Investigating post-stroke fatigue: An individual participant data meta-analysis

Cumming, Toby; Yeo, Ai Beng; Marquez, Jodie; Чурилов, Леонид; Annoni, Jean Marie; Badaru, Umaru Muhammad; Ghotbi, Nastaran; Harbison, J.; Kwakkel, Gert; Lerdal, Anners; Mills, Roger; Næss, Halvor; Nyland, Harald; Schmid, Arlene A.; Tang, Wai Kwong; Tseng, B.; Port, Ingrid van de; Mead, Gillian; English, Coralie

doi:10.1016/j.jpsychores.2018.08.006

Cited by 46 publications

(43 citation statements)

References 46 publications

(88 reference statements)

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“…In contrast to a recent meta‐analysis (Cumming et al, 2018), our results showed no change in fatigue over time. However, it is worth noting that only 27 of the 47 participants with fatigue at inclusion were still fatigued at 18 months, indicating that about 40% improve from fatigue while almost the same amount became fatigued over time.…”

Section: Discussioncontrasting

confidence: 99%

“…However, it is worth noting that only 27 of the 47 participants with fatigue at inclusion were still fatigued at 18 months, indicating that about 40% improve from fatigue while almost the same amount became fatigued over time. Physical deconditioning and a negative cycle of inactivity have been suggested as potential reasons for the increasing number of people suffering from post‐stroke fatigue (Cumming et al, 2018). The activity data in the present study showed that participants spent 10% less time on sedentary behaviour and 15% more time standing compared to findings among people with stroke in previous studies (Fini, Holland, Keating, Simek, & Bernhardt, 2017; Janssen et al, 2010; Mudge, Barber, & Stott, 2009).…”

Section: Discussionmentioning

confidence: 99%

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Fatigue and activity after stroke. Secondary results from the Life After Stroke study

Braaten

Askim

Gunnes

et al. 2020

Physiotherapy Res Intl

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Objectives: The aim of this study was to describe how the prevalence of fatigue changed from the subacute phase to the chronic phase after stroke, and to investigate how activity was associated with fatigue among participants included in the randomized controlled multicentre-study Life After STroke (LAST). Methods: The present study represents secondary analysis based on data from the LAST study. One-hundred-and-forty-five patients with mild and moderate stroke (mean (SD) age: 71.5 (10.5) years, 57.2% males) recruited from St. Olav's University Hospital were included. Fatigue was assessed by the Fatigue Severity Scale (FSS-7) at inclusion, 3 months after stroke, and at follow-up 18 months later. activPAL was used to measure activity at follow-up. Results: A total of 46 (31.7%) participants reported fatigue at inclusion and 43 (29.7%) at follow-up (p = .736). In the univariable regression analysis, sedentary behaviour, walking and sedentary bouts were significantly associated with fatigue (p ≤ .015), whereas only time spent walking was significantly associated with fatigue in the multivariable regression analysis (p = .017). Conclusions: The present study showed that fatigue is a common symptom after stroke and that the prevalence of fatigue remained unchanged from the subacute to the chronic phase. The study also showed that increased time spent walking was strongly related to lower fatigue, while no such associations were found between the other activity categories and fatigue.

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Section: Discussioncontrasting

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Fatigue and activity after stroke. Secondary results from the Life After Stroke study

Braaten

Askim

Gunnes

et al. 2020

Physiotherapy Res Intl

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“…The association seen between fatigue and the anxiety and depression subscales of HADS is not surprising. There is significant overlap between affective symptoms in neurological disorders (Cumming et al, 2018;De Doncker et al, 2018), suggesting that fatigue, anxiety and depression may share common underlying mechanisms resulting in a cluster of symptoms (Ayache and Chalah, 2019). This is also evident from similar findings of lower corticospinal excitability in the left hemisphere of patients with clinical depression (Lefaucheur et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

Role of left motor cortex in post-stroke fatigue: a corticospinal excitability study

