OP22 Factors independently associated with fatigue in IBD: Results from the baseline dataset of the PREdiCCt study
Derikx, L.(1,2);Siakavellas, S.(2);Derr, L.(2);Williams, L.(2);Nikolas, P.(2);Jenkinson, P.(2);Lucaciu, L.(2);Constantine-Cooke, N.(3);Covil, K.(2);Murdoch, L.(2);Jones, G.R.(2,4);Lees, C.(2,5)
(1)Radboud University Nijmegen Medical Centre, Inflammatory Bowel Disease Centre- Department of Gastroenterology and Hepatology- Route 455, Nijmegen, The Netherlands;(2)Western General Hospital, The Edinburgh IBD Unit, Edinburgh, United Kingdom;(3)University of Edinburgh- Western General Hospital, MRC Human Genetics Unit- Institute of Genetics and Molecular Medicine, Edinburgh, United Kingdom;(4)University of Edinburgh, Centre for Inflammation Research- The Queen's Medical Research Institute, Edinburgh, United Kingdom;(5)University of Edinburgh- Western General Hospital, Centre for Genomics and Experimental Medicine- Institute of Genetics and Molecular Medicine, Edinburgh, United Kingdom PREdiCCt Study Writing Group
Background
Fatigue is one of the most common symptoms in IBD resulting in decreased quality of life, impaired work productivity, and higher societal costs. However, little is known about its etiology and pathophysiology. We aimed to estimate the prevalence of fatigue and to identify predictive factors for fatigue.
Methods
The PREdiCCt study (https://www.predicct.co.uk) is the largest prospective study of the causes of IBD flare. 2629 patients in clinical remission were recruited from 48 UK sites. 1946 (74%) patients completed the baseline questionnaires. We assessed the prevalence of fatigue at baseline using a single item from the IBD Control questionnaire. To identify predictors for fatigue, we performed univariable and multivariable analyses including demographic, biochemical, environmental and psychosocial factors such as anxiety and depression [HADS], sleep quality [PSQI] and physical exercise [GPAQ]).
Results
759/1919 IBD patients in clinical remission (39.6%) reported fatigue in the past 2 weeks, while 1034 patients (53.9%) did not report fatigue. Patients who reported fatigue were more frequently female, had more frequently CD, and were more frequently smokers (Table 1). Univariable comparisons showed higher inflammatory markers in the fatigued group, with fewer patients in clinical remission. Multivariable analyses identified female sex (OR 2.4), CRP>5 (OR 2.1), bad sleep quality (OR 2.5), anxiety (OR 1.8) and depression (OR 6.2) as independent factors associated with fatigue (Table 2).
Table 1
| Variable (n [%], or median [IQR]) | Often lack energy – yes(n=759) | Often lack energy – no(n=1034) | P-value |
|---|---|---|---|
| Female sex | 504 (66.4) | 508 (49.1) | <0.001 |
| Current smoker | 57 (8.9) | 45 (4.9) | 0.002 |
| IBD type (CD) | 431 (57.2) | 492 (48.0) | <0.001 |
| Haemoglobin (g/L) | 136 (127-145) | 140 (131-148) | <0.001 |
| White cell count (x10^9/L) | 6.3 (5.3-7.8) | 6.0 (5.0-7.2) | <0.001 |
| CRP <5 mg/L | 360 (62.8) | 588 (76.5) | <0.001 |
| Ferritin (ug/L) | 56 (27-106.5) | 66 (36-116) | 0.011 |
| Folate (ug/L) | 6.5 (4.3-10.5) | 7.3 (5.0-10.9) | 0.011 |
| Clinical remission (HBI<4, pMayo<2) | 287 (71.8) | 482 (82.7) | <0.001 |
| Depression (HADS>9) | 224 (30.0) | 49 (4.8) | <0.001 |
| Anxiety (HADS>9) | 336 (45.0) | 165 (16.2) | <0.001 |
| Physical activity (GPAQ<600) | 207 (27.6) | 193 (18.8) | <0.001 |
| Sleep quality (PSQI>5) | 633 (90.2) | 693 (69.9) | <0.001 |
Table 2
| Variable | OR | 95% CI | P-value |
|---|---|---|---|
| Female sex | 2.4 | 1.5-3.8 | <0.001 |
| CRP >5 mg/L | 2.1 | 1.3-3.5 | 0.004 |
| Depression (HADS>9) | 6.2 | 2.9-13.3 | <0.001 |
| Anxiety (HADS>9) | 1.8 | 1.1-3.0 | 0.031 |
| Sleep quality (PSQI>5) | 2.5 | 1.4-4.6 | 0.002 |
Conclusion
We show the significant burden of fatigue in IBD patients and describe putative causes which demonstrate both the impact of residual gut inflammation and the relationship between fatigue and psychological well-being. The impact of environmental and dietary factors on fatigue is being further investigated with ongoing longitudinal data collection in the PREdiCCt study.