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. 2021 Feb 10;16(2):e0246890. doi: 10.1371/journal.pone.0246890

Comparisons of fatigue between dialysis modalities: A cross-sectional study

Yukio Maruyama 1,*, Masaaki Nakayama 2, Atsushi Ueda 3, Mariko Miyazaki 4, Takashi Yokoo 1
Editor: Andrea K Viecelli5
PMCID: PMC7875388  PMID: 33566855

Abstract

Background

Fatigue is one of the most frequent complications in dialyzed patients and is associated with poorer patient outcomes. Multiple factors are reported to be associated with fatigue development. Of them, the impacts of dialysis modalities remain unknown.

Methods

A total of 194 dialysis patients (mean age, 61±11 years; 134 males; modalities included hemodialysis (HD) in 26, online hemodiafiltration (HDF) in 74, peritoneal dialysis (PD) in 68, and combined therapy with PD and HD in 26 cases) were recruited for this cross-sectional study. Fatigue was assessed using the Profile of Mood States (POMS), a Visual Analogue Scale (VAS), and our original scale of fatigue, and depression was assessed by the Beck Depression Inventory-second edition (BDI-II). Our original scale of fatigue was administered both on dialysis and dialysis-free days to patients on HD and online HDF.

Results

The scores of the POMS, VAS, and our original scale were weakly but significantly inter-related (rho = 0.58, P<0.01; rho = 0.47, P<0.01, and rho = 0.42, P<0.01 between POMS and VAS, POMS and our original scale for fatigue, and VAS and our original scale for fatigue, respectively). The scores of these 3 tests showed no significant differences among the 4 modalities. On multivariate analysis, age, body mass index, creatinine, and employment status were associated with the presence or severity of fatigue, whereas dialysis modality was not. A similar result was obtained in 122 patients without depression. The prevalence of fatigue by our original scale was significantly lower on dialysis-free days than on dialysis days in patients on HD and online HDF.

Conclusions

The results suggest that there is no significant association between different dialysis modalities including HD, online HDF, PD and combined therapy with PD and HD and the prevalence or severity of fatigue.

Introduction

Fatigue is one of the most frequent complications in patients receiving renal replacement therapy, and its prevalence has been reported to range from 42% to 89%, depending on patients’ characteristics and assessment tools [1]. Notably, the presence of fatigue was associated with higher mortality in dialyzed patients [2–4]. Several factors, including physiological, psychological or behavioral, sociodemographic, and dialysis-related factors are associated with the development of fatigue [5]. Among them, physiological factors such as anemia, inflammation, malnutrition, uremia, and comorbidities are thought to be important because they are all modifiable. Depression, the most important psychological factor, is strongly associated with fatigue [6, 7] and is also associated with worse outcomes in patients on dialysis [8–10]. There have been several therapeutic strategies including both pharmacological and non-pharmacological approaches [1, 5].

Hemodialysis (HD) per se could induce fatigue through several factors such as bio-incompatibility of the dialyzer and dialysis apparatus which could induce production of pro-inflammatory cytokines or acute reduction of body fluid along with a decrease in blood pressure, whereas peritoneal dialysis (PD) per se could induced fatigue through dwelling of a bio-incompatible PD solution, chronic overhydration status, or a physiological burden [1, 5]. However, there have been only limited studies comparing the severity of fatigue between HD and PD patients [2, 11, 12]. Additionally, studies assessing the fatigue of patients receiving hemodiafiltration (HDF) have been very sparse [13].

The aim of this cross-sectional study was to compare the prevalence and severity of fatigue among patients receiving different dialysis modalities, including HD, online HDF, PD, and combined therapy with PD and HD. Furthermore, the state of depression was assessed in order to exclude possible psychological factors related to fatigue in these patients.

Materials and methods

Subjects

In this cross-sectional study, 194 patients receiving HD (n = 26, 13.4%), online HDF (n = 74, 38.1%), PD (n = 68, 35.1%), and combined therapy with PD and HD (n = 26, 13.4%) at Jikei University Hospital (Tokyo, Japan), the Jikei University Kashiwa Hospital (Chiba, Japan), the Jikei University Katsushika Medical Center (Tokyo, Japan), Shinagawa Kidney Clinic (Tokyo, Japan), Iidabashi Murai Clinic (Tokyo, Japan), Aoto Kidney Clinic (Tokyo, Japan), and Shin Kashiwa Clinic (Kashiwa, Chiba) were recruited between April 2018 and December 2018. Patients under 18 years of age, in addition to patients with a mental disorder, such as schizophrenia, depression or dementia, and those with terminal cancer were excluded. The ethics committees at Tohoku University Hospital and Jikei University Hospital approved this study protocol, and written, informed consent was obtained from all patients.

Samples

Blood samples were collected once a month at regular outpatient visits from patients undergoing PD and at the start of HD treatment after the longest interval from those undergoing HD, online HDF, and combined therapy with PD and HD. Laboratory tests were conducted by standard laboratory techniques. Of note, approximately 20% of all patients had C-reactive protein (CRP) levels below the detectable levels, and the results of these patients are reported as being at the detectable levels. Each patient’s employment status was determined using a self-reported questionnaire.

Assessments of fatigue and depression

The patients’ fatigue was evaluated using the Profile of Mood States (POMS), a Visual Analogue Scale (VAS), and our original scale of fatigue, whereas depression was assessed using the Beck Depression Inventory-second edition (BDI-II). All questionnaires were written format. The POMS scale is a questionnaire measuring six mood states: tension-anxiety (tension), depression-dejection (depression), anger-hostility (anger), fatigue-inertia (fatigue), vigor-activity (vigor), and confusion-bewilderment (confusion) on a five-point scale from 0 (not at all) to 4 (extreme); the fatigue subscale was used for the analysis. The VAS is a unidimensional scale in which a 100-mm line is anchored at either end by ‘no tiredness at all’ at the left end and ‘complete exhaustion’ at the other. The intensity of fatigue is measured in millimeters from the low (left) end of the scale. Our original scale of fatigue is a five-grade evaluation including Grade 1 (inexhaustible, feels well, and extremely active), Grade 2 (tireless, acts in the ordinary way without a sense of fatigue), Grade 3 (mild fatigue, acts in the ordinary way but feels tired), Grade 4 (moderate fatigue, feels tired with light work), and Grade 5 (intense fatigue, very tired, and falls asleep). Grades 3, 4 and 5 are regarded as fatigued states. We have already used this scale for the assessment of fatigue in two previous studies [14, 15]. Although the effectiveness of this scale has not yet been validated, we used this scale because of its usability and lower cost than other scales. Our original scale of fatigue was administered both on dialysis and dialysis-free days to patients on HD and online HDF.

The BDI–II is a 21-item, self-reported inventory designed to assess the presence and severity of depressive symptoms. Each item is rated on a 4-point scale ranging from 0 to 3, and the total score ranges from 0 to 63. A cutoff score of 14 indicates at least a mild-to-moderate level of depression [16, 17]. For all scales, higher scores indicate an increased level of fatigue or depression. Patients receiving PD or combined therapy with PD and HD answered all self-reported questionnaires at regular outpatient visits. Patients receiving HD or online HDF answered all self-reported questionnaires shortly after dialysis sessions.

Statistical analyses

Data are presented as means ± standard deviation (SD) or medians and interquartile range (IQR), as appropriate. A p-value of less than 0.05 was considered significant. Differences among the four groups of renal dialysis were analyzed using one-way analysis of variance (ANOVA) or the non-parametric Kruskal-Wallis test, as appropriate. Differences were considered significant when the F-value was less than 0.05. The associations between each clinical parameter were calculated using Spearman’s correlation coefficient (rho). Independent factors affecting fatigue were assessed using a logistic regression model. In these analyses, the objective variables were dichotomous variables, including POMS score ≥ 10, VAS score ≥ 48, and our original scale of fatigue score ≥ 3. The changes in our original scale of fatigue between dialysis and dialysis-free day were evaluated using a paired t-test. The cut-off values of the POMS and VAS scores were based on receiver operating characteristic analysis, in which fatigue was defined as our original scale of fatigue score ≥ 3. On multivariate analysis, several confounding factors reported to be associated with fatigue in dialyzed patients, including age, sex, dialysis duration, state of employment, the presence of cardiovascular disease and diabetes, body mass index (BMI), hemoglobin (Hb), and serum albumin, were included. Additionally, confounding factor that had shown an appreciable association (P<0.1) with a measure of fatigue were also included in the multivariate analysis. Of them, dialysis duration was markedly skewed and was therefore log-transformed to normalize its distribution. Additionally, independent factors affecting fatigue were assessed using a multiple regression model with the same confounding factors. In these analyses, POMS, VAS, and our original scale of fatigue were treated as continuous variables, and the POMS score was log-transformed to normalize its distribution. Sensitivity analyses including 122 patients without depression (BDI-II score < 14) were performed. Data were statistically analyzed using STATA version 16.0 (STATA Corporation, College Station, TX, USA).

Results

Table 1 shows the patients’ demographic and biochemical characteristics. The age of the patients was 61 ± 11 years, and males predominated (69.1%). Diabetic patients accounted for 27.3%. Age, sex, prevalence of diabetes, and BMI were not significantly different among the four groups. The duration of dialysis was longer in the HD and online HDF groups (129 (42–259), 153 (96–228), 25 (9–41), and 58 (35–74) months for HD, online HDF, PD, and combined therapy, respectively). Hb was higher in patients receiving combined therapy. Serum creatinine was higher in patients receiving online HDF and combined therapy. Urea nitrogen was higher in patients receiving online HDF. Serum albumin was lower in patients receiving PD and combined therapy. CRP and β2 microglobulin levels showed no significant differences among the four groups.

