Fatigue and cognitive fatigability in patients with chronic pain

OBJECTIVES

Fatigue is common in patients with chronic pain. Still, there is a lack of studies examining objectively measurable cognitive aspects of fatigue: cognitive fatigability (CF). We aimed to investigate the presence of CF in patients with chronic pain and its relation to self-rated fatigue, attention, pain characteristics, sleep disturbance, depression, and anxiety.

METHODS

Two hundred patients with chronic pain and a reference group of 36 healthy subjects underwent a comprehensive neuropsychological test battery, including measurement of CF with the Wechsler Adult Intelligence Scale-III Coding subtest, and self-assessment of trait and state fatigue.

RESULTS

The patients with chronic pain did not show more CF as compared to the reference group. There was an association between CF and processing speed on a test of sustained and selective attention in the chronic pain group, while self-rated fatigue measures and pain characteristics were not associated with CF. Self-rated fatigue measures were highly correlated with self-rated pain intensity, spreading of pain, depression, anxiety, and sleep disturbance.

CONCLUSIONS

The findings highlight the distinction between objective and subjective aspects of fatigue in chronic pain, and that the underlying causes of these different aspects of fatigue need to be studied further.

Validation of Discrete and Regression-Based Performance and Cognitive Fatigability Normative Data for the Paced Auditory Serial Addition Test in Multiple Sclerosis

Cognitive fatigability is an objective performance decrement that occurs over time during a task requiring sustained cognitive effort. Although cognitive fatigability is a common and debilitating symptom in multiple sclerosis (MS), there is currently no standard for its quantification. The objective of this study was to validate the Paced Auditory Serial Addition Test (PASAT) discrete and regression-based normative data for quantifying performance and cognitive fatigability in an Ontario-based sample of individuals with MS. Healthy controls and individuals with MS completed the 3″ and 2″ versions of the PASAT. PASAT performance was measured with total correct, dyad, and percent dyad scores. Cognitive fatigability scores were calculated by comparing performance on the first half (or third) of the task to the last half (or third). The results revealed that the 3″ PASAT was sufficient to detect impaired performance and cognitive fatigability in individuals with MS given the increased difficulty of the 2″ version. In addition, using halves or thirds for calculating cognitive fatigability scores were equally effective methods for detecting impairment. Finally, both the discrete and regression-based norms classified a similar proportion of individuals with MS as having impaired performance and cognitive fatigability. These newly validated discrete and regression-based PASAT norms provide a new tool for clinicians to document statistically significant cognitive fatigability in their patients.

Does Intensive Training of Attention Influence Cognitive Fatigability in Patients With Acquired Brain Injury?

Research Objectives

Impairments in attention and the speed of information processing are central to the experience of cognitive fatigue in patients with acquired brain injury (ABI). Attention may be improved through intensive training in a rehabilitation setting. The aim of the study was to investigate the feasibility of reducing cognitive fatigability (CF) using attention training and to explore the effect of two different approaches to attention training.

Design

Randomised controlled study in a rehabilitation setting.

Participants

59 patients (age 19-59 years) with mild to moderate stroke or traumatic brain injury in the early (<4 month) phase.

Interventions

Patients were randomly assigned to intensive specific training with Attention Process Training (APT) or Activity-Based Attention Training (ABAT) for 3-5 days per week for a period of 5-6 weeks with a total of 20 h, in addition to traditional interdisciplinary rehabilitation.

Main Outcome Measure

CF was conceptualised as performance decline in terms of an increased number of incorrect responses between the first and the last quintiles of the Paced Auditory Serial Addition Test (PASAT). A negative result was defined as fatigability. The evaluator of fatigability was blinded to treatment.

Results

At baseline, there were no differences between the groups in age, education, reasoning, anxiety or depression. After training, a significant treatment effect was found (p = 0.020), as the APT-group, but not the ABAT-group, had improved. However, after controlling for baseline differences regarding CF on the PASAT-f, the difference was no longer significant.

Conclusion

The results indicate that cognitive training might be a feasible method for reducing CF through attention training and that patients with high levels of CF benefit most from attention training. The type of intervention provided, whether specific or activity-based attention training, appears to be of less importance, as there was no treatment effect after controlling for the baseline level of CF. Future studies are required to confirm the validity of the findings.

