76;-48]%, respectively, both p<0.001), RFD200ms (-24 [-40;-9]% and -38 [-52;-24]%, respectively, both p<0.001), and Fmax (-21 [-32;-9]% and -19 [-30;-8]%, respectively, both p<0.001) (Fig. 1). Overall, the observed deficits in RFD50ms (but not in RFD200ms or in Fmax) remained after adjusting for age and sex (data not shown).
Fig. 1RFD = rate of force development. Fmax = maximal muscle strength. Statistical level of significance set at p<0.05 (trends p<0.10, shown in italic): a = different from non-fallers. ⊗ = Different from RFD50ms (within same falls group). ⊕ = different from RFD200ms (within same falls group). Data is shown as mean ± 95%CI.
In fallers, deficits were greater for RFD50ms compared to RFD200ms (-23 [-46;-2],p=0.034) and for RFD50ms compared to Fmax (-28 [-50;-5],p=0.015), but not for RFD200ms compared to Fmax (-4 [-26;18],p=0.740) (Fig. 1). In recurrent fallers, deficits were greater for RFD50ms compared to RFD200ms (-24 [-43;-6],p=0.010), for RFD50ms compared to Fmax (-43 [-62;-25], p<0.000), and for RFD200ms compared to Fmax (-19 [-37;-1],p=0.043) (Fig. 1).
3.3 Association between RFD as well as FMAX and falls
Across all participants, correlations were observed between RFD50ms and falls (rs = -0.46 [-0.67;-0.24], p<0.001), between RFD200ms and falls (rs = -0.34 [-0.59;-0.09],p=0.013), and between Fmax and falls (rs = -0.24 [-0.48;0.01],p=0.090). These correlations corresponded to neuromuscular functioning explaining 21, 11, and 6%, respectively, of the variance in number of falls. Comparable correlations were observed between RFD50ms and falls group (r=-0.45 [-0.64;-0.20], p<0.001), RFD200ms and falls group (r=-0.36 [-0.58;-0.10],p=0.008), and Fmax and falls (r=-0.27 [-0.50;0.00],p=0.052).
4. Discussion
To the best of our knowledge, the present study is the first to examine the association between lower extremity RFD and falls in pwMS. The main findings were that RFD (early phase RFD in particular) was superior to Fmax in terms of discriminating fallers and recurrent fallers from non-fallers in pwMS. This was evidenced by greater impairments in absolute and relative (deficit) values in RFD50ms vs. RFD200ms vs. Fmax in recurrent fallers vs. fallers vs. non-fallers, alongside moderate associations between RFD and falls yet only weak associations between Fmax and falls.
In contrast to the scarcity of studies examining RFD in pwMS (
Neuromuscular adaptations to long-term progressive resistance training translates to improved functional capacity for people with multiple sclerosis and is maintained at follow-up.
) - especially in relation to falls - numerous studies involving older individuals free of neurological disorders exist. The latter has been summarized in a review from our group (
), also revealing greater deficits in RFD compared to that of Fmax when comparing fallers to non-fallers (-18 vs. -11%; pooled data across early and late phase RFD). This is, however of much smaller magnitudes than that observed in pwMS participating in the present study (-42 vs. -20%; pooled data across fallers and recurrent fallers as well as across early and late phase RFD; see Supplementary Table). Based on these data, it is reasonable to assume that RFD in pwMS will become even more compromised with advanced age (i.e., 60 years and beyond) potentially increasing the risk of falling.
Regarding Fmax, deficits were observed in fallers compared to non-fallers Fmax (-21%) and in recurrent fallers compared to non-fallers (-19%), thereby complying with previous study findings. Matsuda and colleagues reported that lower extremity Fmax (subjectively evaluated: 5-point scale survey, rating severity of weakness in legs) was more frequent in fallers compared to non-fallers (6 months retrospective) (
), and Kasser and colleagues reported that lower extremity muscle Fmax (objectively evaluated: dynamometer; knee extension and flexion) was predictive of 2 or more falls in pwMS (12 months prospective) (
). In contrast, Hoang and colleagues alongside Gunn and colleagues did not observe any differences in knee extensor Fmax (objectively evaluated: dynamometer; knee extension) when comparing fallers to non-fallers (3 months prospective) (
). These discrepancies may be explained by the choice of study design (retrospective vs. prospective, with the former underestimating number of falls compared to the latter (
); 3-to-12 months duration, with longer duration being more robust) and by the methods applied to assess muscle strength (objective vs. subjective; different muscles / muscle groups; lack of normalization of Fmax to body mass - a recommended approach (
) - indicative of how well an individual would cope with whole body movement tasks). As for the latter, if we re-analyze our data using absolute Fmax (Nm) instead of normalized Fmax (Nm.kg−1), statistical differences between non-fallers, fallers, and recurrent fallers are slightly attenuated (e.g., shift in overall group differences from p=0.057 to p=0.081). In order to provide more reliable outcomes of neuromuscular function in pwMS, and especially when linking it to physical functional performance, future studies should apply the recommended normalization methods (
). A number of these were also evaluated in the present study. Neither fatigue (MFIS total score as well as sub-scores) nor information processing speed (SDMT) differed between non-fallers, fallers, and recurrent fallers. In contrast, fear of falling (FES-I), all measures of walking capacity (T25FWT, 2MWT, SSST), and balance/coordination (T25FWT:SSST ratio) were all negatively affected in fallers and recurrent fallers compared to non-fallers. Hence, the complexity of falls with contribution of multiple risk factors, must be taken into consideration when interpreting individual risk factors (such as RFD and Fmax).
