The Effects of Dialysis Modality and Emotional Distress on Fatigue in Patients Undergoing Dialysis

Hemodialysis (HD) and peritoneal dialysis (PD) are the primary major methods of renal replacement therapy for patients diagnosed with end-stage renal disease (ESRD). While dialysis has significantly improved the survival rate of ESRD patients, these individuals often experience a range of physiological, psychological, and social issues. Fatigue is a prevalent symptom among ESRD patients [1], significantly impacting their quality of life and daily functioning. However, there is no universally accepted definition of fatigue. Ream et al. [2] defined fatigue as “a subjective, unpleasant symptom that encompasses feelings of tiredness and exhaustion.” Evidence has demonstrated that fatigue directly increases the risk of mortality and hospitalization in dialysis patients [3]. Despite the high levels of fatigue among dialysis patients, it remains largely under-recognized. Existing studies have primarily focused on fatigue in HD patients, with limited investigations into fatigue among PD patients. Additionally, few studies have compared the degree of fatigue between these patient groups.

Psychological symptoms, particularly anxiety and depression, are frequently noticed among dialysis patients. However, the correlation between psychological factors and fatigue has not been extensively studied. In our research, we examined the psychological status of anxiety and depression in dialysis patients. We also collected information regarding insomnia among participants and investigated its association with fatigue. This study evaluated fatigue in 256 dialysis patients, compared fatigue levels between the PD and HD groups, explored potential factors influencing fatigue, and provided evidence for the prevention and management of fatigue in dialysis patients.

A total of 256 ESRD patients who regularly underwent PD or HD in a comprehensive hospital in Hunan province between June 2019 and January 2020 were included in this study. The inclusion criteria were as follows: (1) ESRD patients who had undergone PD or HD for at least 3 months, and PD patients receiving continuous ambulatory PD; (2) patients aged between 18 and 80 years; (3) all patients voluntarily participated in this study and provided written informed consent form prior to enrollment. The exclusion criteria were as follows: (1) patients receiving combined PD and HD therapy; (2) patients with active medical disease, including acute heart failure, myocardial infarction, cerebrovascular disorders, severe infectious diseases, and tumors; (3) patients unable to fully comprehend the questionnaire or cooperate with the survey.

Patients’ demographic characteristics including sex, age, primary disease, duration of dialysis, body mass index (BMI), systolic blood pressure, diastolic pressure, marital status, living arrangements, educational level, occupational status, monthly income, smoking, and drinking, were recorded.

The Multidimensional Fatigue Inventory-20 (MFI-20) is a well-established instrument used to assess the fatigue levels of participants over the past 2 weeks. It comprises five dimensions of fatigue: general fatigue, physical fatigue, reduced motivation, reduced activity, and mental fatigue [4]. The Chinese version of the MFI-20 has been demonstrated to possess high validity and excellent reliability [5]. The MFI-20 consists of 20 items, rated on a five-point Likert scale (ranging from 1 to 5), with a total score range of 20–100. A higher total score indicates a more severe level of fatigue.

The Athens Insomnia Scale (AIS) was initially designed based on the original diagnostic criteria for sleep disorders and has been translated into multiple languages [6]. The Chinese version of the AIS assesses sleeping difficulties experienced in the past month based on subjective sleep sensations [7]. The AIS consists of 8 items, with the first 5 items evaluating nighttime insomnia symptoms and the last 3 items assessing daytime consequences of insomnia. Each item is scored from 0 to 3 points, and the sum of the item scores yields the total AIS score, ranging from 0 to 24 points. A higher total AIS score indicates poorer sleep quality. Total scores below 4, between 4 and 6, and above 6 indicate the absence of a sleep disorder, suspected insomnia, and diagnosed insomnia, respectively [6].

The Hospital Anxiety and Depression Scale (HADS) was originally developed to identify anxiety and depression among patients in nonpsychiatric hospital clinics [8]. The Chinese version of the HADS has been shown to possess high validity and reliability in Chinese patients [9, 10]. This scale consists of two subscales: the anxiety subscale (HADS-A) and the depression subscale (HADS-D). Each subscale comprises 7 items, with each item scored from 0 to 3 points. Scores exceeding 7 on either subscale indicate a diagnosis of anxiety or depression. A higher total score indicates more severe symptoms.