Table 1. Patients’ characteristics.

All patients HD Online HDF PD Combined Tx P
Number (%) 194 26 (13.4%) 74 (38.1%) 68 (35.1%) 26 (13.4%)
Age (y) 61±11 66±9 59±10 60±12 62±11 0.06
Male sex (%) 134 (69.1%) 19 (73.1%) 46 (62.2%) 51 (75.0%) 18 (69.2%) 0.40
Duration of dialysis (months) 64 (27–152) 129 (42–259) 153 (96–228) 25 (9–41) 58 (35–74) <0.01
Employed (%) 104 (53.9%) 9 (34.6%) 45 (60.8%) 38 (55.9%) 12 (48.0%) 0.12
Smoker (%) 17 (8.9%) 0 (0%) 11 (14.9%) 6 (8.8%) 0 (0%) 0.04
History of CVD (%) 57 (29.4%) 12 (46.2%) 17 (23.0%) 19 (27.9%) 9 (34.6%) 0.14
Diabetes (%) 53 (27.3%) 10 (38.5%) 18 (24.3%) 17 (25.0%) 8 (30.8%) 0.51
Height (cm) 165±9 164±9 165±9 165±9 164±10 0.86
BW (kg) 62.8±14.4 61.9±17.9 61.6±14.8 64.3±13.1 63.0±13.3 0.73
BMI (kg/m2) 23.0±4.4 22.8±5.3 22.4±4.5 23.6±4.2 23.3±3.8 0.40
Systolic BP (mmHg) 142±17 140±16 149±19 136±14 141±16 <0.01
Diastolic BP (mmHg) 80±12 72±13 82±12 80±11 84±11 <0.01
Laboratory findings
    Hemoglobin (g/dL) 11.3±1.2 11.2±1.0 11.1±1.0 11.4±1.2 11.8±1.6 0.04
    Creatinine (mg/dL) 11.5±2.8 10.9±2.3 12.4±2.3 10.5±2.9 12.3±3.2 <0.01
    Urea nitrogen (mg/dL) 59.7±12.5 59.7±12.3 64.9±12.0 55.1±13.5 56.7±14.4 <0.01
    Serum albumin (g/dL) 3.5±0.4 3.8±0.4 3.7±0.3 3.3±0.5 3.1±0.3 <0.01
    CRP (mg/dL) 0.10 (0.05–0.27) 0.17 (0.04–0.26) 0.09 (0.01–0.22) 0.10 (0.05–0.43) 0.10 (0.10–0.29) 0.41
    β2 microglobulin (mg/L) 27.3±7.4 28.7±5.8 28.2±4.1 25.7±0.9 29.7±1.5 0.09
Use of ESAs (%) 171 (88.1%) 21 (80.8%) 61 (82.4%) 64 (94.1%) 25 (96.2%) 0.06
POMS 11.3±4.1 11.6±3.9 11.2±3.8 11.1±4.6 12.0±3.5 0.76
VAS 48 (27–63) 49 (39–56) 46 (21–62) 48 (27–63) 51 (41–63) 0.43
Our original scale of fatigue 3.0±1.0 3.3±0.9 2.9±1.1 2.9±0.9 3.5±0.9 0.02
Our original scale of fatigue (dialysis-free day) 2.4±0.8 2.6±0.8 2.3±0.7 N.A. N.A. 0.08
BDI-II 11 (7–17) 11 (10–13) 10 (6–16) 13 (6–18) 11 (9–19) 0.33
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* n = 168, for values below the detection level, the detection level was used.

Abbreviations: HD, hemodialysis; HDF, hemodiafiltration; PD, peritoneal dialysis; Tx, therapy; CVD, cardiovascular disease; BW, body weight; BMI, body mass index; BP, blood pressure; CRP, C-reactive protein; ESAs, erythropoiesis-stimulating agents; N.A., not applicable; POMS, Profile of Mood States; VAS, Visual Analogue Scale; BDI-II, the Beck Depression Inventory-second edition.

All participants read and responded to the questionnaires themselves. According to the results of the self-reported questionnaire, 104 (53.9%) patients were employed. The percentage of employment was not significantly different among the four groups. Of the 104 patients at work, 92 (88.5%) patients felt that the fatigue affected their work to mild (n = 48, 47.1%), moderate (n = 28, 26.9%), and severe (n = 16, 15.4%) degrees, whereas 10 (9.6%) patients felt that the fatigue did not affect their work. Of the 90 unemployed patients, 75 (83.3%) patients felt that the fatigue affected their daily life to mild (n = 28, 31.1%), moderate (n = 32, 35.6%), and severe (n = 15, 16.7%) degrees, whereas 10 (11.1%) patients felt that the fatigue did not affect their daily life. However, 22 (24.4%) patients wished to work.

The scores of the three assessments for fatigue including POMS, VAS, and our original scale of fatigue were significantly inter-related (rho = 0.58, P<0.01; rho = 0.47, P<0.01, and rho = 0.42, P<0.01 between POMS and VAS, POMS and our original scale for fatigue, and VAS and our original scale for fatigue, respectively). The scores on the POMS and VAS were not significantly different among the four groups, whereas those of our original scale of fatigue were higher in patients receiving combined therapy with PD and HD (Table 1, Fig 1). In the analysis using our original scale of fatigue, the prevalence of fatigue, defined as Grades 3, 4 and 5, was significantly lower on dialysis-free days than on dialysis days in patients on HD and online HDF (50.0% vs. 84.6%; P<0.01 and 32.4% vs. 66.2%; P<0.01 for patients on HD and online HDF, respectively). Similarly, the severity of fatigue, indicated by the scores of this scale, was significantly lower on dialysis-free days than on dialysis days (2.6±0.8 vs. 3.3±0.9; P<0.01 and 2.3±0.7 vs. 2.9±1.1; P<0.01 for patients on HD and online HDF, respectively).

Fig 1. Comparisons of the scores of the POMS, VAS, and our original scale of fatigue in patients receiving HD, online HDF, PD, and combined therapy with PD and HD.

Fig 1

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Abbreviations: POMS, Profile of Mood States; VAS, Visual Analogue Scale; HD, hemodialysis; HDF, hemodiafiltration; PD, peritoneal dialysis. * indicates significance.

Table 2 shows multiple logistic regression models for the results of the three tests, and the modality of dialysis did not affect the presence of fatigue. Instead, employed patients had a significantly lower risk of the presence of fatigue on the VAS and our original scale of fatigue. In addition, BMI, age and the use of erythropoiesis-stimulating agents were associated with the presence of fatigue on the POMS, VAS score and our original scale for fatigue, respectively. The results of the multiple regression model, with analysis using the findings of the three tests as continuous variables, were very similar (Table 3). The modality of dialysis did not affect the severity of fatigue. Instead, employed patients had a significantly lower severity of fatigue on the VAS and our original scale of fatigue. BMI was associated with the severity of fatigue on the POMS score, whereas serum creatinine was associated with the severity of fatigue on the POMS and VAS scores.

Table 2. Logistic regression model for higher scores for fatigue.

