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Abstract Number: 1554

Clusters of Fatigue- a Comparison Between Persons with Systemic Lupus Erythematosus and Age and Gender Matched Controls

Susanne Pettersson1, Karin Eriksson2, Carina Boström2, Elisabet Svenungsson1, Iva Gunnarsson1 and Elisabet MB Welin Henriksson3, 1Department of Medicine, Rheumatology Unit, Karolinska Institutet, Stockholm, Sweden, 2Department of Neurobiology, Care Sciences and Society,, Division of Physiotherapy, Karolinska Institutet Huddinge, Stockholm, Sweden, 3Medicine, Karolinska Institutet Rheum, Stockholm, Sweden

Meeting: 2012 ACR/ARHP Annual Meeting

Keywords: fatigue and systemic lupus erythematosus (SLE)

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Session Information

Session Title: Clinical Practice/Patient Care

Session Type: Abstract Submissions (ARHP)

Background/Purpose:

The aim (1) of this study was to explore fatigue in patients with SLE with age and gender match controls using cluster analysis and (2) analyze the clusters concerning health related quality of life (HRQoL), anxiety, depression and life-style habits.

Methods:

This cross-sectional study included patients with SLE and paired controls (age and gender). The respondents answered self-assessment of fatigue: Fatigue severity scale (FSS), Vitality (VT) from SF-36 and Multidimensional Assessment of Fatigue scale (MAF). All three questionnaires were answered by 616 persons (mean age 47 years, SD 14.6, range 18-84) and hierarchic cluster analysis were used to form homogeneous groups of fatigue. Further the Medical Short Form-36 (SF-36) were used to collect data on HRQoL and The Hospital Anxiety and Depression Scale (HADS) with the two sub-scales, anxiety (HADS-A) and depression (HADS-D).

Results:

Patients with SLE had higher levels of fatigue than the controls on all three fatigue questionnaires as well as all dimensions of HRQoL and depression. The hierarchic cluster analysis identified three divergent clusters of fatigue with significantly different levels of fatigue. The clusters were denominated by their levels of fatigue. The persons in the High fatigue cluster (n=221) were dominated by patients (80%) and most affected by depression and anxiety, had lowest levels of HRQoL. This cluster had the lowest proportion of persons working ≥ 50% and they lived more often without a partner. The Low fatigue cluster (n= 240) was dominated by the controls (78%) and included persons with highest perceived HRQoL, lowest distribution of anxiety and no detected depression (p < 0.001). They represented the lowest proportion of smoker (13% vs 20%, both High and Intermediate). Persons in the Intermediate fatigue cluster (n=155) had smoking habits similar to the High fatigue cluster, and sleeping habits towards the Low fatigue cluster. The intermediate fatigue cluster had the most equal distribution at 48% patients and 52% controls, their level of fatigue were more moderate. There were no differences in gender distribution, age or sedentary behavior between the three clusters.

Comparing patients in the three clusters no significant difference was found regarding the number of ACR criteria, disease duration, or organ damage (SLICC/ACR). However, patients in the High fatigue cluster had more disease activity (SLAM) (mean 9.0, CI 8.3-9.7) than both the Low fatigue cluster (mean 4.2, CI 3.3-5.2, p < 0.001) and the Intermediate fatigue cluster (mean 5.3, CI 4.7-6.0, p < 0.001). However, there was no difference in disease activity between the Low fatigue cluster and the Intermediate fatigue cluster.

Conclusion: The analysis confirmed that a high number of patients with SLE are affected by fatigue but also that non-SLE persons were clustered together with the patients (6%) in the High fatigue cluster. Notable is that in this cross-sectional study a minority (7%) of patients with SLE report low levels of fatigue, high wellbeing and healthier life-style habits e.g interestingly less smoker.


Disclosure:

S. Pettersson,
None;

K. Eriksson,
None;

C. Boström,
None;

E. Svenungsson,
None;

I. Gunnarsson,
None;

E. M. Welin Henriksson,
None.

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