Fatigue: Biomedicine, Health & Behavior - Volume 4, Issue 2, 2016

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Titles and abstracts for the journal, Fatigue: Biomedicine, Health & Behavior, Volume 4, Issue 2, 2016.

Volume 4, Issue 2, 2016[edit | edit source]

  • The biological challenge of myalgic encephalomyelitis/chronic fatigue syndrome: a solvable problem, Editorial by Jonathan C.W. Edwards, Simon McGrath, Adrian Baldwin, Mark Livingstone & Andrew Kewley. (FULL TEXT)
    Introduction - Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is comparable to multiple sclerosis, diabetes or rheumatoid arthritis in prevalence (∼0.2% to 1%), long-term disability, and quality of life,[1–5] yet the scale of biomedical research and funding has been pitifully limited, as the recent National Institutes of Health (NIH) and Institute of Medicine reports highlight. Recently in the USA, NIH Director Francis Collins has stated that the NIH will be ramping up its efforts and levels of funding for ME/CFS, which we hope will greatly increase the interest in, and resources for researching this illness. Despite scant funding to date, researchers in the field have generated promising leads that throw light on this previously baffling illness. We suggest the key elements of a concerted research programme and call on the wider biomedical research community to actively target this condition.[1]
  • Fatigue severity in World Trade Center (9/11) responders: a preliminary study.
    Abstract - Purpose: To assess fatigue severity in World Trade Center (9/11) responders 13 years later. Methods: The participant pool consisted of male 9/11 responders enrolled in the Stony Brook World Trade Center Health Program (WTC-HP), one of five centers of excellence established by the Centers for Disease Control and Prevention. Fatigue severity was assessed with the Fatigue Severity Scale. WTC-related medical conditions were certified by a physician and diagnoses of 9/11-related post-traumatic stress disorder (PTSD) and major depressive disorder (MDD) were determined with the Structured Clinical Interview for DSM-IV (SCID). Results: High fatigue severity was reported by 20.8% of the sample (N = 1079) and was significantly associated with PTSD, major depressive disorder, sleep apnea, gastro-esophageal reflux disease, upper respiratory disease, and lower respiratory disease. These associations remained significant for PTSD, major depressive disorder and lower respiratory disease when adjusted for medications, age and BMI. Only 17.3% of the high fatigue subgroup did not have an identified medical or psychiatric diagnosis. Fewer fatigued (21.1%) than non-fatigued (72.0%) responders rated their physical health as ‘good’ or ‘very good.’ Also fewer fatigued (33.9%) than non-fatigued (54.1%) responders were employed full-time (p < .0001). Conclusions: This study found clinically elevated fatigue in a high percentage of a male WTC responder cohort that prior to 9/11/2001 would be considered a ‘healthy worker cohort.’ To better understand the pathophysiology of fatigue, newer methodologies such as symptom provocation (e.g. exercise) designs may be useful.[2]
  • A comparative polysomnography analysis of sleep in healthy controls and patients with chronic fatigue syndrome
    Abstract - Background: Sleep disturbance affects almost 95% of people with chronic fatigue syndrome (CFS). However, existing studies of sleep in CFS have shown mixed results and methodological issues prevent between-study comparisons. Purpose: To redress this, the present study aimed to investigate whether there are differences in the sleep of patients with CFS and healthy controls, using a comparative analysis of polysomnography over three consecutive nights. Methods: Twenty-two patients with CFS (1994 Centers for Disease Control and Prevention criteria) and 22 healthy controls underwent three nights of polysomnographic sleep assessment. Groups were compared on their objective sleep variables derived from the third night of assessment, to allow for participant adaptation to the sleep study. Results: 9.1% of patients met criteria for an objectively verifiable sleep disorder. Differences in sleep were observed between CFS patients and healthy controls on four objectively derived sleep variables (wake after sleep onset, sleep efficiency, percentage wake and REM Latency). In addition, people with CFS reported more severe symptoms of insomnia than healthy controls. Conclusions: The study reports on key differences in sleep between people with CFS and healthy individuals. The potential presence of a sleep disorder in this patient population is high, it is therefore important that during early evaluation, a detailed history of sleep is taken to rule out a sleep disorder in CFS. In addition, patients with CFS show poorer sleep as defined by objectively derived measures and also self-report poorer quality sleep. Improving sleep is a potential treatment target in CFS.[3]
  • Polysomnographic and multiple sleep latency testing data in a large sample of patients with chronic fatigue syndrome and their relationship with subjective scores
    Abstract - Background: Despite the majority of patients with chronic fatigue syndrome (CFS) complaining about sleep disturbances and/or non-refreshing sleep, abnormalities in objective sleep parameters have not consistently been identified in this population. Purpose: To assess objective parameters of sleep and sleepiness in a large sample of patients with CFS and their relationship with the subjective dimensions of mental and physical health, sleep quality, daytime sleepiness and fatigue. Methods: Objective sleep parameters were derived from polysomnography (PSG) and multiple sleep latency testing (MSLT). Subjective scores for mental and physical health, sleep quality, daytime sleepiness and fatigue were based on validated, self-report questionnaires. Hierarchical multiple regression analysis was performed to predict sleepiness, global quality of sleep and fatigue. Results: PSG in 184 CFS patients indicated decreased total sleep time and sleep efficiency as well as increased sleep latency and waking after sleep onset. Only a few modest but significant correlations (r’s < .30) were found between objective parameters of sleep and sleepiness and subjective scores for health, sleep quality and fatigue. Conclusions: Objective sleep parameters indicated poor sleep in CFS, suggesting an insomnia phenotype, but with only modest associations to subjective scores of mental and physical health, sleep quality, daytime sleepiness and fatigue.[4]
  • Neural effect of physical fatigue on mental fatigue: a magnetoencephalography study
    Abstract - Background: Mental fatigue manifests as a reduced efficiency of cognitive workload and has become a significant cause of accidents. It is important to clarify the neural relationships between physical fatigue and mental fatigue. Purpose: We sought to clarify the neural effect of physical fatigue on mental fatigue using magnetoencephalography (MEG), with high temporal resolution and relatively high spatial resolution and classical conditioning techniques. Methods: Fourteen right-handed volunteers participated in this study. On the first experimental day, participants performed fatigue-inducing mental task trials for 30 min. Metronome sounds, started just after the beginning of the trials, were used as conditioned stimuli and the mental task trials were used as unconditioned stimuli to induce mental fatigue. On the next day, MEG was recorded under an eyes-closed condition with the metronome sounds for 3 min just before (control session) and after a 10-min fatigue-inducing physical task session. Subjective fatigue and motivation were rated on visual analogue scales. Results: In the left caudate, decreased alpha-band power in the physical fatigue session relative to the control session was found. The magnitude of the reduced power was positively associated with subjective level of motivation during the fatigue-inducing physical task session. Conclusion: These results suggest that physical fatigue suppressed activity in the left caudate via increased motivation to compensate for the effects of fatigue.[5]
  • The effect of obesity on central activation failure during ankle fatigue: a pilot investigation
    Abstract - Background: In a forward-directed oscillation, individuals who are obese may be at higher risk of falls due to weaker ankle dorsiflexor muscles as the prime controllers of the balance recovery. Muscle recovery may be negatively affected by fatigue at either the central (activation) and/or peripheral (contraction) levels. Additional body weight support, as required with obesity, may increase lower extremity muscle fatigue development. Purpose: The objective of this pilot study was to quantify the relationship between body mass index (BMI) and fatigue symptoms quantified as endurance time, torque loss, and central activation failure for the tibialis anterior. Methods: Twenty-two young males (mean BMI = 27.0 kg/m2; range: 20.5–36.7 kg/m2) completed maximum voluntary isometric contractions (MVICs) of the ankle dorsiflexors before (pre-MVIC) and after (post-MVIC) a sustained isometric fatiguing task at 60% of their strength. Electrical stimulation was superimposed during each MVIC to identify central activation failure. Results: Pre-fatigue central activation was equivalent across participants. However, BMI and pre-MVIC explained 59% of the variation in central activation failure after the fatiguing task as well as 29% of the variation in endurance time. In fact, a significant effect of obesity on central activation failure was observed with fatigue. Finally, 43% of the torque loss following fatigue variation was explained only with pre-MVIC. Conclusions: The findings of this pilot investigation indicate that endurance and central activation after fatigue may be impaired with increased BMI. This finding may aid in the evaluation of falls mechanisms and the development of falls prevention strategies.[6]