The statistical analysis was performed using SPSS 25.0 software (IBM, Armonk, NY, USA). Descriptive analysis was conducted for the general characteristics and findings of the relevant scales. Quantitative data were presented as mean ± standard deviation (⁠$x¯$ ± s), while qualitative data were expressed as percentages (%). The normality of the data was assessed using the Shapiro-Wilk test. Continuous data between two groups were compared using either the independent t test or the Mann-Whitney U test. The χ² test or Fisher’s exact test was employed for the comparison of categorical data. Pearson correlation or Spearman correlation analysis was used accordingly. Multivariate linear regression analysis was performed to explore the factors influencing fatigue in ESRD patients. A p value of less than 0.05 was considered statistically significant.

A total of 256 patients were included in the analysis, with 160 undergoing PD and 96 undergoing HD. The mean age was 50.04 ± 11.95 years for PD patients and 52.84 ± 11.94 years for HD patients. The general demographic characteristics are shown in Table 1. There were no significant differences in the general demographic data between the PD and HD groups (p > 0.05), indicating that the two groups were comparable.

The total fatigue score was 53.83 ± 14.22 points in the PD group and 57.92 ± 16.35 points in the HD group. The scores for the general fatigue and physical fatigue dimensions were significantly lower in the PD group compared to the HD group (p < 0.05) (Table 2).

In the PD group, there were 71 cases of insomnia, 45 cases of suspected insomnia, 19 cases of anxiety, and 31 cases of depression. In the HD group, there were 41 cases of insomnia, 27 cases of suspected insomnia, 13 cases of anxiety, and 33 cases of depression. The prevalence of depression was significantly higher in the HD group than in the PD group (p < 0.05), while the prevalence of anxiety and insomnia did not differ significantly between the two groups (Table 1).

Fatigue in patients undergoing PD and HD was not associated with primary disease, marital status, living arrangements, smoking, and drinking. In the PD group, the total fatigue score was positively correlated with age, BMI, occupational status, income, insomnia score, anxiety score, and depression score (p < 0.05). Similarly, in the HD group, fatigue was positively correlated with age, duration of dialysis, educational level, income, insomnia score, anxiety score, and depression score (p < 0.05) (Tables 3, 4).

A stepwise regression model was used to identify the independent factors of fatigue in the dialysis population. The results of the multivariate regression analysis revealed that income and depression were the major factors influencing fatigue in patients undergoing PD, while duration of dialysis, income, and depression were the major factors influencing fatigue in patients undergoing HD (Table 5).

The findings of the present study indicate that the total fatigue score is associated with age, duration of dialysis, BMI, occupational status, educational level, monthly income, sleep, anxiety, and depression. Furthermore, duration of dialysis, income, and depression can independently predict the severity of fatigue in patients undergoing dialysis. This study compares the degree of fatigue between different dialysis modes and identifies factors influencing fatigue in PD and HD patients. These findings can assist healthcare professionals in focusing on fatigue in dialysis patients, identifying those at high risk of fatigue, and initiating appropriate treatment measures earlier.

To date, there are a limited number of studies comparing the degree of fatigue between PD and HD patients. Our study demonstrates that PD is associated with less fatigue compared to HD, which is consistent with a previous study [11]. However, other studies have failed to find such relationships [3, 12, 13]. PD offers advantages over HD in terms of job stability and daily living, as PD is typically being performed at home. We also observe lower scores in general fatigue and physical fatigue in the PD group. Therefore, it is crucial to pay attention to fatigue symptoms in dialysis patients, in addition to clinical indicators. Specifically, HD patients should receive greater attention as they are at a higher risk of fatigue compared to peritoneal dialysis patients.

Fatigue in patients with ESRD on dialysis is associated with various demographic factors. Previous studies have demonstrated that age is independently associated with fatigue [14]. Our study confirms that fatigue increases with age in patients undergoing dialysis. We speculate that elderly patients may experience physiological changes associated with aging, as well as the psychosocial effects of chronic illness. Additionally, the elderly may lack knowledge of how to cope with fatigue. We also find that fatigue is associated with the duration of dialysis. Consistent with our findings, previous studies have shown that patients with longer dialysis duration experience more severe fatigue [15]. Individuals with longer dialysis duration are at a higher risk of malnutrition, inflammation, and complications, all of which might worsen the fatigue. Kim et al. investigated fatigue and its influencing factors in 104 HD patients and found a correlation between fatigue and weight gain [16]. Obesity has been linked to varying degrees of fatigue in various diseases due to the limited mobility and compromised cardiopulmonary function in obese patients [17, 18]. While our study reveals an association between the fatigue score of PD patients and BMI, no such association is observed in the HD group. This may be attributed to a few individuals with higher BMI in our study.

Furthermore, our research findings suggest that individuals with higher educational levels experience lower levels of fatigue. Compared to patients with lower educational levels, those with higher educational levels are likely more aware of the severity and consequences of their illness and pay more attention to their health. Additionally, higher education is often accompanied by better economic circumstances, resulting in a reduced financial burden of treatment and access to better healthcare options.

