Literature DB >> 33387289

Post-stroke fatigue level is significantly associated with mental health component of health-related quality of life: a cross-sectional study.

Khader A Almhdawi1, Hanan B Jaber2, Hanan W Khalil2, Saddam F Kanaan2, Awni A Shyyab3, Zaid M Mansour4, Alza H Alazrai2.   

Abstract

PURPOSE: Individuals post-stroke might have high levels of post-stroke fatigue (PSF) which might affect their quality of life. This study aimed to investigate the prevalence of post-stroke fatigue in Jordan and to comprehensively identify its possible associated factors.
METHODS: A cross-sectional design was implemented through one-hour face-to-face assessment sessions. The modified fatigue impact scale, 12-item Short-Form Health Survey, Montreal Cognitive Assessment, Motor Assessment Log, Upper Extremity Fugl Meyer assessment, Nine Hole Peg Test, 10 Meter Walk Testing, active and passive goniometry, Hand-held dynamometry, and modified Ashworth scale were used as outcome measures. Prevalence of post-stroke fatigue and levels of quality of life were reported using descriptive analyses. Multiple variable linear regression analysis was used to identify PSF associated factors of post-stroke fatigue. P < 0.05 was considered significant for all statistical tests.
RESULTS: 153 individuals with stroke participated in the study. A total of 117 participants (69.9%, 95% CI = 62.0-77.1%) were fatigued. Fatigue was significantly predicted by mental component of quality of life (β -0.42 [95% CI -0.53--0.31]; p < 0.001), cognition (β -0.69 [95% CI -1.08--0.29], p = 0.001), weekly sport hours (β -0.94 [95% CI -1.73--0.14], p = 0.022), and shoulder abduction spasticity (β -1.81 [95% CI -3.38--0.24], p = 0.024. The model explained 51% of the variation in the fatigue (F = 29.006, p < 0.001).
CONCLUSION: Jordanian individuals with stroke have a high prevalence of fatigue. Mental related quality of life was significantly associated with PSF levels. Other factors significantly associated with PSF included cognition status, sport participation, and spasticity. Healthcare practitioners working in neurorehabilitation should take PSF and its significant correlates into consideration when treating individuals with stroke.

Entities:  

Keywords:  Fatigue; Neurorehabilitation; Quality of life; Stroke

Mesh:

Year:  2021        PMID: 33387289     DOI: 10.1007/s11136-020-02714-z

Source DB:  PubMed          Journal:  Qual Life Res        ISSN: 0962-9343            Impact factor:   4.147


  50 in total

Review 1.  Post-stroke fatigue: epidemiology, clinical characteristics and treatment.

Authors:  Monica Acciarresi; Julien Bogousslavsky; Maurizio Paciaroni
Journal:  Eur Neurol       Date:  2014-09-24       Impact factor: 1.710

2.  Is fatigue an independent factor associated with activities of daily living, instrumental activities of daily living and health-related quality of life in chronic stroke?

Authors:  I G L van de Port; G Kwakkel; V P M Schepers; C T I Heinemans; E Lindeman
Journal:  Cerebrovasc Dis       Date:  2006-09-12       Impact factor: 2.762

3.  Fatigue in the general population: a translation and test of the psychometric properties of the Norwegian version of the fatigue severity scale.

Authors:  Anners Lerdal; Astrid Wahl; Tone Rustøen; Berit R Hanestad; Torbjørn Moum
Journal:  Scand J Public Health       Date:  2005       Impact factor: 3.021

4.  Post-stroke fatigue and return to work: a 2-year follow-up.

Authors:  G Andersen; D Christensen; M Kirkevold; S P Johnsen
Journal:  Acta Neurol Scand       Date:  2011-06-21       Impact factor: 3.209

5.  Stroke and transient ischemic attack incidence rate in Spain: the IBERICTUS study.

Authors:  Jaime Díaz-Guzmán; Jose-A Egido; Rafael Gabriel-Sánchez; Gloria Barberá-Comes; Blanca Fuentes-Gimeno; Cristina Fernández-Pérez
Journal:  Cerebrovasc Dis       Date:  2012-10-20       Impact factor: 2.762

6.  Dimensions of post-stroke fatigue: a two-year follow-up study.

Authors:  Doris Christensen; Soeren Paaske Johnsen; Torquil Watt; Ingegerd Harder; Marit Kirkevold; Grethe Andersen
Journal:  Cerebrovasc Dis       Date:  2008-06-17       Impact factor: 2.762

Review 7.  Stroke in Arab countries: a systematic literature review.

Authors:  Hani T S Benamer; Donald Grosset
Journal:  J Neurol Sci       Date:  2009-05-09       Impact factor: 3.181

8.  Fatigue in the general Korean population: application and normative data of the Brief Fatigue Inventory.

Authors:  Young Ho Yun; Myung Kyung Lee; Han Na Chun; Young Mi Lee; Sang Min Park; Tito R Mendoza; Xin Shelley Wang; Charles S Cleeland
Journal:  J Pain Symptom Manage       Date:  2008-04-14       Impact factor: 3.612

9.  Incidence of first stroke: a population study in Iceland.

Authors:  Agust Hilmarsson; Olafur Kjartansson; Elias Olafsson
Journal:  Stroke       Date:  2013-05-09       Impact factor: 7.914

10.  The effects of fatigue, pain, and depression on quality of life in ischemic stroke patients: the Bergen Stroke Study.

Authors:  Halvor Naess; Lene Lunde; Jan Brogger
Journal:  Vasc Health Risk Manag       Date:  2012-06-27
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  1 in total

1.  Model Construction of Using Physiological Signals to Detect Mental Health Status.

Authors:  Xiaoqian Liu
Journal:  J Healthc Eng       Date:  2021-10-20       Impact factor: 2.682

  1 in total

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