Literature DB >> 18374732

Prognosis of fatigue. A systematic review.

Iris Nijrolder1, Henriëtte van der Horst, Daniëlle van der Windt.   

Abstract

OBJECTIVE: The objective of the study was to summarize evidence on the course and prognostic factors of fatigue in primary care patients and in the community.
METHODS: Two reviewers independently screened identified citations, discussed eligible studies, and assessed methodological quality of selected studies. Data concerning study population, duration of follow-up, measurement of fatigue, outcome, and prognostic factors were extracted. Studies with populations selected by a specific disease or postpartum condition were excluded.
RESULTS: We selected 21 articles reporting on 11 (partly) primary care cohorts and six community cohorts. Follow-up was up to 1 year in primary care and up to 4 years in the community, and in most studies that presented duration of fatigue, participants were chronically fatigued. Because of wide heterogeneity of studies, a qualitative analysis was performed. Recovery of fatigue varied widely, but no differences were found between settings. Sufficient evidence for an association with recovery was found for lower severity of fatigue, and limited evidence was found for good self-reported health, mental health, and psychological attributions. A major deficit in methodological quality of most studies was a potential bias due to low or selective response or loss to follow-up.
CONCLUSION: Most studies on fatigue included patients with long symptom duration at baseline, making it difficult to study prognosis early in the course of fatigue. To provide clear evidence on prognosis in fatigued persons, prognostic studies should use an optimal design including selection of an inception cohort with limited duration of fatigue at baseline, a sufficient sample size, and information on rates and selectivity of response and loss to follow-up.

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Mesh:

Year:  2008        PMID: 18374732     DOI: 10.1016/j.jpsychores.2007.11.001

Source DB:  PubMed          Journal:  J Psychosom Res        ISSN: 0022-3999            Impact factor:   3.006


  9 in total

Review 1.  Findings and Guidelines on Provider Technology, Fatigue, and Well-being: Scoping Review.

Authors:  Donald M Hilty; Christina M Armstrong; Shelby A Smout; Allison Crawford; Marlene M Maheu; Kenneth P Drude; Steven Chan; Peter M Yellowlees; Elizabeth A Krupinski
Journal:  J Med Internet Res       Date:  2022-05-25       Impact factor: 7.076

2.  Prediction of outcome in patients presenting with fatigue in primary care.

Authors:  Iris Nijrolder; Daniëlle van der Windt; Henriëtte van der Horst
Journal:  Br J Gen Pract       Date:  2009-04       Impact factor: 5.386

3.  Chronic fatigue self-management in primary care: a randomized trial.

Authors:  Fred Friedberg; Anthony Napoli; Janna Coronel; Jenna Adamowicz; Viktoria Seva; Indre Caikauskaite; Man Chi Ngan; Jeremy Chang; Hongdao Meng
Journal:  Psychosom Med       Date:  2013-08-06       Impact factor: 4.312

4.  Prognosis of fatigue and functioning in primary care: a 1-year follow-up study.

Authors:  Iris Nijrolder; Daniëlle A W M van der Windt; Henriëtte E van der Horst
Journal:  Ann Fam Med       Date:  2008 Nov-Dec       Impact factor: 5.166

5.  Cost-Utility of Home-Based Fatigue Self-Management versus Usual Care for the Treatment of Chronic Fatigue Syndrome.

Authors:  Hongdao Meng; Fred Friedberg
Journal:  Fatigue       Date:  2017-06-30

6.  Differences in Physical and Psychosocial Characteristics Between CFS and Fatigued Non-CFS Patients, a Case-Control Study.

Authors:  Veronique De Gucht; Franshelis Katerinee Garcia; Marielle den Engelsman; Stan Maes
Journal:  Int J Behav Med       Date:  2016-10

7.  Subacute fatigue in primary care - two sides of the story.

Authors:  Katrin Hulme; Paul Little; Abigail Burrows; Anna Julia; Rona Moss-Morris
Journal:  Br J Health Psychol       Date:  2019-03-08

8.  The prevalence of fatigue among Chinese nursing students in post-COVID-19 era.

Authors:  Shou Liu; Hai-Tao Xi; Qian-Qian Zhu; Mengmeng Ji; Hongyan Zhang; Bing-Xiang Yang; Wei Bai; Hong Cai; Yan-Jie Zhao; Li Chen; Zong-Mei Ge; Zhiwen Wang; Lin Han; Pan Chen; Shuo Liu; Teris Cheung; Brian J Hall; Feng-Rong An; Yu-Tao Xiang
Journal:  PeerJ       Date:  2021-04-13       Impact factor: 2.984

9.  Overview of data-synthesis in systematic reviews of studies on outcome prediction models.

Authors:  Tobias van den Berg; Martijn W Heymans; Stephanie S Leone; David Vergouw; Jill A Hayden; Arianne P Verhagen; Henrica C W de Vet
Journal:  BMC Med Res Methodol       Date:  2013-03-16       Impact factor: 4.615

  9 in total

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