Prevalence, Trajectory, and Predictors of Poststroke Fatigue among Ghanaians

Sarfo, Fred Stephen; Berchie, Patrick; Singh, Arti; Nichols, Michelle; Agyei-Frimpong, Maria; Jenkins, Carolyn; Ovbiagele, Bruce

doi:10.1016/j.jstrokecerebrovasdis.2019.02.002

Cited by 26 publications

(16 citation statements)

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“…The most failed criterion was appropriate sampling as only two papers had a representative sample, with either a population-based or randomised sample, whereas the majority had a consecutive sampling. 37,38 All studies reported a cut-off point of four or more to identify fatigued participants. There was only one study that exclusively included participants with severe fatigue and reported a PSF prevalence of 92%, as a result, it was not included in the final quantitative synthesis.…”

Section: Resultsmentioning

confidence: 99%

Prevalence of fatigue after stroke: A systematic review and meta-analysis

Alghamdi

Ariti

Williams

et al. 2021

European Stroke Journal

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Background and Purpose Post-stroke fatigue is a debilitating and long-lasting condition. However, there are uncertainties regarding its prevalence and variability between studies. This review aims to estimate the prevalence of fatigue and determine the factors responsible for its variation in the literature. Methods A systematic review was conducted for all published studies (search to November 2020) using AMED, CINAHL, EMBASE, MEDLINE, PsycINFO, SCOPUS and Web of Science. Papers were included if they recruited participants with stroke, used a validated scale to measure fatigue and were in English. Two reviewers screened and assessed the relevant studies for eligibility ( n = 96). The included papers were appraised using the Joanna Briggs Institute (JBI) tool for prevalence studies, and data were extracted by one reviewer. To understand the variation in PSF prevalence between papers, data were pooled and analysed based on relevant methodological (e.g. time of assessment) or clinical factors (e.g. depression) using Review Manager 5.4 software. Results While 48 studies were included and summarised ( N = 9004), only 35 were appropriate for the meta-analysis ( N = 6851). The most frequently used tool to measure fatigue was the Fatigue Severity Scale (FSS) ( n = 31). The prevalence was calculated with a cut-off point of four or more using FSS and resulted in an estimate of 48% (95% CI 42–53%). Time of assessment (<6 vs ≥6 months), stroke type (ischaemic vs haemorrhagic/subarachnoid haemorrhage) and geographical location (East Asia vs Europe) could explain the prevalence variation between studies. Conclusions Fatigue is prevalent among stroke survivors. This condition varies in terms of occurrence between studies; however, time of assessment, stroke type and geographical location might explain this variation. As this review estimates the overall burden of fatigue after stroke, it provides a useful indicator to inform policy, planning and healthcare professionals. Further efforts are required to investigate the mechanisms that lead to PSF, particularly in the groups that show high prevalence, in order to prevent or alleviate it.

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Section: Resultsmentioning

confidence: 99%

Prevalence of fatigue after stroke: A systematic review and meta-analysis

Alghamdi

Ariti

Williams

et al. 2021

European Stroke Journal

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“…Another possible reason is studies’ use of different fatigue scales, with varying classifications of fatigue. Notably, stroke survivors with depressive symptoms are at a significantly higher risk of experiencing fatigue (adjusted odds ratio = 8.86) [ 52 ]. Fatigue is also significantly correlated with anxiety and cognitive functioning in stroke survivors [ 53 ].…”

Section: Discussionmentioning

confidence: 99%

Contribution of sleep quality to fatigue following a stroke: a cross-sectional study

Lai

2021

BMC Neurol

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Background The prevalence of fatigue and sleep disturbances is high in stroke populations. Sleep quality can be targeted by interventions to alleviate fatigue following a stroke. This study aimed to determine the prevalence of fatigue and poor sleep quality, and to quantify the contribution of sleep quality to fatigue following a stroke, in chronic (≥1 year) stroke survivors. Methods A cross-sectional design was adopted. A total of 112 stroke survivors (mean age ± standard deviation [year], 64.18 ± 5.77) at 6.08 ± 4.80 years post-stroke completed this study. All participants were assessed using the Fatigue Assessment Scale, the Pittsburgh Sleep Quality Index, the Visual Analogue Scale-Pain, the Fugl-Meyer Assessment of the upper and lower extremities, the 5-Time Sit-To-Stand Test, the Epworth Sleepiness Scale, the Frenchay Activities Index, the Life-Space Assessment, the Community Integration Measure, and the Multidimensional Scale of Perceived Social Support. Pearson and partial correlation coefficients were used to examine the correlation between fatigue and other variables. A multiple linear regression (the forced entry method) was performed to quantify the independent contribution of sleep quality to prediction of fatigue. Results Of the 112 participants, 52.7% reported experiencing fatigue and 64.3% reported poor sleep quality. Sleep quality could independently account for 5.9% of the variance in fatigue scores after a stroke. Conclusions There is a high prevalence of fatigue and poor sleep quality in Chinese stroke survivors. Sleep quality is an independent predictor of fatigue in those living in the community who have survived a stroke for a year or longer.

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“…Most data on stroke complications in Africa come from hospital-based studies and suggest that some form of complication occurs in >80% of inpatients with stroke (Table 2 ). Stroke complications in Africa include delirium 159 – 161 , post-stroke aspiration pneumonia 85 , 86 , 162 – 166 , bacteriuria and urinary tract infection 167 – 169 , aphasia and deglutition disorders 170 , anxiety 99 , 171 – 173 , fatigue 174 – 176 , sexual dysfunction 177 – 179 , pain (central post-stroke pain syndrome) 180 – 183 , depressive illness 184 – 193 and cognitive impairment that often leads to dementia 194 – 197 .…”

Section: Stroke Phenotypes In Africamentioning

confidence: 99%

Stroke in Africa: profile, progress, prospects and priorities

et al. 2021

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Stroke is a leading cause of disability, dementia and death worldwide. Approximately 70% of deaths from stroke and 87% of stroke-related disability occur in low-income and middle-income countries. At the turn of the century, the most common diseases in Africa were communicable diseases, whereas non-communicable diseases, including stroke, were considered rare, particularly in sub-Saharan Africa. However, evidence indicates that, today, Africa could have up to 2–3-fold greater rates of stroke incidence and higher stroke prevalence than western Europe and the USA. In Africa, data published within the past decade show that stroke has an annual incidence rate of up to 316 per 100,000, a prevalence of up to 1,460 per 100,000 and a 3-year fatality rate greater than 80%. Moreover, many Africans have a stroke within the fourth to sixth decades of life, with serious implications for the individual, their family and society. This age profile is particularly important as strokes in younger people tend to result in a greater loss of self-worth and socioeconomic productivity than in older individuals. Emerging insights from research into stroke epidemiology, genetics, prevention, care and outcomes offer great prospects for tackling the growing burden of stroke on the continent. In this article, we review the unique profile of stroke in Africa and summarize current knowledge on stroke epidemiology, genetics, prevention, acute care, rehabilitation, outcomes, cost of care and awareness. We also discuss knowledge gaps, emerging priorities and future directions of stroke medicine for the more than 1 billion people who live in Africa.

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Prevalence, Trajectory, and Predictors of Poststroke Fatigue among Ghanaians

Cited by 26 publications

References 55 publications

Prevalence of fatigue after stroke: A systematic review and meta-analysis

Prevalence of fatigue after stroke: A systematic review and meta-analysis

Contribution of sleep quality to fatigue following a stroke: a cross-sectional study

Stroke in Africa: profile, progress, prospects and priorities

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