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Stroke Research and Treatment
Volume 2012 (2012), Article ID 863978, 8 pages
http://dx.doi.org/10.1155/2012/863978
Research Article

Poststroke Fatigue: Who Is at Risk for an Increase in Fatigue?

1Clinical Health Sciences, Faculty of Medicine, Utrecht University, 3508 TC, Utrecht, The Netherlands
2Rudolf Magnus Institute of Neuroscience and Center of Excellence for Rehabilitation Medicine, University Medical Center Utrecht and Rehabilitation Center De Hoogstraat, Rembrandtkade 10, 3582 TM Utrecht, The Netherlands
3Department of Rehabilitation Medicine, Research Institute MOVE, VU University Medical Centre, 1081 HV Amsterdam, The Netherlands

Received 14 June 2011; Revised 22 July 2011; Accepted 15 August 2011

Academic Editor: Gillian Mead

Copyright © 2012 Hanna Maria van Eijsden et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background. Several studies have examined determinants related to post-stroke fatigue. However, it is unclear which determinants can predict an increase in poststroke fatigue over time. Aim. This prospective cohort study aimed to identify determinants which predict an increase in post-stroke fatigue. Methods. A total of 250 patients with stroke were examined at inpatient rehabilitation discharge (T0) and 24 weeks later (T1). Fatigue was measured using the Fatigue Severity Scale (FSS). An increase in post-stroke fatigue was defined as an increase in the FSS score beyond the 95% limits of the standard error of measurement of the FSS (i.e., 1.41 points) between T0 and T1. Candidate determinants included personal factors, stroke characteristics, physical, cognitive, and emotional functions, and activities and participation and were assessed at T0. Factors predicting an increase in fatigue were identified using forward multivariate logistic regression analysis. Results. The only independent predictor of an increase in post-stroke fatigue was FSS (OR 0.50; 0.38–0.64, ). The model including FSS at baseline correctly predicted 7.9% of the patients who showed increased fatigue at T1. Conclusion. The prognostic model to predict an increase in fatigue after stroke has limited predictive value, but baseline fatigue is the most important independent predictor. Overall, fatigue levels remained stable over time.