The results of the present research indicate that fatigue in patients undergoing HD and PD is positively associated with scores of insomnia, anxiety, and depression. Patients with poorer mental status in terms of sleep quality, anxiety, and depression experience higher severity of fatigue. This suggests that sleep quality, anxiety, and depression significantly influence fatigue, regardless of the dialysis method used for ESRD patients. Furthermore, the results of multivariate regression analysis indicate that depression score is independently associated with the degree of fatigue in both HD and PD patients.

Previous studies have shown that sleep disorders are common among patients receiving dialysis [19]. Fatigue in ESRD is significantly associated with sleep quality [20, 21]. It has been hypothesized that excessive daytime sleepiness and increased levels of certain inflammatory cytokines contribute to fatigue-induced sleep disorders [22]. There may be shared cellular inflammatory factors between signaling pathways of sleep disorders and fatigue. Further research is needed to investigate the possible mechanisms linking fatigue and sleep disorders. The aforementioned findings suggest that improving sleep disorders could potentially prevent or alleviate fatigue in patients undergoing dialysis.

Depression is a common mental issue among patients receiving dialysis, with estimated prevalence rates ranging from 13.1% to 76.3% [23]. Depression in the dialysis population has been independently associated with increased mortality, primarily due to its role in promoting the expression of inflammatory cytokines [24]. The positive relationship between fatigue and depression observed in our study is consistent with previous studies [25, 26]. In fact, fatigue is one of the diagnostic criteria for major depression. Screening scales for fatigue and depression have overlapping symptoms. Some scholars have speculated that depression and fatigue interact through inflammatory pathways [26, 27]. Additionally, depressed patients are at an increased risk of fatigue due to poor therapy compliance and decreased social interactions. Further studies are needed to determine the causality between fatigue and depression. It is worth mentioning that the prevalence of depression was significantly lower in the PD group compared to the HD group (p < 0.05). This may partially contribute to the lower fatigue levels in PD patients versus HD patients. One possible explanation for this finding is that PD patients experience less daily time restriction and have a better quality of life compared to HD patients. However, our discovery is in agreement with some studies [28, 29], but not all [30].

Existing literature indicates that the risk of anxiety in dialysis patients is much higher than in the general population [31]. Our study found a positive association between anxiety and fatigue, which is consistent with findings in other diseases such as cancer [32] and sarcoidosis [32]. However, no studies have directly reported the correlation between anxiety and fatigue in patients with CKD. Anxiety and depressive disorders often coexist due to their bidirectional relationship [33]. Therefore, we speculate that anxiety could be associated with fatigue through its interaction with depression. In summary, it is important to pay attention not only to the somatic health but also to the mental health of patients undergoing dialysis in order to identify individuals at increased risk for fatigue.

Finally, the present study has several limitations that should be taken into consideration. Due to the cross-sectional design of the survey, prospective longitudinal studies need to be conducted to further explore factors influencing fatigue in ESRD patients undergoing dialysis. Additionally, this study was conducted at a single center, and therefore, the findings do not reflect the overall fatigue level of Chinese patients undergoing dialysis. Furthermore, the potential effects of drugs were not accounted for in this study.

This study aimed to investigate fatigue, mental status, and related influencing factors in ESRD patients undergoing dialysis. The results revealed that fatigue was a common complaint among dialysis patients, with a lower level of fatigue observed in the PD group compared to the HD group. Fatigue in patients undergoing dialysis was found to be associated not only with demographic characteristics such as age, duration of dialysis, and income but also with mental factors including sleep quality, anxiety, and depression. Furthermore, depression was identified as an independent predictor of fatigue in both HD and PD patients.

We appreciate those who participated in the study for their cooperation and help.

This study was approved by the Ethics Committee of the Third Xiangya Hospital of Central South University (Approval No. 2020-S356). All patients voluntarily participated in this study and provided written informed consent form prior to enrollment.

The authors state they have no conflicts of interest.

The study was not supported by funding.

Qin Ouyang, Fengjie Yang, and Xinyue Peng were responsible for designing this study and manuscript drafting. Jianwen Wang and Fengjie Yang are responsible for data collection and collation. Hong Wu, Shiqi Tang, and Yuxin Li contributed to data analysis and literature search. Jianwen Wang and Jun Liu reviewed and edited the manuscript. All authors reviewed and edited the manuscript and approved the final version of the manuscript.

Qin Ouyang and Fengjie Yang contributed equally to this work.