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OP0134 Multifactorial explanatory model of fatigue in patients with rheumatoid arthritis: a path analysis
  1. C.R. Silva1,
  2. C. Duarte1,2,
  3. R. Ferreira1,2,3,
  4. E. Santos2,3,4,
  5. J.A. da Silva2,5
  1. 1Faculty of Medicine, University of Coimbra, Portugal
  2. 2Rheumatology Department, Centro Hospitalar e Universitário de Coimbra
  3. 3Health Sciences Research Unit: Nursing (UICISA:E), Escola Superior de Enfermagem de Coimbra, Coimbra
  4. 4Instituto de Ciências Biomédicas Abel Salazar, Porto
  5. 5Faculty of Medicine, University of Coimbra, Coimbra, Portugal


Background Fatigue is one of the most prevalent and disabling symptoms among patients with Rheumatoid Arthritis (RA). However, it is also one of the most neglected by health professionals. Much of this problem is due to health professionals’ poor understanding of the etiology of fatigue and, also, the absence of effective strategies to prevent or treat it.

Objectives This study aimed at developing a multidimensional explanatory model of fatigue in patients with RA as means to foster better understanding and care of this symptom.

Methods This was an ancillary analysis of an observational, cross-sectional, single centre study. Patients completed a questionnaire that included demographic data and measures of sleep (0–10 Numeric Rating Scale (NRS)), pain (0–10 NRS), disability (HAQ), anxiety and depression (HADS), and personality (TIPI). Fatigue was assessed by the Functional Assessment of Chronic Illness Therapy – Fatigue (FACIT-F). Disease activity (DAS28-CRP3v) and haemoglobin levels were also assessed. Path analysis was performed to test and improve a hypothesised model for fatigue.

Results In total, this analysis included 142 patients (83.1% females, mean (SD) age of 61.1 (11.7) years). The final path analysis model (figure 1) presented acceptable fit (Goodness of Fit Index, GFI=0.92; Comparative Fit Index, CFI=0.89; Root Mean Square Error of Approximation, RMSEA=0.10), and explained 60.0% of the variance of fatigue. Depression and disability had the greater direct influences upon fatigue (β=0.412; p<0.001 and β=0.465; p<0.001, respectively). Sleep disturbance also influenced directly fatigue but at a lower intensity (β=0.157; p=0,007). Disease activity and pain had only an indirect influence on fatigue through disability and sleep disturbance (β=0.149, p=0.005, and β=0.199, p=0.005, respectively). Age was negatively associated with fatigue (β=-0.162, p=0.003). Extroverted patients presented less depressive symptoms and, consecutively, less fatigue (β=-0.224, p=0.002).

Abstract OP0134 – Figure 1 Final path analysis model with standardised direct coefficients.

Goodness of fit index=0.92; Comparative fit index=0.89; Root mean square error of approximation=0.10.

All coefficients in the model presented p<0.05.

Conclusions Depression, disability and sleep disturbance appear to be the main factors explaining fatigue in patients with RA. Disease activity and pain seem to play only a secondary role. These findings foster a shift in the paradigm of patient care towards a more holistic management of fatigue, integrating adjunctive therapies in association with measures driven solely towards abrogation of the inflammatory process.

References [1] van Steenbergen HW, et al. Fatigue in rheumatoid arthritis; A persistent problem: a large longitudinal study. RMD Open2015;1:e000041.

[2] Nikolaus S, et al. Fatigue and factors related to fatigue in rheumatoid arthritis: A systematic review. Arthritis Care Res (Hoboken)2013;65:1128–46.

Acknowledgements We thank study participants who gave their time to take part in this study. We thank the Rheumatology outpatient department medical staff for their assistance with gathering data for this study. We also thank Teresa Neves for statistical advice.

Disclosure of Interest None declared

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