Unadjusted Adjusted
Odds ratio (95% CI) P value Odds ratio (95% CI) P value
POMS
Age 1.001 (0.975 to 1.028) 0.92 0.981 (0.950 to 1.014) 0.25
Male gender 0.551 (0.285 to 1.063) 0.08 0.729 (0.336 to 1.579) 0.42
Dialysis duration * 1.106 (0.872 to 1.403) 0.41 1.032 (0.724 to 1.471) 0.86
Employed 0.602 (0.333 to 1.088) 0.09 0.668 (0.321 to 1.391) 0.28
Smoker 0.655 (0.241 to 1.781) 0.41
Dialysis modality
    HD Ref. Ref.
    Online HDF 0.870 (0.342 to 2.215) 0.77 0.760 (0.267 to 2.164) 0.61
    PD 0.712 (0.278 to 1.823) 0.48 1.013 (0.295 to 3.478) 0.98
    Combined therapy 1.437 (0.439 to 4.699) 0.55 1.913 (0.445 to 8.218) 0.38
CVD 0.766 (0.407 to 1.439) 0.41 0.591 (0.288 to 1.216) 0.15
Diabetes 1.244 (0.642 to 2.410) 0.52 1.976 (0.908 to 4.296) 0.09
BMI 0.922 (0.862 to 0.986) 0.02 0.895 (0.825 to 0.970) 0.01
Hemoglobin 0.901 (0.704 to 1.153) 0.41 0.820 (0.619 to 1.087) 0.17
Creatinine 1.037 (0.955 to 1.126) 0.39
Urea nitrogen 0.996 (0.975 to 1.018) 0.72
Serum albumin 1.057 (0.549 to 2.033) 0.87 1.425 (0.566 to 3.587) 0.45
CRP * 0.979 (0.755 to 1.268) 0.87
β2 microglobulin 1.004 (0.959 to 1.052) 0.87
Use of ESAs 1.319 (0.546 to 3.182) 0.54
VAS
Age 0.992 (0.967 to 1.018) 0.56 0.966 (0.934 to 0.998) 0.04
Male gender 0.910 (0.492 to 1.682) 0.76 1.578 (0.744 to 3.351) 0.24
Dialysis duration * 1.173 (0.928 to 1.483) 0.18 1.384 (0.964 to 1.986) 0.08
Employed 0.466 (0.260 to 0.832) 0.01 0.370 (0.176 to 0.776) <0.01
Smoker 1.186 (0.423 to 3.327) 0.75
Dialysis modality
    HD Ref. Ref.
    Online HDF 0.769 (0.314 to 1.884) 0.57 0.629 (0.229 to 1.728) 0.37
    PD 0.938 (0.378 to 2.324) 0.89 1.166 (0.342 to 3.978) 0.81
    Combined therapy 1.821 (0.582 to 5.698) 0.30 1.651 (0.399 to 6.837) 0.49
CVD 0.820 (0.441 to 1.524) 0.53 0.636 (0.312 to 1.295) 0.21
Diabetes 0.963 (0.509 to 1.822) 0.91 1.060 (0.498 to 2.256) 0.88
BMI 0.964 (0.903 to 1.028) 0.27 0.959 (0.887 to 1.038) 0.30
Hemoglobin 1.129 (0.887 to 1.436) 0.33 1.065 (0.808 to 1.404) 0.65
Creatinine 1.039 (0.962 to 1.122) 0.33
Urea nitrogen 0.986 (0.965 to 1.007) 0.20
Serum albumin 0.612 (0.319 to 1.175) 0.14 0.713 (0.285 to 1.787) 0.47
CRP * 1.192 (0.919 to 1.546) 0.19
β2 microglobulin 1.041 (0.993 to 1.090) 0.10
Use of ESAs 0.682 (0.28 to 1.661) 0.40
Our original scale of fatigue
Age 1.014 (0.986 to 1.043) 0.34 0.984 (0.95 to 1.020) 0.38
Male gender 0.855 (0.432 to 1.689) 0.65 1.258 (0.544 to 2.907) 0.59
Dialysis duration * 1.138 (0.884 to 1.464) 0.32 1.136 (0.770 to 1.677) 0.52
Employed 0.394 (0.203 to 0.762) 0.01 0.433 (0.190 to 0.987) 0.047
Smoker 0.319 (0.116 to 0.877) 0.03 0.373 (0.113 to 1.226) 0.10
Dialysis modality
    HD Ref. Ref.
    Online HDF 0.356 (0.111 to 1.147) 0.08 0.422 (0.113 to 1.573) 0.20
    PD 0.333 (0.103 to 1.080) 0.07 0.649 (0.149 to 2.820) 0.56
    Combined therapy 1.394 (0.279 to 6.953) 0.69 1.994 (0.313 to 12.701) 0.47
CVD 0.936 (0.475 to 1.845) 0.85 0.650 (0.289 to 1.464) 0.30
Diabetes 1.550 (0.743 to 3.233) 0.24 1.625 (0.673 to 3.924) 0.28
BMI 0.974 (0.908 to 1.043) 0.45 0.940 (0.861 to 1.026) 0.17
Hemoglobin 1.187 (0.910 to 1.549) 0.21 0.973 (0.699 to 1.352) 0.87
Creatinine 0.976 (0.922 to 1.033) 0.40
Urea nitrogen 1.006 (0.983 to 1.029) 0.61
Serum albumin 0.942 (0.467 to 1.901) 0.87 1.265 (0.452 to 3.535) 0.65
CRP* 1.183 (0.886 to 1.580) 0.26
β2 microglobulin 1.032 (0.982 to 1.085) 0.21
Use of ESAs 0.334 (0.095 to 1.173) 0.09 0.222 (0.052 to 0.951) 0.04
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Abbreviations: CI, confidence interval; POMS, Profile of Mood States; HD, hemodialysis; HDF, hemodiafiltration; PD, peritoneal dialysis; CVD, cardiovascular disease; BMI, body mass index; CRP, C-reactive protein; ESAs, erythropoiesis-stimulating agents; VAS, Visual Analogue Scale.

* Dialysis duration and CRP are log-transformed.

Table 3. Multiple regression model for the scales of fatigue.

Variable Unadjusted Adjusted
Regression coefficient 95%CI t value p value Regression coefficient 95%CI t value p value
POMS (log-transformed)
Age 0.0002 -0.0043 to 0.0048 0.10 0.92 -0.0015 -0.0070 to 0.0039 -0.56 0.57
Male gender -0.0639 -0.1723 to 0.0445 -1.16 0.25 -0.0088 -0.1322 to 0.1147 -0.14 0.89
Dialysis duration * 0.0146 -0.0264 to 0.0556 0.70 0.48 -0.0111 -0.0713 to 0.0491 -0.36 0.72
Employed -0.0824 -0.1831 to 0.0183 -1.61 0.11 -0.1020 -0.2230 to 0.0191 -1.66 0.10
Smoker -0.016 -0.195 to 0.162 -0.18 0.86
Dialysis modality
    HD Ref. Ref.
    Online HDF -0.0290 -0.1884 to 0.1303 -0.36 0.72 -0.0493 -0.2179 to 0.1192 -0.58 0.56
    PD -0.0637 -0.2249 to 0.0975 -0.78 0.44 -0.0517 -0.2546 to 0.1512 -0.5 0.62
    Combined therapy 0.0633 -0.1306 to 0.2572 0.64 0.52 0.0757 -0.1573 to 0.3086 0.64 0.52
CVD -0.0583 -0.1683 to 0.0518 -1.04 0.30 -0.0834 -0.2014 to 0.0347 -1.39 0.17
Diabetes -0.0291 -0.1418 to 0.0837 -0.51 0.61 0.0186 -0.1057 to 0.1429 0.29 0.77
BMI -0.0115 -0.0229 to -0.0002 -2.01 0.046 -0.0149 -0.0279 to -0.0019 -2.26 0.03
Hemoglobin -0.0154 -0.0578 to 0.0270 -0.72 0.48 -0.0240 -0.0694 to 0.0213 -1.05 0.30
Creatinine 0.00889 -0.00057 to 0.01834 1.85 0.07 0.01117 0.00088 to 0.02146 2.14 0.03
Urea nitrogen -0.00022 -0.00394 to 0.00351 -0.12 0.91
Serum albumin -0.0137 -0.1274 to 0.1001 -0.24 0.81 0.0135 -0.1367 to 0.1637 0.18 0.86
CRP * -0.0005 -0.0469 to 0.0458 -0.02 0.98
β2 microglobulin 0.00515 -0.00323 to 0.01353 1.22 0.23
Use of ESAs 0.0724 -0.0828 to 0.2275 0.92 0.36
VAS
Age -0.138 -0.425 to 0.150 -0.94 0.35 -0.274 -0.616 to 0.069 -1.58 0.12
Male gender 0.00 -6.84 to 6.84 0.00 1.00 3.32 -4.36 to 11.00 0.85 0.40
Dialysis duration * 0.59 -1.99 to 3.18 0.45 0.65 1.17 -2.59 to 4.92 0.61 0.54
Employed -6.63 -12.92 to -0.34 -2.08 0.04 -9.73 -17.34 to -2.13 -2.53 0.01
Smoker 3.63 -7.74 to 15.00 0.63 0.53
Dialysis modality
    HD Ref. Ref.
    Online HDF -2.95 -12.90 to 6.99 -0.59 0.56 -3.70 -14.19 to 6.79 -0.70 0.49
    PD 0.19 -9.88 to 10.27 0.04 0.97 0.95 -11.74 to 13.64 0.15 0.88
    Combined therapy 5.67 -6.55 to 17.88 0.92 0.36 3.71 -10.80 to 18.21 0.50 0.61
CVD -0.08 -6.99 to 6.82 -0.02 0.98 -1.21 -8.60 to 6.18 -0.32 0.75
Diabetes 2.08 -5.02 to 9.17 0.58 0.57 2.88 -4.93 to 10.68 0.73 0.47
BMI -0.122 -0.838 to 0.593 -0.34 0.74 -0.439 -1.251 to 0.373 -1.07 0.29
Hemoglobin 1.30 -1.35 to 3.95 0.97 0.34 0.89 -1.95 to 3.72 0.62 0.54
Creatinine 0.698 0.110 to 1.287 2.34 0.02 0.804 0.163 to 1.444 2.47 0.01
Urea nitrogen -0.188 -0.423 to 0.047 -1.58 0.12
Serum albumin -4.38 -11.45 to 2.69 -1.22 0.22 -2.29 -11.64 to 7.05 -0.48 0.63
CRP * 1.99 -0.81 to 4.80 1.40 0.16
β2 microglobulin 0.325 -0.190 to 0.840 1.25 0.21
Use of ESAs -0.26 -9.98 to 9.45 -0.05 0.96
Our original scale of fatigue
Age 0.00995 -0.00290 to 0.02281 1.53 0.13 -0.00397 -0.01915 to 0.01120 -0.52 0.61
Male gender -0.126 -0.434 to 0.182 -0.81 0.42 0.115 -0.230 to 0.460 0.66 0.51
Dialysis duration * 0.0775 -0.0389 to 0.1938 1.31 0.19 0.1007 -0.0664 to 0.2678 1.19 0.24
Employed -0.465 -0.744 to -0.186 -3.29 0.00 -0.339 -0.679 to -0.0003 -1.98 0.050
Smoker -0.433 -0.932 to 0.065 -1.72 0.09 -0.230 -0.756 to 0.296 -0.86 0.39
Dialysis modality
    HD Ref. Ref.
    Online HDF -0.323 -0.766 to 0.120 -1.44 0.15 -0.234 -0.707 to 0.239 -0.98 0.33
    PD -0.387 -0.835 to 0.061 -1.70 0.09 -0.142 -0.708 to 0.424 -0.50 0.62
    Combined therapy 0.269 -0.270 to 0.808 0.99 0.33 0.243 -0.408 to 0.893 0.74 0.46
CVD -0.066 -0.379 to 0.247 -0.41 0.68 -0.217 -0.547 to 0.113 -1.30 0.20
Diabetes 0.274 -0.044 to 0.591 1.70 0.09 0.257 -0.091 to 0.605 1.46 0.15
BMI -0.0126 -0.0451 to 0.0198 -0.77 0.44 -0.0135 -0.0496 to 0.0226 -0.74 0.46
Hemoglobin 0.0468 -0.0733 to 0.1669 0.77 0.44 -0.0017 -0.1290 to 0.1255 -0.03 0.98
Creatinine -0.0254 -0.0522 to 0.0014 -1.87 0.06 -0.0202 -0.0488 to 0.0084 -1.39 0.17
Urea nitrogen -0.00297 -0.01353 to 0.00758 -0.56 0.58
Serum albumin -0.140 -0.459 to 0.179 -0.87 0.39 0.005 -0.414 to 0.425 0.03 0.98
CRP * 0.0403 -0.0843 to 0.1648 0.64 0.52
β2 microglobulin 0.0103 -0.0122 to 0.0329 0.91 0.37
Use of ESAs -0.145 -0.585 to 0.296 -0.65 0.52
Open in a new tab

Abbreviations: CI, confidence interval; POMS, Profile of Mood States; HD, hemodialysis; HDF, hemodiafiltration; PD, peritoneal dialysis; CVD, cardiovascular disease; BMI, body mass index; CRP, C-reactive protein; ESAs, erythropoiesis-stimulating agents; VAS, Visual Analogue Scale.

