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

Cumming, Toby B.; Yeo, Ai Beng; Marquez, Jodie; Churilov, Leonid; Annoni, Jean-Marie; Badaru, Umaru; Ghotbi, Nastaran; Harbison, Joe; Kwakkel, Gert; Lerdal, Anners; Mills, Roger; Naess, Halvor; Nyland, Harald; Schmid, Arlene; Tang, Wai Kwong; Tseng, Benjamin; Port, Ingridvan de; Mead, Gillian; English, Coralie

doi:10.1016/j.jpsychores.2018.08.006

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

Cumming, Toby B. Florey Institute of Neuroscience and Mental Health, University of Melbourne, Australia - Centre of Research Excellence in Stroke Rehabilitation and Brain Recovery, Australia
Yeo, Ai Beng School of Health Sciences and Priority Research Centre for Stroke and Brain Injury, University of Newcastle, Callaghan, Australia
Marquez, Jodie School of Health Sciences and Priority Research Centre for Stroke and Brain Injury, University of Newcastle, Callaghan, Australia
Churilov, Leonid Florey Institute of Neuroscience and Mental Health, University of Melbourne, Australia
Annoni, Jean-Marie Department of Medicine, University of Fribourg, Switzerland
Badaru, Umaru Department of Physiotherapy, Bayero University, Kano, Nigeria
Ghotbi, Nastaran Department of Physiotherapy, Tehran University of Medical Sciences, Iran
Harbison, Joe Department of Medical Gerontology, Trinity College Dublin, Ireland
Kwakkel, Gert Department of Rehabilitation Medicine, VU University, Amsterdam, the Netherlands
Lerdal, Anners Department of Nursing Science, University of Oslo, Norway
Mills, Roger Department of Neurology, Royal Preston Hospital, UK
Naess, Halvor Department of Neurology, Haukeland University Hospital, Norway
Nyland, Harald Institute of Clinical Medicine, University of Bergen, Norway
Schmid, Arlene Department of Occupational Therapy, Colorado State University, Fort Collins, USA
Tang, Wai Kwong Department of Psychiatry, Chinese University of, Hong Kong
Tseng, Benjamin Department of Health & Kinesiology, University of Texas, Tyler, USA
Port, Ingridvan de Revant Rehabilitation Centres, Breda, the Netherlands
Mead, Gillian Centre for Clinical Brain Sciences, University of Edinburgh, UK
English, Coralie Centre of Research Excellence in Stroke Rehabilitation and Brain Recovery, Australia - School of Health Sciences and Priority Research Centre for Stroke and Brain Injury, University of Newcastle, Callaghan, Australia

01.10.2018

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Journal of Psychosomatic Research. - 2018, vol. 113, p. 107–112

English The prevalence of post-stroke fatigue differs widely across studies, and reasons for such divergence are unclear. We aimed to collate individual data on post-stroke fatigue from multiple studies to facilitate high-powered meta-analysis, thus increasing our understanding of this complex phenomenon.Methods: We conducted an Individual Participant Data (IPD) meta-analysis on post-stroke fatigue and its associated factors. The starting point was our 2016 systematic review and meta-analysis of post-stroke fatigue prevalence, which included 24 studies that used the Fatigue Severity Scale (FSS). Study authors were asked to provide anonymised raw data on the following pre-identified variables: (i) FSS score, (ii) age, (iii) sex, (iv) time post-stroke, (v) depressive symptoms, (vi) stroke severity, (vii) disability, and (viii) stroke type. Linear regression analyses with FSS total score as the dependent variable, clustered by study, were conducted.Results: We obtained data from 14 of the 24 studies, and 12 datasets were suitable for IPD meta-analysis (total n = 2102). Higher levels of fatigue were independently associated with female sex (coeff. = 2.13, 95% CI 0.44–3.82, p = 0.023), depressive symptoms (coeff. = 7.90, 95% CI 1.76–14.04, p = 0.021), longer time since stroke (coeff. = 10.38, 95% CI 4.35–16.41, p = 0.007) and greater disability (coeff. = 4.16, 95% CI 1.52–6.81, p = 0.010). While there was no linear association between fatigue and age, a cubic relationship was identified (p < 0.001), with fatigue peaks in mid-life and the oldest old.Conclusion: 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.

Faculty

Faculté des sciences et de médecine

Department

Médecine 3ème année

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