- Title
- Investigating post-stroke fatigue: an individual participant data meta-analysis
- Creator
- 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; van de Port, Ingrid; Mead, Gillian; English, Coralie
- Relation
- Journal of Psychosomatic Research Vol. 113, p. 107-112
- Publisher Link
- http://dx.doi.org/10.1016/j.jpsychores.2018.08.006
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2018
- Description
- 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.
- Subject
- depression; fatigue; fatigue Severity Scale; individual data; meta-analysis; stroke; SDG 3; Sustainable Development Goals
- Identifier
- http://hdl.handle.net/1959.13/1459848
- Identifier
- uon:45795
- Identifier
- ISSN:0022-3999
- Language
- eng
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