Article Text

THU0310 Quantitative Assessment of Fatigue in Routine Care Using a Multidimensional Health Assessment Questionnaire (MDHAQ)
  1. E. Nikiphorou1,
  2. I. Castrejon2,
  3. R. Jain2,
  4. A. Huang2,
  5. J.A. Block2,
  6. T. Pincus2
  1. 1Rheumatology, Addenbrooke's Hospital, Cambridge, United Kingdom
  2. 2Rheumatology, Rush University Medical Center, Chicago, United States


Background Fatigue generally is captured as a qualitative description rather than as quantitative data to compare from one visit to the next. Fatigue is included on a multidimensional health assessment questionnaire (MDHAQ) as a 0-10 visual analogue scale (VAS), facilitating quantification.

Objectives To assess fatigue VAS scores in patients with 4 different rheumatic conditions: rheumatoid arthritis (RA), osteoarthritis (OA), systemic lupus erythematosus (SLE), and fibromyalgia (FM), and to analyze possible associations of fatigue scores with other quantitative clinical scores included on the MDHAQ.

Methods All patients seen in one academic clinical setting complete an MDHAQ in 5-10 minutes in the waiting area, prior to seeing the rheumatologist, as part of the infrastructure of routine care. The two-page MDHAQ includes physical function in 10 activities of daily living, three 0-10 VAS for pain, patient global estimate, and fatigue, 60-symptom checklist, and demographic data. RAPID 3 (0-30) is the sum of three 0-10 scores for function, pain, and patient global estimate. A cross-sectional study was performed in patients in 4 diagnosis groups: RA, OA, SLE, and FM. Median scores for fatigue and other MDHAQ scales were computed in the four diagnosis groups, and compared by Kruskall-Wallis one way analysis of variance. Correlations also were calculated to evaluate possible associations of fatigue with other MDHAQ scores.

Results Analyses included 612 patients, 173 with RA, 199 with OA, 146 with SLE and 94 with FM. Fatigue scores were highest in FM, and differed significantly from RA, SLE, and OA (p<0.001); scores for function, patient global, RAPID3, RADAI and number of symptoms also differed significantly in FM versus other diseases (Table). Fatigue scores were correlated significantly with scores for function, pain, and patient global estimate in all patients (r>0.53, p<0.01), RA (r>0.66, p<0.01), and SLE (r>0.60, p<0.01) patients, but at lower levels in OA (r>0.33, p<0.01), and FM (r>0.32, p<0.01), indicating stronger associations of fatigue with other measures in diseases characterized by higher levels of inflammation.

Conclusions Fatigue scores may be collected in the infrastructure of routine care as quantitative data on an MDHAQ, with no extra work for the doctor and minimal interference with clinic patient flow. Fatigue scores are associated with scores on other MDHAQ scales at considerably higher levels in RA and SLE than in OA and FM.

Disclosure of Interest None declared

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