Fatigue is commonly reported in many neurologic illnesses, including multiple sclerosis, Parkinson disease, myasthenia gravis, traumatic brain injury, and stroke. Fatigue contributes substantially to decrements in quality of life and disability in these illnesses. Despite the clear impact of fatigue as a disabling symptom, our understanding of fatigue pathophysiology is limited and current treatment options rarely lead to meaningful improvements in fatigue. Progress continues to be hampered by issues related to terminology and assessment. In this article, we propose a unified taxonomy and a novel assessment approach to addressing distinct aspects of fatigue and fatigability in clinical and research settings. This taxonomy is based on our current knowledge of the pathophysiology and phenomenology of fatigue and fatigability. Application of our approach indicates that the assessment and reporting of fatigue can be clarified and improved by utilizing this taxonomy and creating measures to address distinct aspects of fatigue and fatigability. We review the strengths and weaknesses of several common measures of fatigue and suggest, based on our model, that many research questions may be better addressed by using multiple measures. We also provide examples of how to apply and validate the taxonomy and suggest directions for future research.

Fatigue and fatigability in neurologic illnesses: Proposal for a unified taxonomy

Fatigue is a common disabling symptom of multiple sclerosis (MS). It is often considered a state of exhaustion distinct from depressed mood or physical weakness. Fatigue can be assessed by either self-report scales or performance-based measures; however, neither method captures all features of fatigue. Fatigue in MS frequently leads to unemployment. It is associated with a sense of loss of control over one's environment, low positive affect, psychological distress and neurological impairment. To date there is no reproducible neuroimaging marker or biological correlate that has been identified. Proposed pathological mechanisms of fatigue in MS include neuronal factors such as dysfunction of premotor, limbic, basal ganglia or hypothalamic areas; disruption of the neuroendrocrine axis leading to low arousal; alteration in serotoninergic pathways; changes in neurotransmitter levels; and altered CNS functioning caused by a disruption of the immune response. Treatment of fatigue is best approached in a multidisciplinary fashion that incorporates nonpharmacological interventions as well as medication. Amantadine and modafinil are among the most commonly used medications for fatigue associated with MS. Both medications have been studied with positive results in controlled clinical trials. Additional research towards measurement and pathogenesis of fatigue will hopefully lead to improved therapies.

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Fatigue in Multiple Sclerosis

Predicting quality of life in multiple sclerosis: accounting for physical disability, fatigue, cognition, mood disorder, personality, and behavior change.

Objectives – In a series of 504 patients with multiple sclerosis (MS), quality of life (QOL) and its main clinical and demographic determinants were assessed in comparison with healthy individuals.

Materials and methods – A postal questionnaire with self-completed measures of disability (Expanded Disability Status Scale, EDSS), QOL (Quality of Life Index, QLI), depressive mood (Self-rating Depression Scale, SDS), fatigue severity (Fatigue Severity Scale, FSS) and sleep quality (Pittsburgh Sleep Quality Index, PSQI) was sent to this sample of MS patients.

Results – Most patients were severely disabled; almost half were mildly to severely depressed, suffering from reduced sleep quality and/or fatigue. The multiple sclerosis patients had significantly lower QLI scores than healthy controls. EDSS and SDS scores were found to be predictors of global QLI score. Regarding the different QLI domains, mean SDS scores remained predictive for all QLI items, while mean EDSS, PSQI and FSS scores were only predictive for physical domains.

Conclusion – Our study clearly demonstrates that depressive mood is the main factor influencing QOL. The disability status, fatigue and reduced sleep quality have an impact mainly on physical domains of life quality.

Factors influencing quality of life in multiple sclerosis patients: disability, depressive mood, fatigue and sleep quality

Background:Psychiatric comorbidity is associated with lower quality of life, more fatigue, and reduced adherence to disease-modifying therapy in multiple sclerosis (MS).Objectives:The objectives of...

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The incidence and prevalence of psychiatric disorders in multiple sclerosis: A systematic review

This study deals with the assessment of quality of life and its main clinical and demographical determinants in a clinical series of 103 patients with multiple sclerosis (MS) (37 men; 66 women; mean age 44.89 years; mean disease duration 12.40 years; mean EDSS score 4.07). We used the MSQOL-54 inventory, a disease-specific instrument recently validated in an Italian population. Each patient underwent a complete clinical assessment, including that of disability status (Expanded Disability Status Scale), cognitive function (Mini Mental State Examination), depression (Hamilton Rating Scale for Depression) and fatigue (Fatigue Severity Scale). In terms of Pearson's correlations, there was a moderate inverse relationship between disability level and the MSQOL-54 physical composite score, and a moderate to strong inverse correlation between depression or fatigue severity and both the physical and mental composite scores. In a stepwise linear regression analysis, depression, fatigue and disability level were confirmed to be significant and independent predictors of quality of life. Quality of life instruments can help to provide a broader measure of the disease impact and to develop a care program tailored to the patient's needs.

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Papers

Quality of life in multiple sclerosis: the impact of depression, fatigue and disability