See also[edit | edit source]

References[edit | edit source]

  1. Edwards, JCW; McGrath, S; Baldwin, A; Livingstone, M; Kewley, A (Apr 2, 2016), "The biological challenge of myalgic encephalomyelitis/chronic fatigue syndrome: a solvable problem", Fatigue: Biomedicine, Health & Behavior, 4 (2): 63–69, doi:10.1080/21641846.2016.1160598 
  2. Friedberg, F.; Adamowicz, J.L.; Caikauskaite, I.; Napoli, A.; Shapira, 0.; Hobbs, M.; Bromet, E.; Kotov, R.; Gonzalez, A.; Clouston, S.; Luft, B. (2016), "Fatigue severity in World Trade Center (9/11) responders: a preliminary study", Fatigue: Biomedicine, Health & Behavior, 4 (2): 70-79, doi:10.1080/21641846.2016.1169726 
  3. Gotts, Z.M.; Dearya, V.; Newton, Julia L.; Ellis, J. G. (2016), "A comparative polysomnography analysis of sleep in healthy controls and patients with chronic fatigue syndrome.", Fatigue: Biomedicine, Health & Behavior, 4 (2): 80-93, doi:10.1080/21641846.2016.1167470 
  4. Tobback, E., Mariman, A., Hanoulle, I. P., Delesie, L., Vogelaers, D., & Pevernagie, D. (2016). Polysomnographic and multiple sleep latency testing data in a large sample of patients with chronic fatigue syndrome and their relationship with subjective scores. Fatigue: Biomedicine, Health & Behavior, 4 (2):94-103. doi:10.10.1080/21641846.2015.1106176
  5. Tanaka, M., Ishii, A., & Watanabe, Y. (2016). Neural effect of physical fatigue on mental fatigue: a magnetoencephalography study. Fatigue: Biomedicine, Health & Behavior, 4 (2), 104-114. doi:10.1080/21641846.2016.1167471
  6. Pajoutan, M., Mehta, R. K., & Cavuoto, L. A. (2016). The effect of obesity on central activation failure during ankle fatigue: a pilot investigation. Fatigue: Biomedicine, Health & Behavior, 4(2):115-126. doi:10.1080/21641846.2016.1175178

Myalgic encephalomyelitis or chronic fatigue syndrome, often used when both illnesses are considered the same.

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