Cognitive fatigability is a quantifiable distinct phenomenon in multiple sclerosis

Cognitive fatigability in multiple sclerosis represents the decrease in cognitive performance over time. It is a frequent symptom that negatively affects quality of life and ability to work. There are no objective measures of cognitive fatigability. This study aimed at quantifying cognitive fatigability despite the learning effect and to clarify whether cognitive fatigability represents a free-standing phenomenon rather than an aspect of cognitive impairment. We measured information processing speed with the Symbol Digit Modalities Test, and the number of right answers was recorded every 30 s for 180 s. We approximated the number of right answers as function of time with two logarithmic models, one including a first-order term alone and the other adding also a second-order term. The coefficient of the latter (B) may quantify performance deflection and may represent cognitive fatigability. We tested 173 patients with multiple sclerosis, including 119 cognitively impaired and 54 cognitively preserved patients, and 35 healthy subjects. The performance of cognitively preserved patients showed a deflection at the end of task that was detected neither in controls nor in cognitively impaired patients and needed a second-order term to be approximated (p < .03, F = 14.02). B was explained neither by depression nor fatigue. We proposed for the first time a method to quantify cognitive fatigue via a second-order least square fit model, easily usable in the clinical practice. By using this novel approach, cognitive fatigability results to be a free-standing phenomenon that is more evident in cognitively preserved than in cognitive impaired patients.

Task-Based Cognitive Fatigability for Older Adults and Validation of Mental Fatigability Subscore of Pittsburgh Fatigability Scale

Cognitive fatigue and cognitive fatigability are distinct constructs. Cognitive fatigue reflects perception of cognitive fatigue outside of the context of activity level and duration and can be reliably assessed via established instruments such as the Fatigue Severity Scale (FSS) and the Modified Fatigue Impact Scale (MFIS). In contrast, cognitive fatigability reflects change in fatigue levels quantified within the context of the level and duration of cognitive activity, and currently there are no reliable measures of cognitive fatigability. A recently published scale, the Pittsburgh Fatigability Scale (PFS), attempts to remedy this problem with a focus on the aged population. While the physical fatigability subscore of PFS has been validated using physical activity derived measures, the mental fatigability subscore of PFS remains to be tested against equivalent measures derived from cognitive activities. To this end, we recruited 35 older, healthy adult participants (mean age 73.77 ± 5.9) to complete the PFS as well as a prolonged continuous performance of a Stroop task (>2 h). Task-based assessments included time-on-task changes in self-reported fatigue scores (every 20 min), reaction time, and pupil diameter. Defining subjective fatigability, behavioral fatigability, and physiologic/autonomic fatigability to be the slope of change over time-on-task in the above three assessed variables, we found that the PFS mental subscore was not correlated with any of the three task-based fatigability measures. Instead, the PFS mental subscore was correlated with trait level fatigue measures FSS (ρ = 0.63, p < 0.001), and MFIS cognitive subsection (ρ = 0.36, p = 0.03). This finding suggested that the PFS mental fatigability subscore may not be an adequate measure of how fatigued one becomes after a given amount of mental work. Further development efforts are needed to create a self-report scale that reliably captures cognitive fatigability in older adults.

The relationship between fatigability and sleep quality in people with multiple sclerosis

BACKGROUND

Perceived fatigue and fatigability are constructs of multiple sclerosis (MS)-related fatigue. Sleep disturbances lead to poor sleep quality, which has been found to be associated with perceived fatigue in people with MS (PwMS). However, the relationship between fatigability and sleep quality is unknown.

OBJECTIVE

To explore the relationship between physical and cognitive fatigability with self-reported and objective measures of sleep quality in PwMS.

METHODS

Fifty-one ambulatory PwMS participated in the study. Physical fatigability was measured by percent-change in meters walked on the six-minute walk test (6MWT) and in force exerted on a repeated maximal hand grip test. Cognitive fatigability was measured using response speed variability on the continuous performance test. Self-report sleep quality was measured using the Pittsburgh Sleep Quality Index, and objective sleep quality was measured using 1 week of actigraphy.

RESULTS

Components of the Pittsburgh Sleep Quality Index and several actigraph parameters were significantly associated with physical fatigability and cognitive fatigability. However, controlling for depression eliminated the association between the sleep outcomes and cognitive fatigability and attenuated the association between the sleep outcomes and physical fatigability.

CONCLUSION

Poor sleep quality is related to fatigability in MS but depression appears to mediate these relationships.