<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Cumming, Toby B.</dc:creator>
  <dc:creator>Yeo, Ai Beng</dc:creator>
  <dc:creator>Marquez, Jodie</dc:creator>
  <dc:creator>Churilov, Leonid</dc:creator>
  <dc:creator>Annoni, Jean-Marie</dc:creator>
  <dc:creator>Badaru, Umaru</dc:creator>
  <dc:creator>Ghotbi, Nastaran</dc:creator>
  <dc:creator>Harbison, Joe</dc:creator>
  <dc:creator>Kwakkel, Gert</dc:creator>
  <dc:creator>Lerdal, Anners</dc:creator>
  <dc:creator>Mills, Roger</dc:creator>
  <dc:creator>Naess, Halvor</dc:creator>
  <dc:creator>Nyland, Harald</dc:creator>
  <dc:creator>Schmid, Arlene</dc:creator>
  <dc:creator>Tang, Wai Kwong</dc:creator>
  <dc:creator>Tseng, Benjamin</dc:creator>
  <dc:creator>Port, Ingridvan de</dc:creator>
  <dc:creator>Mead, Gillian</dc:creator>
  <dc:creator>English, Coralie</dc:creator>
  <dc:date>2018-10-01</dc:date>
  <dc:description xmlns:ns0="xml" ns0:lang="en">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 &lt; 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.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>https://folia.unifr.ch/global/documents/307299</dc:identifier>
  <dc:identifier>https://folia.unifr.ch/documents/307299/files/ann_ips.pdf</dc:identifier>
  <dc:identifier>https://folia.unifr.ch/documents/307299/files/ann_ips_sm.pdf</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jpsychores.2018.08.006</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>License undefined</dc:rights>
  <dc:source>Journal of Psychosomatic Research. - 2018, vol. 113, p. 107–112</dc:source>
  <dc:subject>info:eu-repo/classification/udc/57</dc:subject>
  <dc:title xmlns:ns1="xml" ns1:lang="en">Investigating post-stroke fatigue: An individual participant data meta-analysis</dc:title>
  <dc:type>http://purl.org/coar/resource_type/c_6501</dc:type>
</oai_dc:dc>
