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Investigating Post-Stroke Fatigue: An Individual Participant Data Meta-Analysis Publisher Pubmed



Cumming TB1, 2 ; Yeo AB3 ; Marquez J3 ; Churilov L1 ; Annoni JM4 ; Badaru U5 ; Ghotbi N6 ; Harbison J7 ; Kwakkel G8 ; Lerdal A9 ; Mills R10 ; Naess H11 ; Nyland H12 ; Schmid A13 Show All Authors
Authors
  1. Cumming TB1, 2
  2. Yeo AB3
  3. Marquez J3
  4. Churilov L1
  5. Annoni JM4
  6. Badaru U5
  7. Ghotbi N6
  8. Harbison J7
  9. Kwakkel G8
  10. Lerdal A9
  11. Mills R10
  12. Naess H11
  13. Nyland H12
  14. Schmid A13
  15. Tang WK14
  16. Tseng B15
  17. Van De Port I16
  18. Mead G17
  19. English C2, 3
Show Affiliations
Authors Affiliations
  1. 1. Florey Institute of Neuroscience and Mental Health, University of Melbourne, Australia
  2. 2. Centre of Research Excellence in Stroke Rehabilitation and Brain Recovery, Australia
  3. 3. School of Health Sciences and Priority Research Centre for Stroke and Brain Injury, University of Newcastle, Callaghan, Australia
  4. 4. Department of Medicine, University of Fribourg, Switzerland
  5. 5. Department of Physiotherapy, Bayero University, Kano, Nigeria
  6. 6. Department of Physiotherapy, Tehran University of Medical Sciences, Iran
  7. 7. Department of Medical Gerontology, Trinity College Dublin, Ireland
  8. 8. Department of Rehabilitation Medicine, VU University, Amsterdam, Netherlands
  9. 9. Department of Nursing Science, University of Oslo, Norway
  10. 10. Department of Neurology, Royal Preston Hospital, United Kingdom
  11. 11. Department of Neurology, Haukeland University Hospital, Norway
  12. 12. Institute of Clinical Medicine, University of Bergen, Norway
  13. 13. Department of Occupational Therapy, Colorado State University, Fort Collins, United States
  14. 14. Department of Psychiatry, Chinese University of, Hong Kong
  15. 15. Department of Health & Kinesiology, University of Texas, Tyler, United States
  16. 16. Revant Rehabilitation Centres, Breda, Netherlands
  17. 17. Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom

Source: Journal of Psychosomatic Research Published:2018


Abstract

Objective: 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. © 2018 Elsevier Inc.
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