* Dialysis duration and CRP are log-transformed.

Sensitivity analyses including 122 patients without depression (BDI-II score < 14) were performed. The results of the logistic regression models (Table 4) and those of the multiple regression models (Table 5) were very similar.

Table 4. Logistic regression model for higher scores for fatigue in patients without depression.

Unadjusted Adjusted
Odds ratio (95% CI) P value Odds ratio (95% CI) P value
POMS
Age 0.998 (0.965 to 1.032) 0.90 0.965 (0.920 to 1.011) 0.14
Male gender 0.581 (0.258 to 1.309) 0.19 0.829 (0.308 to 2.229) 0.71
Dialysis duration * 1.076 (0.808 to 1.434) 0.62 0.975 (0.648 to 1.468) 0.91
Employed 0.556 (0.263 to 1.172) 0.12 0.499 (0.196 to 1.269) 0.14
Smoker 0.465 (0.111 to 1.953) 0.30
Dialysis modality
    HD Ref. Ref.
    Online HDF 0.818 (0.289 to 2.317) 0.71 0.647 (0.192 to 2.181) 0.48
    PD 0.662 (0.223 to 1.967) 0.46 0.951 (0.228 to 3.966) 0.95
    Combined therapy 1.473 (0.362 to 5.996) 0.59 2.186 (0.343 to 13.926) 0.41
CVD 0.745 (0.334 to 1.660) 0.47 0.597 (0.242 to 1.474) 0.26
Diabetes 1.227 (0.551 to 2.735) 0.62 2.196 (0.821 to 5.871) 0.12
BMI 0.939 (0.865 to 1.020) 0.14 0.895 (0.802 to 0.998) 0.045
Hemoglobin 0.839 (0.607 to 1.159) 0.29 0.747 (0.512 to 1.088) 0.13
Creatinine 0.992 (0.873 to 1.127) 0.90
Urea nitrogen 0.989 (0.962 to 1.016) 0.43
Serum albumin 1.214 (0.503 to 2.931) 0.67 1.316 (0.355 to 4.877) 0.68
CRP * 0.988 (0.693 to 1.409) 0.95
β2 microglobulin 1.014 (0.954 to 1.077) 0.66
Use of ESAs 1.209 (0.409 to 3.570) 0.73
VAS
Age 0.993 (0.959 to 1.028) 0.69 0.959 (0.911 to 1.009) 0.11
Male gender 0.933 (0.412 to 2.111) 0.87 1.329 (0.473 to 3.734) 0.59
Dialysis duration * 1.290 (0.949 to 1.753) 0.10 1.321 (0.852 to 2.048) 0.21
Employed 0.459 (0.215 to 0.979) 0.04 0.372 (0.141 to 0.984) 0.046
Smoker 0.44 (0.085 to 2.277) 0.33
Dialysis modality
    HD Ref. Ref.
    Online HDF 0.501 (0.176 to 1.433) 0.20 0.342 (0.099 to 1.182) 0.09
    PD 0.443 (0.146 to 1.344) 0.15 0.551 (0.127 to 2.385) 0.43
    Combined therapy 1.309 (0.316 to 5.431) 0.71 1.225 (0.188 to 7.966) 0.83
CVD 0.838 (0.370 to 1.897) 0.67 0.663 (0.261 to 1.686) 0.39
Diabetes 1.072 (0.474 to 2.426) 0.87 1.502 (0.555 to 4.065) 0.42
BMI 0.952 (0.876 to 1.036) 0.26 0.931 (0.832 to 1.041) 0.21
Hemoglobin 1.150 (0.831 to 1.591) 0.40 1.052 (0.715 to 1.548) 0.80
Creatinine 1.026 (0.901 to 1.169) 0.70
Urea nitrogen 0.988 (0.960 to 1.017) 0.40
Serum albumin 0.930 (0.380 to 2.275) 0.87 0.816 (0.211 to 3.149) 0.77
CRP * 0.935 (0.651 to 1.342) 0.71
β2 microglobulin 1.021 (0.959 to 1.086) 0.52
Use of ESAs 0.607 (0.205 to 1.798) 0.37
Our original scale of fatigue
Age 1.003 (0.969 to 1.038) 0.87 0.953 (0.904 to 1.005) 0.08
Male gender 1.051 (0.464 to 2.384) 0.90 1.222 (0.417 to 3.582) 0.71
Dialysis duration * 1.101 (0.821 to 1.476) 0.52 1.129 (0.717 to 1.776) 0.60
Employed 0.436 (0.196 to 0.970) 0.04 0.440 (0.154 to 1.257) 0.13
Smoker 0.157 (0.031 to 0.792) 0.03 0.140 (0.021 to 0.944) 0.04
Dialysis modality
    HD Ref. Ref.
    Online HDF 0.293 (0.086 to 1.003) 0.051 0.267 (0.064 to 1.114) 0.07
    PD 0.309 (0.087 to 1.098) 0.07 0.601 (0.114 to 3.154) 0.55
    Combined therapy 0.917 (0.170 to 4.930) 0.92 0.958 (0.112 to 8.208) 0.97
CVD 0.951 (0.419 to 2.157) 0.90 0.655 (0.238 to 1.801) 0.41
Diabetes 1.987 (0.829 to 4.760) 0.12 2.475 (0.782 to 7.833) 0.12
BMI 1.011 (0.931 to 1.098) 0.79 0.946 (0.842 to 1.063) 0.35
Hemoglobin 1.239 (0.885 to 1.735) 0.21 0.922 (0.591 to 1.438) 0.72
Creatinine 1.048 (0.918 to 1.197) 0.49
Urea nitrogen 1.004 (0.977 to 1.033) 0.76
Serum albumin 1.050 (0.426 to 2.587) 0.92 0.916 (0.212 to 3.946) 0.91
CRP * 1.276 (0.872 to 1.867) 0.21
β2 microglobulin 1.035 (0.973 to 1.101) 0.27
Use of ESAs 0.212 (0.046 to 0.986) 0.048 0.195 (0.031 to 1.213) 0.08
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Abbreviations: CI, confidence interval; POMS, Profile of Mood States; HD, hemodialysis; HDF, hemodiafiltration; PD, peritoneal dialysis; CVD, cardiovascular disease; BMI, body mass index; CRP, C-reactive protein; ESAs, erythropoiesis-stimulating agents; VAS, Visual Analogue Scale.

* Dialysis duration and CRP are log-transformed.

Table 5. Multiple regression model for the scales of fatigue in patients without depression.

