Poststroke Fatigue: Who Is at Risk for an Increase in Fatigue?
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...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Stroke Research and Treatment |
| Online Access: | http://dx.doi.org/10.1155/2012/863978 |
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| _version_ | 1849409418853089280 |
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| author | Hanna Maria van Eijsden Ingrid Gerrie Lambert van de Port Johanna Maria August Visser-Meily Gert Kwakkel |
| author_facet | Hanna Maria van Eijsden Ingrid Gerrie Lambert van de Port Johanna Maria August Visser-Meily Gert Kwakkel |
| author_sort | Hanna Maria van Eijsden |
| collection | DOAJ |
| description | 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, P<0.001). 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. |
| format | Article |
| id | doaj-art-7d1389706fb644ddaadf4616b24799ff |
| institution | Kabale University |
| issn | 2090-8105 2042-0056 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Stroke Research and Treatment |
| spelling | doaj-art-7d1389706fb644ddaadf4616b24799ff2025-08-20T03:35:29ZengWileyStroke Research and Treatment2090-81052042-00562012-01-01201210.1155/2012/863978863978Poststroke Fatigue: Who Is at Risk for an Increase in Fatigue?Hanna Maria van Eijsden0Ingrid Gerrie Lambert van de Port1Johanna Maria August Visser-Meily2Gert Kwakkel3Clinical Health Sciences, Faculty of Medicine, Utrecht University, 3508 TC, Utrecht, The NetherlandsClinical Health Sciences, Faculty of Medicine, Utrecht University, 3508 TC, Utrecht, The NetherlandsRudolf 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 NetherlandsRudolf 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 NetherlandsBackground. 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, P<0.001). 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.http://dx.doi.org/10.1155/2012/863978 |
| spellingShingle | Hanna Maria van Eijsden Ingrid Gerrie Lambert van de Port Johanna Maria August Visser-Meily Gert Kwakkel Poststroke Fatigue: Who Is at Risk for an Increase in Fatigue? Stroke Research and Treatment |
| title | Poststroke Fatigue: Who Is at Risk for an Increase in Fatigue? |
| title_full | Poststroke Fatigue: Who Is at Risk for an Increase in Fatigue? |
| title_fullStr | Poststroke Fatigue: Who Is at Risk for an Increase in Fatigue? |
| title_full_unstemmed | Poststroke Fatigue: Who Is at Risk for an Increase in Fatigue? |
| title_short | Poststroke Fatigue: Who Is at Risk for an Increase in Fatigue? |
| title_sort | poststroke fatigue who is at risk for an increase in fatigue |
| url | http://dx.doi.org/10.1155/2012/863978 |
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