We found that severe fatigue is a persistent problem in the daily life of HPN patients. This finding has also been reported in other patient categories, such as (disease-free) breast cancer patients [23
], chronic peritoneal dialysis patients [13
] and patients suffering from rheumatoid arthritis [24
]. For HPN patients, no predictors of fatigue were available from the literature. Our first longitudinal analysis showed that fatigue is the most important predictor for persistent fatigue. This result has also been found by Servaes et al. [23
] in disease-free breast cancer patients. Avoidance was the second predictor of fatigue in HPN patients. From literature in CFS patients, it is known that patients avoid all kinds of activities because of the fear that activity enhances symptoms [46
]. Because the body gets unused to activity, symptoms will emerge at increasingly lower levels of activity. In this way, a self-fulfilling prophecy is established. Motivating patients and decreasing the fear of activity therefore is important to decrease levels of fatigue. Our second cross-sectional analysis showed that functional impairment, self-efficacy and depression explain a considerable part of fatigue at baseline.
Whilst fatigue is a frequent symptom in HPN patients, it has received no attention in research. As HPN patients may suffer from anaemia, problems with fluid intake/diarrhoea, renal disease or liver disease, it is reasonable to assume that fatigue is related to somatic problems. However, our results show no correlations between relevant laboratory measures and fatigue. This is in accordance with several studies in patients on haemodialysis and in patients with primary biliary cirrhosis where no association was found between anaemia, albumin, creatinine and bilirubin levels and fatigue [12
As in our study, studies in patients suffering from rheumatoid arthritis show that the relationships between psychosocial variables and fatigue are often much stronger than ‘objective’ measures of disease severity or inflammatory markers, like laboratory values, swollen joints or deformities [47
]. Riemsma et al. [50
] showed that laboratory measurements like haemoglobin concentration and erythrocyte sedimentation rate are not significantly related to fatigue, whilst psychosocial aspects like self-efficacy and problematic social support are the most important variables in explaining fatigue.
With regard to the results for functional impairment, it can be concluded that HPN patients experiencing more functional impairment have higher levels of fatigue. Regarding self-efficacy, a lower sense of control with respect to fatigue complaints is associated with an increase in experienced fatigue. Both these findings are consistent with results of studies in chronic fatigue syndrome patients, multiple sclerosis patients and patients with rheumatoid arthritis [17
]. In these patient populations, a low self-efficacy was found to have a direct negative causal effect on fatigue severity. It is known that self-efficacy can be enhanced by self-management courses, and it may thus be possible to improve fatigue [50
]. Self-efficacy is also an important aspect of cognitive behaviour therapy in CFS patients. Prins et al. [40
] found that patients with a greater sense of control at baseline had a larger decrease in fatigue severity after cognitive behaviour therapy (CBT) than patients with lower sense of control.
For CFS patients, CBT has been proven to be successful in reducing fatigue complaints [40
]. Besides reducing fatigue severity, CBT also had a positive effect on functional impairment [40
]. A systematic review of Neill et al. [54
] showed the effectiveness of non-pharmacological interventions for fatigue in chronic diseases. Exercise appears to be an effective, appropriate and feasible non-pharmacological intervention for reducing fatigue in people with multiple sclerosis (MS), rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE). This is consistent with recommendations for patients with cancer-related fatigue and chronic fatigue syndrome. In addition, a range of behavioural interventions, like energy conservation, may be helpful in reducing fatigue in MS, RA and SLE [55
]. Educational interventions also produced statistically significant reductions in fatigue.
The finding that depression partly explains fatigue is also confirmed by other studies on fatigue. Leserman et al. [58
] showed that depression directly results in fatigue. Lui [22
] found that depression was the most important predictor of fatigue in haemodialysis patients. Although this remains to be proven in future research, in our opinion, the adequate identification and treatment for depression might also prove to be an effective strategy for decreasing levels of fatigue [22
]. In HPN patients, a study by Smith et al. [60
] showed that by means of interactive education, depressive reactions can be prevented and the patients’ capacity to solve problems is promoted. This intervention also led to a higher health-related quality of life.
Surprisingly, fatigue also was a main problem in patients who discontinued HPN. Their fatigue scores were higher than those in patients still on HPN. This can possibly be explained by having less energy because of their nutritional status. To maintain their body weight, these patients have to eat often during the day.
Importantly, we included about 70% of all Dutch HPN patients who were treated according to largely similar protocols. The 30% not included in this study did not differ from our sample in gender, age, duration or indication for HPN. Therefore, the sample seems representative of the whole population of HPN patients in the Netherlands. Unfortunately, reasons for not participating are unknown.
We used validated questionnaires and a strength of our present study is that there were no missing data. With the exception of the patients who died, there was no loss to follow-up in 2007.
A weakness of this study, however, is that although we included about 70% of the Dutch HPN population, the sample size as a whole remains relatively small. Due to this problem, we could only include the total SIP-68 score in our analysis and not its different subscales. Based on these notions, an additional longitudinal, and ideally a multicentre international study, is recommended. Several factors, including variables of disease severity, subscales of the SIP-68, sleep disturbance, and general and HPN-related characteristics could be included in this study.
The importance of identifying modifiable factors to predict fatigue is that these can help in the prevention and treatment of this problem.