Variable Unadjusted Adjusted
Regression coefficient 95%CI t value p value Regression coefficient 95%CI t value p value
POMS (log-transformed)
Age 0.0015 -0.0037 to 0.0066 0.56 0.58 -0.0030 -0.0098 to 0.0039 -0.86 0.39
Male gender -0.0692 -0.1921 to 0.0538 -1.11 0.27 -0.0016 -0.1460 to 0.1427 -0.02 0.98
Dialysis duration * 0.0171 -0.0268 to 0.0611 0.77 0.44 -0.0054 -0.0665 to 0.0558 -0.17 0.86
Employed -0.1138 -0.2257 to -0.0019 -2.01 0.046 -0.1117 -0.2472 to 0.0239 -1.63 0.11
Smoker -0.103 -0.312 to 0.107 -0.97 0.33
Dialysis modality
    HD Ref. Ref.
    Online HDF -0.0618 -0.2205 to 0.0970 -0.77 0.44 -0.0818 -0.2587 to 0.0951 -0.92 0.36
    PD -0.128 -0.293 to 0.038 -1.52 0.13 -0.102 -0.313 to 0.108 -0.96 0.34
    Combined therapy 0.0510 -0.1581 to 0.2601 0.48 0.63 0.0648 -0.2027 to 0.3322 0.48 0.63
CVD -0.0326 -0.1560 to 0.0908 -0.52 0.60 -0.0750 -0.2069 to 0.0569 -1.13 0.26
Diabetes -0.0223 -0.1458 to 0.1012 -0.36 0.72 0.0178 -0.1232 to 0.1587 0.25 0.80
BMI -0.0079 -0.0201 to 0.0044 -1.28 0.21 -0.0090 -0.0242 to 0.0062 -1.17 0.24
Hemoglobin -0.0309 -0.0794 to 0.0176 -1.26 0.21 -0.0391 -0.0927 to 0.0145 -1.45 0.15
Creatinine -0.00451 -0.02416 to 0.01515 -0.45 0.65
Urea nitrogen -0.00011 -0.00429 to 0.00407 -0.05 0.96
Serum albumin -0.0165 -0.1530 to 0.1200 -0.24 0.81 -0.0249 -0.2159 to 0.1661 -0.26 0.80
CRP * 0.0036 -0.0535 to 0.0608 0.13 0.90
β2 microglobulin 0.00693 -0.00259 to 0.01644 1.45 0.15
Use of ESAs 0.0432 -0.1237 to 0.2102 0.51 0.61
VAS
Age -0.081 -0.434 to 0.273 -0.45 0.65 -0.393 -0.858 to 0.071 -1.68 0.10
Male gender 4.22 -4.08 to 12.52 1.01 0.32 5.82 -3.69 to 15.33 1.21 0.23
Dialysis duration * 1.31 -1.65 to 4.27 0.88 0.38 1.22 -2.83 to 5.27 0.6 0.55
Employed -5.07 -12.66 to 2.53 -1.32 0.19 -6.78 -15.77 to 2.22 -1.49 0.14
Smoker -3.92 -18.53 to 10.68 -0.53 0.60
Dialysis modality
    HD Ref. Ref.
    Online HDF -5.77 -16.24 to 4.71 -1.09 0.28 -6.21 -17.85 to 5.43 -1.06 0.29
    PD -6.80 -17.79 to 4.19 -1.22 0.22 -4.45 -18.38 to 9.49 -0.63 0.53
    Combined therapy 8.29 -5.82 to 22.40 1.16 0.25 7.29 -10.32 to 24.90 0.82 0.41
CVD 2.20 -6.05 to 10.44 0.53 0.60 0.82 -7.93 to 9.57 0.19 0.85
Diabetes 4.22 -4.09 to 12.52 1.01 0.32 6.81 -2.52 to 16.14 1.45 0.15
BMI -0.333 -1.153 to 0.486 -0.81 0.42 -0.828 -1.830 to 0.175 -1.64 0.11
Hemoglobin 2.33 -0.91 to 5.58 1.42 0.16 1.07 -2.48 to 4.62 0.6 0.55
Creatinine 0.595 -0.728 to 1.919 0.89 0.38
Urea nitrogen -0.098 -0.385 to 0.189 -0.68 0.50
Serum albumin -0.76 -9.87 to 8.36 -0.16 0.87 -1.19 -13.76 to 11.38 -0.19 0.85
CRP * 0.04 -3.64 to 3.72 0.02 0.98
β2 microglobulin 0.120 -0.507 to 0.747 0.38 0.70
Use of ESAs 0.01 -11.14 to 11.16 0.00 1.00
Our original scale of fatigue
Age 0.00967 -0.00787 to 0.02720 1.09 0.28 -0.0117 -0.0339 to 0.0105 -1.05 0.30
Male gender -0.105 -0.523 to 0.314 -0.49 0.62 0.100 -0.360 to 0.560 0.43 0.67
Dialysis duration * 0.0392 -0.1111 to 0.1894 0.52 0.61 0.0968 -0.0981 to 0.2916 0.98 0.33
Employed -0.521 -0.895 to -0.146 -2.75 0.01 -0.408 -0.844 to 0.028 -1.86 0.07
Smoker -0.955 -1.641 to -0.269 -2.76 0.01 -0.803 -1.510 to -0.096 -2.25 0.03
Dialysis modality
    HD Ref.
    Online HDF -0.420 -0.944 to 0.104 -1.59 0.12 -0.422 -0.990 to 0.146 -1.47 0.14
    PD -0.311 -0.858 to 0.237 -1.12 0.26 -0.107 -0.783 to 0.570 -0.31 0.76
    Combined therapy 0.543 -0.1478 to 1.234 1.56 0.12 0.278 -0.590 to 1.145 0.64 0.53
CVD -0.103 -0.522 to 0.316 -0.49 0.63 -0.323 -0.744 to 0.098 -1.52 0.13
Diabetes 0.395 -0.018 to 0.809 1.89 0.06 0.457 -0.001 to 0.914 1.98 0.05
BMI 0.0123 -0.0294 to 0.0541 0.59 0.56 -0.0064 -0.0548 to 0.0420 -0.26 0.79
Hemoglobin 0.0224 -0.1434 to 0.1882 0.27 0.79 -0.0830 -0.2561 to 0.0901 -0.95 0.34
Creatinine -0.0013 -0.0681 to 0.0654 -0.04 0.97
Urea nitrogen -0.01070 -0.02475 to 0.00335 -1.51 0.13
Serum albumin -0.353 -0.804 to 0.098 -1.55 0.12 -0.229 -0.849 to 0.390 -0.73 0.46
CRP * 0.113 -0.067 to 0.293 1.25 0.22
β2 microglobulin 0.0163 -0.0153 to 0.0479 1.03 0.31
Use of ESAs -0.350 -0.913 to 0.214 -1.23 0.22
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Abbreviations: CI, confidence interval; POMS, Profile of Mood States; HD, hemodialysis; HDF, hemodiafiltration; PD, peritoneal dialysis; CVD, cardiovascular disease; BMI, body mass index; CRP, C-reactive protein; ESAs, erythropoiesis-stimulating agents; VAS, Visual Analogue Scale.

* Dialysis duration and CRP are log-transformed.

Discussion

In this cross-sectional study, the prevalence and the severity of fatigue were not significantly different among patients receiving different dialysis modalities (HD, online HDF, PD, and combined therapy with PD and HD). There was a particular focus on the effect of the presence of depression in the present study because fatigue and depression are closely interrelated, and depression may manifest as feelings of tiredness and lack of energy [1, 5]. The fatigue profile was examined in 122 patients without depression in a sensitivity analysis, and the prevalence and the severity of fatigue were not significantly different among patients receiving different dialysis modalities. Additionally, the prevalence of fatigue by our original scale was significantly lower on dialysis-free days than on dialysis days in patients on HD and online HDF.

There have been several studies comparing the severity of fatigue between HD and PD patients. Zazzeroni et al. [11] conducted a systematic review and meta-analysis including 7 studies and 1857 dialyzed patients, of whom 1165 were undergoing HD and 692 were undergoing PD, and they found that the scores of the energy/fatigue subscales were not different between the two groups. Jhamb et al. [2] reported that the SF-36 vitality scales at baseline and 1-year after dialysis initiation were not significantly different between incident HD and PD patients. In the present study, there were no significant differences in the fatigue scales between HD and PD, and the results were consistent with those prior reports.

To the best of our knowledge, this was the first study to examine fatigue in patients receiving online HDF or combined therapy with PD and HD. Online HDF, where replacement fluid is prepared by further purifying dialysate fluid instead of manufacturer-provided solutions, has made HDF more practical and more cost-effective, and high-volume online HDF could potentially improve symptoms, reduce morbidity, and may even improve survival [18]. The number of patients treated with online HDF has been increasing after the 2012 revision to the medical reimbursement system, and it has reached 70000, approximately 30% of all dialysis patients at the end of 2017 in Japan [19]. Suwabe et al. [13] conducted a systematic review and meta-analysis to compare QOL between patients receiving online HDF and HD and concluded that online HDF was associated with a non-significant decrease in the fatigue score compared to HD. Of note, online HDF with post dilution was performed in all of the studies, whereas more than 95% of patients used predilution online HDF in Japan because of the lower blood flow rate and lower serum albumin levels [19]. Because the predilution method is considered advantageous due to the availability of a large volume of substitution solution and lower albumin leakage than the post-dilution method, it could have a good effect on the prevention of fatigue. Although a PD first policy is recommended in order to maximize the advantages of PD therapy including excellent comparable survival, lower cost and improved QOL [20, 21], its long-term continuation is difficult because of a decrease in residual renal function and deterioration of the peritoneal membrane. Combined therapy with PD and HD was introduced in Japan in the 1990s and became popular as the preferred dialysis modality of Japan. The combined therapy, generally in the form of 5–6 days of PD and one HD session per week, is the treatment option for PD patients with inadequate dialysis and/or fluid overload instead of a complete shift to HD alone, and approximately 1900 patients (20% of all patients on PD) are receiving this therapy in Japan [22, 23]. This unique modality is expected to reduce fatigue compared to direct transfer to HD because of a decrease in the number of HD sessions. However, in the current study, there was no significant difference in the fatigue scales between patients receiving online HDF and combined therapy with PD and HD.

While dialysis modalities were not associated with fatigue in dialysis patients in the present study, several influential factors were identified by multivariate analysis, such as age, BMI, creatinine, and employment status. The present findings were consistent with a prior report that showed employment status to be strongly associated with fatigue and depression in HD patients [24–26]. In the present study, more than 80% of patients felt that the fatigue affected their work or daily life, including those who were unemployed, but wished to work. Thus, it is possible that fatigue may have a negative impact patients’ will to work. Interestingly, the prevalence of fatigue, defined as Grades 3, 4 and 5 in our original scale of fatigue, and the severity of fatigue, indicated by the scores of this scale, were significantly lower on dialysis-free days than on dialysis days in patients on HD and online HDF. Thus, these daily fluctuations in fatigue in relation to HD and online HDF session warrant further investigations.

