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Arthritis Care Res (Hoboken) ; 65(6): 862-9, 2013 Jun.
Article in English | MEDLINE | ID: mdl-23729241

ABSTRACT

OBJECTIVE: Fatigue and pain are important symptoms for patients with rheumatoid arthritis (RA), but their temporal association is unknown. Therefore, the objective of this study was to investigate the longitudinal relationship between fatigue and pain in patients with RA using time-lag models. METHODS: Consecutive RA outpatients (n = 228) were enrolled for this 1-year study. Fatigue was assessed monthly with the Checklist Individual Strength (CIS; range 8-56) and pain was assessed monthly with the bodily pain subscale (inverted, range 0-100) of the Short Form 36. The association between monthly changes in fatigue and pain was analyzed using longitudinal regression (mixed models), using the same months and with a 1-month time lag. RESULTS: A total of 198 patients were included in the analyses. At baseline, the mean ± SD pain score was 35.23 ± 19.82 and the mean ± SD CIS fatigue score was 31.0 ± 12.4. Severe fatigue at baseline (CIS score ≥35) was present in 42% of the patients. The mean ± SD patient-averaged CIS fatigue score over 1 year was 30.9 ± 6.0 and the mean ± SD patient-averaged pain score over 1 year was 36.4 ± 18.3. The longitudinal regression analysis showed a significant positive relationship between fatigue and pain during the same month (ß = 2.04; 95% confidence interval 1.82, 2.27). The models using a time lag showed no significant association between changes in pain and changes in fatigue. CONCLUSION: In established RA, pain and fatigue show monthly fluctuations that are synchronous rather than showing a temporal relationship with a time lag; within this timeframe, the results do not indicate that one precedes the other.


Subject(s)
Arthritis, Rheumatoid/complications , Fatigue/etiology , Pain/etiology , Aged , Antirheumatic Agents/therapeutic use , Arthritis, Rheumatoid/drug therapy , Cohort Studies , Female , Humans , Longitudinal Studies , Male , Middle Aged , Prospective Studies , Regression Analysis , Severity of Illness Index , Time Factors
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