Background
Multiple sclerosis (MS) is the most prevalent progressive and chronic disabling neurologic disease that affects the central nervous system (CNS) through demyelination, inflammation, and axonal loss [
1,
2]. In 2020, MS was estimated to affect up to 2.8 million people worldwide with a significant impact on physical, emotional, social, and cognitive functioning [
3,
4]. MS exhibits varying symptoms depending on the affected region, encompassing cerebellar, motor, sensory, emotional, and sexual manifestations [
5]. Among the many symptoms associated with MS, fatigue has been identified as a significant concern, with up to 50–60% of patients experiencing this symptom [
5]. In addition to the limitation in MS individuals’ activities of daily living and social lives from fatigue, it also hurts cognitive functions, decreasing attention and concentration [
6]. In some disorders like MS, fatigue may be associated with motor and, or mood disorders, so it is challenging and sometimes impossible to determine whether fatigue is an aspect of these features or a symptom [
7]. Fatigue physiologically is defined as “the inability of a muscle or group of muscles to sustain the required or expected force” by Bigland-Ritchie et al. [
8]. Fatigue may occur from failure at force-generating capacity within the muscle itself (peripheral fatigue), or because of a disability to maintain the central drive to spinal motor neurons (central fatigue) [
7].
Also, impaired balance is typically the primary symptom of MS, and it arises from a combination of slowed somatosensory conduction and impaired central integration [
9] which cause abnormal gait control, and many fall frequently [
10‐
14]. In this aspect, MS can potentially impact the entire CNS, resulting in various impairments in neurological functions [
11]. Integrating various sensorimotor modalities, including visual, vestibular, and proprioceptive information, plays a significant role in postural control (PC) and sustaining an upright stance [
15,
16]. These complex sensorimotor processes contribute to regulating body sway and facilitate coordinated movement patterns that maintain the center of mass within the limits of stability. Therefore, Understanding how different sensory inputs interact and contribute to PC is essential to developing interventions that can improve balance and prevent falls in vulnerable populations [
15,
16]. Due to the presence of impairments in multiple processes, individuals with MS tend to exhibit weaker PC, as indicated by greater amounts of postural sway when compared to healthy controls [
11,
12,
17,
18].
According to a recent systematic review study, individuals with MS experienced a positive impact on their fatigue levels as a result of sensory integration-based interventions. This led to improved balance and an overall increase in their quality of life. These findings may have important implications for managing symptoms and improving outcomes for individuals with MS [
19]. Also, brain structural and functional alterations are seen in MS-related fatigue [
20]. Particularly, sensorimotor network impairment and abnormal activation of the thalamus are associated with fatigue.
To date, no systematic review has synthesized the available data on the effect of fatigue on the PC of individuals with MS. By providing a comprehensive evaluation of existing research, this review aimed to address this knowledge gap and shed light on the relationship between fatigue and PC in this population.
Discussion
This systematic review aimed to investigate whether there is a relationship between fatigue and PC in individuals with MS. The current literature on the impact of fatigue on PC in individuals with MS is limited. Tasks that induce fatigue have been shown to negatively affect PC in individuals with MS [
27‐
31]. This observation is consistent with previous research highlighting the negative impact of fatigue on various aspects of motor function in individuals with MS. There are several possible reasons for this finding which will be argued in the following paragraphs.
By reviewing the methodological quality of included studies, a large amount of lack of loss to follow-up was noted [
27‐
31], and may not have distinguished all possible causes of missing follow-up data which entailed a risk of bias. Also, while this was an exploratory study, and we evaluated factors that predicted loss to follow-up, it is still possible that bias may have been introduced due to loss to follow-up. Additionally, it is essential to note that all of the included articles in our systematic review lacked blinding [
27‐
31]. Lack of blinding in a study can introduce biases in various ways, depending on who remains unblinded among the study’s participants. Individuals assigned to the experimental group may have more positive expectations or report better outcomes to appease treatment providers. In contrast, those in the control group may have lower expectations and report poorer outcomes [
36]. Thus, implementing blinding protocols where possible in research studies examining fatigue in MS can improve the quality and reliability of study results.
Fatigue severity in MS may depend on several clinical factors, including the number of years since onset, the specific MS subtype, the level of baseline disability, and the degree of disease activity. To address these factors, we compared the included studies in terms of the level of disability, MS subtype, and disease duration. The included studies revealed a wide range of disability levels, as measured by the Expanded Disability Status Scale (EDSS), with scores ranging from 1 to 6, 0–4, 3–5, 1.5-6, and 2–6 [
27‐
31]. The comparison of PC in MS patients with EDSS scores less than 2.5, indicating minimal impairment in functional subsystems, with healthy groups, using criteria such as sway area, velocity, and displacement of the center of pressure, demonstrates that their ability to maintain PC is similar to that of healthy individuals [
37]. However, as the degree of disability increases, significant differences are observed between the more severely affected MS patients and those with only mild or moderate disability [
38]. Hence, a wide range of EDSS of included studies may be considered as a confusing factor regarding the expression and progression of fatigue related to the PC. Also, different types of MS, including relapsing-remitting MS, secondary progressive MS, and primary progressive MS [
39], may play a role in the various results observed during PC evaluation with fatigue. In this regard, cognitive-postural interference was found to be more pronounced in SPMS patients, as they exhibited a higher dual-task cost compared to those with RRMS and healthy controls [
40]. This indicates a greater impact on PC when comparing different types of MS.