The POMS, VAS, and our original scale of fatigue were used to evaluate fatigue in the present study. Although the 36-item Short-Form general health survey (SF-36), especially its vitality scale is frequently used in this area [2, 3], the POMS was used instead for two reasons. First, it includes the fatigue scale. Second, it is widely used in clinical practice and covered by the public medical insurance system in Japan. The scales of fatigue might differ by several sociodemographic factors such as age, sex, and race. The median scores of the fatigue subscale of the POMS scores in a Polish study including 115 dialysis patients were around 5 to 11, lower than in the present study [27], whereas this score at baseline of a randomized, controlled trial including 15 HD patients in the U.S.A. was similar to the present study [28]. The associations between the scores of these three scales were significant but weak. Additionally, the effects of several confounding factors, such as age, BMI, employment status and serum creatinine, on the presence or severity of fatigue differed depending on the scales. These discrepancies indicate the fact that different measures could yield different results. However, the presence or the severity of fatigue assessed using all scales did not differ significantly among patients receiving different dialysis modalities.

There were some limitations in this study. First, the cross-sectional, observational nature of the study allowed the identification of associations, but not causal relationships between fatigue and clinical variables, including dialysis modality. Additionally, the effect of residual confounding factors including adequacy or frequency of dialysis and residual renal function, could not assessed. Second, assessment of inflammation, an important factor related to fatigue, was difficult, because of missing values and lower levels, including below the detectable level, of CRP. Third, selection bias, especially physicians’ preference, for choice of dialysis modalities was considerable, because this study was not a randomized, controlled study, but an observational study. Fourth, although the results of our original scale of fatigue were significantly associated with those of the POMS and VAS, convergent and discriminant validity, test-retest reliability, or social desirability could not be clarified using this study design. Fifth, the details of the screening process at each center were not known. Further selection bias may have been introduced by recruiting predominantly patients who were able to read and respond to the questionnaires themselves, thereby compromising the generalizability of the study. Sixth, since patients receiving combined therapy with PD and HD answered all self-reported questionnaires not on the HD session days but at regular outpatient visits, the impact of HD on the questionnaire scores was unclear, because the timing of assessment related to HD sessions differed among patients in this group. Seventh, sample size was small, which may be the reason for not detecting a statistically significant difference in fatigue levels across modalities.

Conclusions

The results indicated that the type of dialysis modality, including HD, online HDF, PD and combined therapy with PD and HD did not appear to be associated with the prevalence or severity of fatigue of patients on dialysis. In patients undergoing HD or online HDF, fatigue levels were significantly lower on dialysis-free days. Further research to explore the differences in pathophysiology of fatigue between dialysis modalities may be warranted.

Supporting information

S1 Data. Original data set.

(ZIP)

Click here for additional data file. (44.8KB, zip)

Acknowledgments

The authors gratefully acknowledge the support and participation of the patients in Shinagawa Kidney Clinic (Tokyo, Japan), Iidabashi Murai Clinic (Tokyo, Japan), Aoto Kidney Clinic (Tokyo, Japan), and Shin Kashiwa Clinic (Kashiwa, Chiba)

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

This study was supported in part by research grants M.N. has received from Baxter International, Inc. (number 16CECPDAP0002). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study.

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Decision Letter 0

Andrea K Viecelli

23 Jul 2020

PONE-D-20-17573

Comparisons of fatigue between dialysis modalities: A cross-sectional study

PLOS ONE

Dear Dr. Maruyama,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands and will need major revisions in order to be considered for publication. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

In particular, the aims of this study should be clarified (validation study versus assessment of fatigue accross different dialysis modality), the use of POMS instead of SF-36 needs further justification and more emphasis should be given to the difficulties (and limitations) of interpreting results when using different measures of fatigue as presented in this study. The discussion should focus more on the outcome of fatigue then interventions to improve fatigue. 

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Reviewer #1: Yes

Reviewer #2: Partly

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #1: I read with interest the manuscript “Comparisons of fatigue between dialysis modalities: A cross-sectional study” by Maruyama and colleagues. This study provides interesting findings on fatigue in different dialysis modalities, as assessed through three different fatigue evaluation scales (POMS, VAS and an original scale).

Nevertheless, I have a few comments and questions to ask the authors. For simplicity, I will comment by sections.

METHODS

Subjects

1. Could the authors comment on how the patients were screened for inclusion in the study? Were all patients in the included centers screened for inclusion? Was there a minimum duration of dialysis for inclusion (eg. established on dialysis for at least 3 months)?

2. The authors specify that “any patient that had a diagnosable mental health disorder or medical illness, including dementia and terminal cancer were excluded”. As patients with depression, CVD, diabetes, etc. are included in this study, it appears that the “diagnosable mental health disorder or medical illness” warranting exclusion from the study were more specific. The authors should further specify the exact exclusions and/or modify this statement in the manuscript.

Assessments of fatigue and depression

3. All used scales are very well described in the manuscript. However, no details are provided on how the responses to the self-reported questionnaires/scales were collected: were the patients completing the questionnaires in a written form by themselves or verbally answering to the questions to a member of staff? The authors should provide more details on the exact “self-reporting” procedure and if any exclusion from the study would have been related to these. For example, if the questionnaires were completed in a written format, were patients unable to write/read excluded or offered any help to complete the questionnaire?

Statistical analysis

4. Were the variables included in the multivariate analysis chosen on biological/clinical plausibility alone or was a univariate analysis done? As smoking was significantly different across groups, can the authors explain why it was not included in the multivariate analysis?

RESULTS

5. Following on question #1, the authors should provide some information on the included cohort compared to the dialysis population in the participating centers. How many patients were screened for inclusion; how many were excluded and for which reason, etc? This might also need to be mentioned in the limitations of the study depending on the representativity of this cohort compared to the dialysis population screened.

6. Can the authors comment on the predominantly male cohort: is this proportion representative of the dialysis population in Japan or is this related to higher consent to study by men or exclusion of more women due to exclusion criteria?

7. Could the authors provide a brief statement on modality choice in the participating centers (HD vs HDF vs PD vs combined HD/PD): patients’ choice, medical indication, ‘PD first’ policy, etc?

8. In the introduction, the authors mention that “It is unclear whether dialysis-related factors such as the type of dialysis modality and the adequacy or frequency of dialysis are associated with fatigue”. Were data on dialysis prescription (number of exchanges and volume of PD; treatment time and frequency on HD, etc) and on dialysis adequacy (Kt/v or URR) collected as part of this study? If so, these should be described and potentially included in the regression models. If these data were not collected, it should be mentioned in the limitation of the study as they could potentially be important confounders.

9. In the paragraph describing results included in Tables 2 and 3 (p.10-11), the same sentences appear twice. Table 2 describes the logistic regression model for highest score of fatigue (dichotomic outcome) and not the severity of fatigue. This should be corrected in the manuscript. In the second part of that paragraph (describing Table 3), the same sentence describing the association of employment status is used, mentioning the “lower risk of fatigue”. Here, it appears that this results should refer to a “lower severity/score of fatigue” (continuous outcome).

DISCUSSION

10. Could the authors comment on the median VAS and POMS values obtained in their study compared to previous studies?

For example, in a Malaysian study comparing quality of life in HD vs CAPD, mean VAS scores were around 76-77 vs. 48 in the present study.

[Surendra NK, Abdul Manaf MR, Hooi LS, et al. Health related quality of life of dialysis patients in Malaysia: Haemodialysis versus continuous ambulatory peritoneal dialysis. BMC Nephrol. 2019;20(1):151. Published 2019 Apr 30. doi:10.1186/s12882-019-1326-x]

In contrast, a Polish study evaluating defense mechanism in dialysis patients found the fatigue subscale of the POMS around 5-11 vs. 11.3 in the present study.

[Nowak Z, Wańkowicz Z, Laudanski K. Denial Defense Mechanism in Dialyzed Patients. Med Sci Monit. 2015;21:1798-1805. Published 2015 Jun 22. doi:10.12659/MSM.893331]

The generalizability of the results from the present study should be mentioned in the discussion in light of such differences or similarities.

FIGURE 1

11. In Figure 1, for the graph representing the results from the original scale, asterixis (*) are used but no legend for this is provided.

In conclusion, this manuscript presents very interesting findings on severity of fatigue in different dialysis modality, including the combined therapy of PD and HD, which is used much more frequently in Japan than elsewhere in the world. The cross-sectional, observational nature of the study, the potential for selection bias and residual confounding are limitations of this study, which have been clearly identified by the authors in the discussion.

Please note that the data underlying the findings is described as fully available within the manuscript and its Supporting Information files on the submission but no supporting files were attached to the manuscript for review so I cannot comment on the “full availability” of the data.

Reviewer #2: While fatigue is very important for patients on dialysis, I'm not sure that this study adds anything new to the existing body of literature on this topic. Furthermore, I have outlined some major methodological concerns below.

Aim - It is unclear whether the aim is to investigate the levels of fatigue across dialysis modalities or validate a new fatigue measure the authors have created

Introduction:

- Second last paragraph: QOL and fatigue are not interchangeable so this paragraph seems a bit random – either explain how fatigue impacts QOL and thus is the research question for this study, or explore literature around fatigue instead

- Last paragraph: why would comparing modalities expected to help identify which subjects will benefit from interventions to reduce fatigue?

Methods:

- I think the authors should justify why POMS was chosen for this study. If frequency of use was the basis, why wasn’t SF-36 used? POMS includes a subscale for fatigue but given that it is more of a symptom checklist-type measure with a focus on ‘moods’ than a symptom-specific questionnaire, it seems an odd choice of measure to which the authors’ measure is compared

- What was the sampling methodology?