4.1 Methodological considerations
The novel approach of the present study was to explore whether lower extremity neuromuscular function (comprehensively assessed with emphasis on RFD) could discriminate fallers from non-fallers in ambulatory pwMS. The main limitations were the exploratory, cross-sectional, and retrospective study design (i.e., limiting robustness of data as well as inference of causality), the relatively small sample size, the examination of one muscle group only, and the inclusion of ambulatory pwMS only. Regarding the sample size, since falls is so frequent in pwMS (55% of the enrolled pwMS had fallen in the past year), this seems to be a minor issue. Regarding the chosen muscle group (i.e., knee extensor), whilst this is a key muscle group related to ambulation (
) neuromuscular function of all major muscles around trunk, hip, knee, and ankle are theoretically associated with falls risk in pwMS. Lastly, the present study findings cannot be extrapolated to non-ambulatory pwMS (i.e., wheelchair and scooter users) as other falls risk factors may be prevailing for those populations (
). Altogether, the present study findings must be interpreted cautiously with the aspects outlined above in mind. Future studies should take these aspects into account.
4.2 Clinical implications and perspectives
From a clinical perspective, two aspects deserve specific mentioning. First, the findings of the present study suggest that routine assessment of lower extremity neuromuscular function (RFD in particular) may be a helpful tool in identifying (or even predicting) pwMS at future risk of falling. Whilst this would require specific equipment (i.e., a dynamometer), numerous commercially available options that are both reliable and valid exist. Moreover, the findings of the present study corroborate the potential of using lower extremity neuromuscular function (RFD as well as Fmax) as an important health indicator as well as outcome measure in interventions aimed at reducing falls, as previously proposed for pwMS (
Muscular strength as a predictor of all-cause mortality in an apparently healthy population: a systematic review and meta-analysis of data from approximately 2 million men and women.
Muscle-strengthening activities are associated with lower risk and mortality in major non-communicable diseases: a systematic review and meta-analysis of cohort studies.
). Second, identification of modifiable risk factors for falls is extremely useful in developing new and/or optimizing current counteractive strategies (e.g., rehabilitation and exercise). Regarding lower extremity neuromuscular function including both Fmax and RFD, these are influenced by daily physical activity levels in pwMS (following a dose-response pattern) (
). In support of this notion, daily physical activity levels (thigh-worn accelerometers, 7 days, summarized into counts per minute (CPM)) were lower in recurrent fallers vs. fallers vs. non-fallers (581 vs. 676 vs. 815 CPM, p<0.001; data not shown). This corroborates previous observations in pwMS (
), and emphasize the importance of maintaining a physical active lifestyle in pwMS despite living with a chronic progressive disease. Furthermore, the exercise modality resistance training is extremely potent in increasing Fmax and RFD (alongside walking capacity) in pwMS, especially when this is carried out with heavy loading and explosive/rapid muscle contractions (
Neuromuscular adaptations to long-term progressive resistance training translates to improved functional capacity for people with multiple sclerosis and is maintained at follow-up.
Is aerobic or resistance training the most effective exercise modality for improving lower extremity physical function and perceived fatigue in people with multiple sclerosis? A systematic review and meta-analysis.
). In relation to reducing the risk of falls and fall-related injuries such as fractures in pwMS, resistance training should thus be an integral part of the physical rehabilitation programs being offered to pwMS.
To provide further proof-of-concept, large-numbered and long-term prospective as well as interventional (i.e., resistance training) studies are needed to further our understanding of the association between lower extremity neuromuscular function (RFD in particular), falls, and fall-related injuries in pwMS. Ideally, this should be combined with other relevant risk factors for falls.
5. Conclusion
The findings of the present study revealed that knee extensor neuromuscular function can discriminate fallers from non-fallers in pwMS, with RFD being superior to Fmax. Routine assessment of lower extremity neuromuscular function (early phase RFD in particular) may be a helpful tool in identifying (or even predicting) pwMS at future risk of falling.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
CRediT authorship contribution statement
Nick M Kristensen: Conceptualization, Visualization, Formal analysis, Writing – original draft, Writing – review & editing, Data curation. Laurits Taul-Madsen: Conceptualization, Formal analysis, Visualization, Writing – original draft, Writing – review & editing, Data curation. Tobias Gaemelke: Conceptualization, Writing – original draft, Writing – review & editing, Data curation, Visualization. Morten Riemenschneider: Conceptualization, Writing – original draft, Writing – review & editing, Data curation, Visualization. Ulrik Dalgas: Conceptualization, Writing – original draft, Writing – review & editing, Data curation, Visualization. Lars G Hvid: Conceptualization, Visualization, Formal analysis, Writing – original draft, Writing – review & editing, Data curation.
Declaration of Competing Interest
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The author(s) received no financial support for the research, authorship, and/or publication of this article.
Acknowledgments
We like to thank the study participants for their role in the study.
You are as fast as your motor neurons: speed of recruitment and maximal discharge of motor neurons determine the maximal rate of force development in humans.
Muscular strength as a predictor of all-cause mortality in an apparently healthy population: a systematic review and meta-analysis of data from approximately 2 million men and women.
Objectively assessed physiological, physical, and cognitive function along with patient-reported outcomes during the first 2 years of Alemtuzumab treatment in multiple sclerosis: a prospective observational study.
Neuromuscular adaptations to long-term progressive resistance training translates to improved functional capacity for people with multiple sclerosis and is maintained at follow-up.
Muscle-strengthening activities are associated with lower risk and mortality in major non-communicable diseases: a systematic review and meta-analysis of cohort studies.
Is aerobic or resistance training the most effective exercise modality for improving lower extremity physical function and perceived fatigue in people with multiple sclerosis? A systematic review and meta-analysis.
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