Factors associated with fatigue in early arthritis: results from a multicenter national French cohort study.

Arthritis Care Res (Hoboken)

Nancy-Université, Université Paul Verlaine Metz, Université Paris Descartes, EA 4360 Apemac, INSERM, CIC-EC CIE6, CHU Nancy, Nancy, France.

Published: July 2012

AI Article Synopsis

  • The study investigates the factors influencing fatigue in patients with early arthritis and how this fatigue changes over one year.
  • It analyzed data from 813 patients, noting that factors like age, gender, education level, smoking, and disease activity significantly correlated with fatigue levels.
  • Results indicate that the quality of life, particularly the affective domain, plays a crucial role in understanding fatigue in these patients, highlighting the need for healthcare professionals to address this issue effectively.

Article Abstract

Objective: Fatigue frequently occurs in patients with early arthritis (EA). Determinants of its severity are unknown. We aimed to identify the factors associated with fatigue in EA and changes in fatigue after 1 year of followup.

Methods: The Evaluation et Suivi de Polyarthrites Indifférenciées Récentes (Assessment and Followup of Early Undifferentiated Arthritis) cohort study is a multicenter, prospective, national cohort of patients with EA. At baseline and every 6 months up to 1 year, we recorded sociodemographic, clinical, and treatment characteristics, Arthritis Impact Measurement Scales 2 Short Form (AIMS2-SF) and Short Form 36 (SF-36) scores for health-related quality of life (HRQOL), and fatigue severity by a visual analog scale (f-VAS) and the SF-36 vitality score (fatigue_SF36).

Results: We included 813 patients (77% women, mean ± SD age 48 ± 13 years). At baseline, fatigue as assessed by the f-VAS or fatigue_SF36 was independently associated with young age, female sex, low education level, smoking, increased Disease Activity Score in 28 joints (DAS28), waking up at night, Sjögren's syndrome, and worse AIMS2-SF physical, affect, and symptom scores. At 1-year followup, a favorable change in fatigue scores was associated with increased baseline AIMS2-SF physical and affect scores (better quality of life), high baseline fatigue scores, and improved 1-year AIMS2-SF affect scores. Age, sex, and change in AIMS2-SF physical score, DAS28, and hemoglobin or C-reactive protein level were inconsistently associated with change in fatigue scores. The AIMS2-SF affect score explained most of the variance in baseline fatigue score and was an important factor in 1-year change in fatigue score.

Conclusion: Fatigue in EA is multifactorial. Its level and its course are strongly associated with HRQOL, notably the affect dimension. These results should help professionals inform patients about fatigue, explore its causes, and develop tailored interventions.

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Source
http://dx.doi.org/10.1002/acr.21647DOI Listing

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