- The readers would benefit from greater details about the ‘original measure’. How was it developed/through what process? Has the content validity been established? Is this the first time that it has been used in a study? Why/how were grades 3, 4 and 5 chosen as ‘fatigued states’? Is this measure described else where in the literature? If so, please add in the relevant citation

- Depression needs to be better integrated into the rationale of this study

Results:

- Given that POMS, VAS and the original scale were all used to explore fatigue, the rho seems quite low. explore this in the discussion

- POMS and VAS did not differ across four groups, but the original scale did – what does this tell us about the fatigue levels across these groups? Or what does this say about the validity of the original scale?

Discussion

- Discrepancy in results in existing literature regarding fatigue may also be due to the fact that measures of fatigue vary across these studies (as evident in this study where different measures yield different results)

- Discussion on the interventions for fatigue seems out of place – link the results of this study back to what the implications are for future research aiming to look at interventions for fatigue across different modalities

- 4th limitation is noted as the fact that ‘convergent and discriminant validity, test-retest reliability or social desirability could not be clarified using this study design’. This is a major flaw of this study, as using a measure that has not been adequately validated runs the risk of yielding not only inconclusive but also misleading results. I would advise that the authors rethink the true aim of this study

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2021 Feb 10;16(2):e0246890. doi: 10.1371/journal.pone.0246890.r002

Author response to Decision Letter 0

2 Sep 2020

Response to Reviewers

In particular, the aims of this study should be clarified (validation study versus assessment of fatigue across different dialysis modality), the use of POMS instead of SF-36 needs further justification and more emphasis should be given to the difficulties (and limitations) of interpreting results when using different measures of fatigue as presented in this study. The discussion should focus more on the outcome of fatigue then interventions to improve fatigue.

RESPONSE: Thank you for raising these very important points. We have clarified the aims of this study in the Introduction as follows: “The aim of this cross-sectional study was to compare the prevalence or severity of fatigue among patients receiving different dialysis modalities, including HD, online HDF, PD, and combined therapy with PD and HD.” As we mentioned in the Limitation, we could not validate the effectiveness of our original scale of fatigue using this study design. Since the last sentence of the Introduction of "Additionally, the effectiveness of our original, very simple scale of fatigue was verified" is inadequate, we have deleted this sentence. We did not use SF-36, especially its the vitality scale, despite the frequently use in this area [Ref. 2, Ref. 3] and used POMS instead for two reasons. First, it includes the fatigue scale. Second, it is widely used in clinical practice and covered by the public medical insurance system in Japan. The associations between the scores of POMS, VAS and our original scale of fatigue were significant but weak. Additionally, the effects of several confounding factors, such as age, BMI, employment status and serum creatinine, on the presence or severity of fatigue differed depending on the scales. These discrepancies indicate the fact that different measures could yield different results. We have added this information to the Discussion. As suggested, we have deleted the discussion on the interventions for fatigue because this information is not necessary. We modified the discussion focused more on the outcome of fatigue.

Please include your amended Funding Statement within your cover letter. We will change the online submission form on your behalf.

RESPONSE: As suggested, we amended Funding Statement within our cover letter.

Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf.

RESPONSE: As suggested, we updated Competing Interests statement in our cover letter.

Reviewer #1: I read with interest the manuscript “Comparisons of fatigue between dialysis modalities: A cross-sectional study” by Maruyama and colleagues. This study provides interesting findings on fatigue in different dialysis modalities, as assessed through three different fatigue evaluation scales (POMS, VAS and an original scale).

Nevertheless, I have a few comments and questions to ask the authors. For simplicity, I will comment by sections.

METHODS

Subjects

1. Could the authors comment on how the patients were screened for inclusion in the study? Were all patients in the included centers screened for inclusion? Was there a minimum duration of dialysis for inclusion (eg. established on dialysis for at least 3 months)?

RESPONSE: Thank you for raising this important point. As we described in the Materials and methods, we excluded patients under 18 years of age, in addition to patients with a mental disorder, such as schizophrenia, depression or dementia, and those with terminal cancer. We did not determine other inclusion or exclusion criteria and did not exclude patients with shorter duration of dialysis. Unfortunately, we are unaware of the detail of screening process at each center. We have added this information to the Limitation.

2. The authors specify that “any patient that had a diagnosable mental health disorder or medical illness, including dementia and terminal cancer were excluded”. As patients with depression, CVD, diabetes, etc. are included in this study, it appears that the “diagnosable mental health disorder or medical illness” warranting exclusion from the study were more specific. The authors should further specify the exact exclusions and/or modify this statement in the manuscript.

RESPONSE: Thank you for pointing out this error. As suggested, we did not exclude patients with history of CVD or diabetes. Therefore, the word of “medical illness” is inappropriate. We have corrected the description of exclusion criteria as follows: “Patients under 18 years of age, in addition to patients with a mental disorder, such as schizophrenia, depression or dementia, and those with terminal cancer were excluded.”

Assessments of fatigue and depression

3. All used scales are very well described in the manuscript. However, no details are provided on how the responses to the self-reported questionnaires/scales were collected: were the patients completing the questionnaires in a written form by themselves or verbally answering to the questions to a member of staff? The authors should provide more details on the exact “self-reporting” procedure and if any exclusion from the study would have been related to these. For example, if the questionnaires were completed in a written format, were patients unable to write/read excluded or offered any help to complete the questionnaire?

RESPONSE: Thank you for noticing this issue. We confirmed that all participants read and wrote questionnaires for themselves, although we did not excluded patients who need help to answer “written format” questionnaires. We noticed that there was a bias in recruiting participants for this study. We have added this information to the Materials and methods, the Results and the Limitation.

Statistical analysis

4. Were the variables included in the multivariate analysis chosen on biological/clinical plausibility alone or was a univariate analysis done? As smoking was significantly different across groups, can the authors explain why it was not included in the multivariate analysis?

RESPONSE: Thank you for raising this important point. On multivariate analysis, we selected several confounding factors reported to be associated with fatigue in dialyzed patients. However, there could be a possible confounding factor, including smoking status, as the reviewer suggested. Therefore, we changed the methods of variable selection. We also included confounding factor that had shown an appreciable association (P<0.1) with a measure of fatigue in multivariate analysis in order to avoid omissions error and created new Table 2 to 5. We have added this information to the Materials and methods and have modified the descriptions in the Results and Discussion, because the results of regression analysis were partially changed.

RESULTS

5. Following on question #1, the authors should provide some information on the included cohort compared to the dialysis population in the participating centers. How many patients were screened for inclusion; how many were excluded and for which reason, etc? This might also need to be mentioned in the limitations of the study depending on the representativity of this cohort compared to the dialysis population screened.

RESPONSE: Thank you for raising this important point. As described before, we are unaware of the detail of screening process at each center. Additionally, there could be a bias in recruiting participants for this study and representative sampling may not reflect the general dialysis population, because all participants read and wrote questionnaires for themselves although we did not excluded patients who need help to answer written format questionnaires. We have added this information to the Limitation.

6. Can the authors comment on the predominantly male cohort: is this proportion representative of the dialysis population in Japan or is this related to higher consent to study by men or exclusion of more women due to exclusion criteria?

RESPONSE: Thank you for this helpful comment. The percentage of male participants in this study was 69.1% and we think that it is similar to the general dialysis population in Japan. According to annual surveys of dialysis facilities throughout Japan in 2017, 65% of prevalent dialysis patients were male [Ref. 19].

7. Could the authors provide a brief statement on modality choice in the participating centers (HD vs HDF vs PD vs combined HD/PD): patients’ choice, medical indication, ‘PD first’ policy, etc?

RESPONSE: Thank you for this helpful comment. As we described in the Limitation, selection bias, especially physicians’ preference, for choice of dialysis modalities was considerable, because this study was not a randomized controlled study, but an observational study. PD First policy is recommended in order to maximize the advantages of PD therapy including excellent comparable survival, lower cost and improved quality of life also in Japan [Ref. 20, Ref. 21]. However, its long-term continuation is difficult because of a decline in residual renal function and deterioration of the peritoneal membrane. Patients who become unmanageable only by PD need to change the modality of RRT. Although they often directly transfer to HD, transfer to combined therapy with PD and HD, generally consists of 5-6 days of PD and commonly one HD session per week, was relatively common in Japan. PD therapy and combined therapy with PD and HD are thought to be performed especially among young and socially engaged patients. Indeed, the mean age of PD patients was 63.5 years, whereas the mean age of HD patients was 69.4 years [Ref. 19]. Additionally, the number of patients treated with online HDF have been increasing after the 2012 revision to the medical reimbursement system, and have reached 70000, approximately 30% of all dialysis patients at the end of 2017 in Japan. Since the mean age of HDF patients was 66.6 years and approximately 3 years younger than HD patients, this therapy is also thought to be performed especially among young and socially engaged patients [Ref. 19]. Therefore, we think that the prevalence or the severity of fatigue should be investigated not only among patients on PD and HD but those on online HDF and combined therapy with PD and HD. We have added this information to the Introduction and the Discussion.

8. In the introduction, the authors mention that “It is unclear whether dialysis-related factors such as the type of dialysis modality and the adequacy or frequency of dialysis are associated with fatigue”. Were data on dialysis prescription (number of exchanges and volume of PD; treatment time and frequency on HD, etc) and on dialysis adequacy (Kt/v or URR) collected as part of this study? If so, these should be described and potentially included in the regression models. If these data were not collected, it should be mentioned in the limitation of the study as they could potentially be important confounders.

RESPONSE: Thank you for noticing this issue. As the reviewer indicated, we did not have the data of neither adequacy nor frequency of dialysis. We have deleted these descriptions from the Introduction. Furthermore, we have added following sentences to the Limitations: “The effect of residual confounding factors including adequacy or frequency of dialysis and residual renal function, was unavoidable.”