Disability progression in MS appears to be linked to heightened fatigue and PC issues. Motl et al. [
41] found that higher levels of disability were significantly correlated with increased fatigue in individuals with MS. Another study by Prosperini et al. [
42] demonstrated that disability progression was associated with worsening PC, as measured by the Berg Balance Scale. These findings are consistent with those of Karpatkin et al. [
29] whose study also employed the Berg balance scale score. Hence, it is crucial to manage disability progression to mitigate the impact on fatigue and PC problems in individuals with MS. While it is recommended that individuals with MS engage in regular physical activity, such as walking, to improve their quality of life, it is important to note that disability progression may still occur even in the absence of relapses. However, they often engage in less physical activity due to increased fatigue, mobility impairment, and fear of falling after a previous fall [
28]. Furthermore, the included studies identified other factors that may contribute to PC impairment in individuals with MS, such as gender differences [
27] and lower leg muscle function [
28]. These factors should be considered when assessing PC in individuals with MS, as they may require different management strategies..
Accuracy and reliability of physician outcomes versus patient-reported outcomes is another important topic to consider. Physicians may not always be aware of the full extent of a patient’s symptoms, particularly if the patient does not report them or if the physician does not ask about them specifically [
43]. Patient-reported outcomes provide a more direct measure of the patient’s experience of their symptoms and the impact of various interventions on their quality of life [
43]. Patients may be more likely to report symptoms that are not easily observable by physicians, such as fatigue or cognitive difficulties [
44]. However, patient-reported outcomes may also be influenced by factors such as mood, anxiety, or other comorbidities that could affect their perception of their symptoms [
44]. In this regard, the Fatigue Scale for Motor and Cognitive Functions Questionnaire demonstrates high sensitivity and specificity in detecting fatigue in patients with MS (Cronbach’s alpha a > 0.91 and test–retest reliability r > 0.80 [
45]. The Visual Analogue Scale of Fatigue exhibits a strong correlation with the physical aspects of fatigue. While its reliability has been established for various conditions, it has not been specifically examined in the context of MS [
46,
47]. The Fatigue Severity Scale is a widely used tool in both clinical and research settings to measure the severity of fatigue and identify distinguishing features between two chronic medical disorders [
48]. All of the included studies utilized Patient-reported outcomes, which can enhance the accuracy and reliability of data, facilitating the derivation of significant conclusions from various research findings..
The mechanism underlying postural instability in individuals with MS is a multifaceted process involving various factors. These factors include impaired lower leg muscle function [
28], compromised PC [
31], and an increased risk of falls [
29]. Fatigue in MS patients is often associated with motor exertion, which can lead to decreased performance on balance scales and increased postural sway [
27,
30]. Gender differences were inconclusive in the context of a fatiguing task’s impact on PC in individuals with MS [
27]. In addition to task complexity, vision, and symptomatic fatigue [
31], another mechanism that contributes to postural instability in MS patients is the sensorimotor mechanism. Fatigue affects the performance of individuals with MS on the Berg Balance Score [
29], a measure of balance. Maintaining balance relies on the integration of sensorimotor information [
49], which involves combining sensory input with motor output for coordinated movement [
50]. Also, muscle fatigue can disrupt the central perception system, leading to a lack of motor control and an increased risk of falls. Individuals with MS often have deficient sensory systems and rely more on vision to maintain their postural balance [
31]. In this regard, CNS lesions in MS can impact sensory and motor function, leading to sensory loss and fatigue, which may contribute to poor balance control [
31]. Moreover, in the context of the sensorimotor mechanism, lower leg muscle function becomes a crucial target for intervention to improve gait, balance, and fall risk among individuals with MS [
28]. This is because muscle fatigue can be divided into central and peripheral components, with central fatigue originating in the CNS and peripheral fatigue occurring at or distal to the neuromuscular junction [
51,
52]. Individuals with MS experience a greater level of peripheral muscle fatigue while walking compared to those who are healthy [
53]. This may be why walking tests, such as the 6MWT, are commonly used in MS research to assess walking fatigue due to their reliability and validity [
54]. Therefore, it appears that the primary issue is related to peripheral muscle fatigue. Understanding these mechanisms is crucial for developing effective interventions to improve postural stability and reduce the risk of falls in individuals with MS.
The strength of this systematic review lies in its adherence to the PRISMA guidelines, which ensure the use of optimal methods for conducting and reporting systematic reviews. However, there are some limitations to consider. The heterogeneity in disability levels and progression among individuals with MS can introduce a significant risk of bias. This is because the included studies may not adequately represent the entire MS population, particularly in terms of disability severity and progression. Another limitation of the studies included in the investigation is that they utilized different drugs, such as antifatigue drugs [
29,
31] or fampridine [
30]. This variation in medication could have influenced the severity of fatigue or the walking speed, resulting in inconsistent outcomes in terms of PC in individuals with MS who are dealing with fatigue. Furthermore, the fair methodological quality of the included studies may also increase the risk of bias, as these studies may have limitations that affect the reliability and validity of their findings.
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