Doncker

Kuppuswamy

2020

Preprint

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BackgroundThe neural mechanisms that underlie post-stroke fatigue are poorly understood. Previous work show an inverse relationship between motor cortex excitability and post-stroke fatigue, however, it is unclear if the side of lesion influences this relationship. The left hemisphere plays a dominant role in motor control, therefore we hypothesised that left hemisphere strokes are more likely to show a significant inverse relationship between corticospinal excitability and fatigue.MethodsResting motor threshold (measure of corticospinal excitability) using transcranial magnetic stimulation was measured in the affected hemisphere of 98 stroke survivors. Fatigue was measured using the fatigue severity scale. The effect of fatigue and hemisphere affected on corticospinal excitability was analysed using a multiple linear regression.ResultsA multiple linear regression with trait fatigue as the outcome variable (F(4,93)=12.04, p < 0.001, adj R2 = 0.313) revealed that RMT was not a significant predictor of FSS-7 (β = −0.063, p = 0.706, CI[-0.394, 0.268]), while the interaction between lesioned hemisphere and RMT was a significant predictor of FSS-7 (β = 0.339, p = 0.039, CI[0.018, 0.659]). The additional explanatory variables of HADSDepression and sex were also significant predictors of FSS-7 (β = 903, p < 0.001, CI[0.584, 1.223] and β = 1.127, p = 0.002, CI[0.425, 1.830] respectively).ConclusionLower corticospinal excitability of the left hemisphere may indicate altered perception of effort and reduced sensory attenuation. This provides evidence to support the sensory attenuation model of fatigue.

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“…Persistent PSF can be highly distressing, negatively impacting quality of life (de Bruijn et al, 2015; Naess, Waje-Andreassen, Thomassen, Nyland, & Myhr, 2006) and preventing social participation and attendance to rehabilitation programs (Nadarajah & Goh, 2015). PSF is associated with both poor functional outcome and increased mortality (Glader, Stegmayr, & Asplund, 2002), and a recent meta-analysis revealed that the prevalence increases with time since stroke (Cumming et al, 2018). Early detection, prevention and treatment of fatigue might thus have positive effects on the overall outcome of stroke rehabilitation and quality of life.…”

Section: Introductionmentioning

confidence: 99%

“…Depression is the most consistently correlated factor (Ponchel, Bombois, Bordet, & Hénon, 2015; Wu, Barugh, Macleod, & Mead, 2014), and, although PSF is generally conceptualized as an independent condition, the nature of the relationship between fatigue and depression has been debated. Although efforts have been made to disentangle the two (Douven et al, 2017; Høgestøl et al, 2019; Kunze, Zierath, Drogomiretskiy, & Becker, 2014), the clinical overlap is substantial (Cumming et al, 2018). The use of advanced brain imaging to detect the brain correlates of the two clinical syndromes may facilitate our understanding of the phenomena through identification of both common and specific brain mechanisms (Høgestøl et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Brain disconnectivity mapping of post-stroke fatigue

Richard

et al. 2020

Preprint

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Stroke patients commonly suffer from post stroke fatigue (PSF). Despite a general consensus that brain perturbations constitute a precipitating event in the multifactorial etiology of PSF, the specific predictive value of conventional lesion characteristics such as size and localization remain unclear. The current study represents a novel approach to assess the neural correlates of PSF in chronic stroke patients. While previous research has focused primarily on lesion location or size, with mixed or inconclusive results, we targeted the extended structural network implicated by the lesion, and evaluated the added explanatory value of a disconnectivity approach with regards to the brain correlates of PSF. To this end, we estimated individual brain disconnectome maps in 84 stroke survivors in the chronic phase (≥ 3 months post stroke) using information about lesion location and normative white matter pathways obtained from 170 healthy individuals. PSF was measured by the Fatigue Severity Scale (FSS). Voxel wise analyses using non-parametric permutation-based inference were conducted on disconnectome maps to estimate regional effects of disconnectivity. Associations between PSF and global disconnectivity and clinical lesion characteristics were tested by linear models, and we estimated Bayes factor to quantify the evidence for the null and alternative hypotheses, respectively. The results revealed no significant associations between PSF and disconnectome measures or lesion characteristics, with moderate evidence in favor of the null hypothesis. These results suggest that symptoms of post-stroke fatigue are not simply explained by lesion characteristics or brain disconnectome measures in stroke patients in a chronic phase, and are discussed in light of methodological considerations.

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Investigating post-stroke fatigue: An individual participant data meta-analysis

Abstract: Use of IPD meta-analysis gave us the power to identify novel factors associated with fatigue, such as longer time since stroke, as well as a non-linear relationship with age.

Cited by 46 publications

References 46 publications

Fatigue and activity after stroke. Secondary results from the Life After Stroke study

Fatigue and activity after stroke. Secondary results from the Life After Stroke study

Role of left motor cortex in post-stroke fatigue: a corticospinal excitability study

Brain disconnectivity mapping of post-stroke fatigue

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