9. In the paragraph describing results included in Tables 2 and 3 (p.10-11), the same sentences appear twice. Table 2 describes the logistic regression model for highest score of fatigue (dichotomic outcome) and not the severity of fatigue. This should be corrected in the manuscript. In the second part of that paragraph (describing Table 3), the same sentence describing the association of employment status is used, mentioning the “lower risk of fatigue”. Here, it appears that this results should refer to a “lower severity/score of fatigue” (continuous outcome).

RESPONSE: Thank you for this helpful comment. As suggested, we have modified the description of the Results. In the results of logistic regression analysis, we changed the description of outcome from the severity of fatigue to the presence of fatigue, because objective variables were not continuous but dichotomic variables. In addition, we changed the description of outcome from the risk of fatigue to the severity of fatigue in multiple regression analysis.

DISCUSSION

10. Could the authors comment on the median VAS and POMS values obtained in their study compared to previous studies?

For example, in a Malaysian study comparing quality of life in HD vs CAPD, mean VAS scores were around 76-77 vs. 48 in the present study.

[Surendra NK, Abdul Manaf MR, Hooi LS, et al. Health related quality of life of dialysis patients in Malaysia: Haemodialysis versus continuous ambulatory peritoneal dialysis. BMC Nephrol. 2019;20(1):151. Published 2019 Apr 30. doi:10.1186/s12882-019-1326-x]

In contrast, a Polish study evaluating defense mechanism in dialysis patients found the fatigue subscale of the POMS around 5-11 vs. 11.3 in the present study.

[Nowak Z, Wańkowicz Z, Laudanski K. Denial Defense Mechanism in Dialyzed Patients. Med Sci Monit. 2015;21:1798-1805. Published 2015 Jun 22. doi:10.12659/MSM.893331]

The generalizability of the results from the present study should be mentioned in the discussion in light of such differences or similarities.

RESPONSE: Thank you for this helpful comment. The scales of fatigue might differ from several sociodemographic factors such as age, gender and race. Unfortunately, we could not find the report comparing the scores of these scales between different populations. The VAS was graduated from 0 (worst imaginable health state) to 100 (best imaginable health state) in the Malaysian study the reviewer introduced, whereas it was graduated from 0 (no tiredness at all) to 100 (complete exhaustion) in our study. As indicated, the fatigue subscale of the POMS scores in the Polish study including 115 dialysis patients the reviewer introduced were lower than those of our study [Ref. 27]. On the contrary, these scores at baseline of randomized controlled trial including 15 HD patients in U.S. were approximately similar to the present study [Ref. 28]. We have added this information to the Discussion.

FIGURE 1

11. In Figure 1, for the graph representing the results from the original scale, asterixis (*) are used but no legend for this is provided.

RESPONSE: As suggested, we have added the explanation of asterixis to the Figure Legend.

In conclusion, this manuscript presents very interesting findings on severity of fatigue in different dialysis modality, including the combined therapy of PD and HD, which is used much more frequently in Japan than elsewhere in the world. The cross-sectional, observational nature of the study, the potential for selection bias and residual confounding are limitations of this study, which have been clearly identified by the authors in the discussion.

RESPONSE: Thank you for the favorable review you gave our manuscript.

Please note that the data underlying the findings is described as fully available within the manuscript and its Supporting Information files on the submission but no supporting files were attached to the manuscript for review so I cannot comment on the “full availability” of the data.

RESPONSE: As suggested, we attached data set we used to the revised manuscript.

Reviewer #2: While fatigue is very important for patients on dialysis, I'm not sure that this study adds anything new to the existing body of literature on this topic. Furthermore, I have outlined some major methodological concerns below.

RESPONSE: Thank you for the review you gave our manuscript. We wholly revised our manuscript according a number of helpful comments. As described before, the aim of this cross-sectional study was to compare the prevalence or severity of fatigue among patients receiving different dialysis modalities, including HD, online HDF, PD, and combined therapy with PD and HD. The main result was the prevalence and the severity of fatigue was not significantly different among patients receiving different dialysis modalities. The present study is the first study examined fatigue condition among patients receiving online HDF or combined therapy with PD and HD. We have added this information to the Introduction and Discussion.

Aim - It is unclear whether the aim is to investigate the levels of fatigue across dialysis modalities or validate a new fatigue measure the authors have created

RESPONSE: Thank you for raising this important point. We have clarified the aims of this study in the Introduction as follows: “The aim of this cross-sectional study was to compare the prevalence or severity of fatigue among patients receiving different dialysis modalities, including HD, online HDF, PD, and combined therapy with PD and HD.” As we mentioned in the Limitation, we could not validate the effectiveness of our original scale of fatigue using this study design. Since the description of "Additionally, the effectiveness of our original, very simple scale of fatigue was verified" is inadequate, we have deleted this sentence.

Introduction:

- Second last paragraph: QOL and fatigue are not interchangeable so this paragraph seems a bit random – either explain how fatigue impacts QOL and thus is the research question for this study, or explore literature around fatigue instead

RESPONSE: Thank you for raising this important point. We completely agree with the point that QOL and fatigue are not compatible. As suggested, we have deleted the description regarding the comparisons of QOL between different dialysis modalities. Instead, we focused on the clinical condition of fatigue.

- Last paragraph: why would comparing modalities expected to help identify which subjects will benefit from interventions to reduce fatigue?

RESPONSE: Thank you for this helpful comment. As suggested, we could not identify the subjects having benefit of interventions to reduce fatigue from this study design. We have deleted this sentence.

Methods:

- I think the authors should justify why POMS was chosen for this study. If frequency of use was the basis, why wasn’t SF-36 used? POMS includes a subscale for fatigue but given that it is more of a symptom checklist-type measure with a focus on ‘moods’ than a symptom-specific questionnaire, it seems an odd choice of measure to which the authors’ measure is compared

RESPONSE: Thank you for raising this important point. As mentioned before, we did not use SF-36, especially its the vitality scale, despite the frequently use in this area [Ref. 2, Ref. 3] and used POMS instead for two reasons. First, it includes the fatigue scale. Second, it is widely used in clinical practice and covered by the public medical insurance system in Japan. We have added this information to the Discussion.

- What was the sampling methodology?

RESPONSE: Thank you for this helpful comment. As mentioned before, we decided exclusion criteria, however we are unaware of the detail of screening process at each center. We have added following sentences to the Limitations: “We are unaware of the detail of screening process at each center. Additionally, there could be a bias in recruiting participants for this study and representative sampling may not reflect the general dialysis population, because all participants read and wrote questionnaires for themselves although we did not excluded patients who need help to answer written format questionnaires.”

- The readers would benefit from greater details about the ‘original measure’. How was it developed/through what process? Has the content validity been established? Is this the first time that it has been used in a study? Why/how were grades 3, 4 and 5 chosen as ‘fatigued states’? Is this measure described else where in the literature? If so, please add in the relevant citation

RESPONSE: Thank you for raising this important point. As we mentioned in the Materials and methods, we developed our original scale of fatigue and have already used in the previous two studies (Ref.14 and Ref. 15). However, only this scale was used for the assessment of fatigue in these two studies. It is first time to compare the findings of this scale with those of well-established scales and we found that the scores of the POMS, VAS, and our original scale of fatigue were significantly inter-related. However, convergent and discriminant validity, test-retest reliability, or social desirability could not be clarified using this study design as we mentioned in the Limitation. As described in the Materials and methods, our original scale of fatigue is a five-grade evaluation including Grade 1 (inexhaustible, feels well, and extremely active), Grade 2 (tireless, acts in the ordinary way without a sense of fatigue), Grade 3 (mild fatigue, acts in the ordinary way but feels tired), Grade 4 (moderate fatigue, feels tired with light work), and Grade 5 (intense fatigue, very tired, and falls asleep). Therefore, we defined Grades 3 to 5 as fatigued state because the examinee realizes the presence of mild, moderate or intense fatigue.

- Depression needs to be better integrated into the rationale of this study

RESPONSE: Thank you for this helpful comment. As we mentioned in the manuscript, it is well-known that depression, the most important psychological factor, is strongly associated with fatigue and they are closely interrelated. Although exclusion criteria included the patients with depression, we could not exclude the effects of depressive status on the prevalence or severity of fatigue. Therefore, we assessed the presence and severity of depressive symptoms using the BDI–II and conducted sensitivity analyses including only patients with lower score of BDI-II. Since the results of these sensitivity analysis were similar to the results including all subjects, depressive state was thought to have a low impact on the prevalence or severity of fatigue in our study. We have added this information to the Results and Discussion.

Results:

- Given that POMS, VAS and the original scale were all used to explore fatigue, the rho seems quite low. explore this in the discussion

RESPONSE: Thank you for this helpful comment. As suggested, the associations between the scores of POMS, VAS and our original scale of fatigue were significant but weak. Additionally, the effects of several confounding factors, such as age, BMI, employment status and serum creatinine, on the presence or severity of fatigue differed depending on the scales. These discrepancies indicate the fact that different measures could yield different results. We have added this information to the Discussion.

- POMS and VAS did not differ across four groups, but the original scale did – what does this tell us about the fatigue levels across these groups? Or what does this say about the validity of the original scale?

RESPONSE: Thank you for this helpful comment. Although only the score of our original scale of fatigue was significantly different among patients on different dialysis modalities in univariate analysis, this finding disappeared in multivariate analysis. Therefore, we considered that the severity of fatigue assessed by our original scale of fatigue were not different. As mentioned before, we could not validate the effectiveness of our original scale of fatigue using this study design.

Discussion

- Discrepancy in results in existing literature regarding fatigue may also be due to the fact that measures of fatigue vary across these studies (as evident in this study where different measures yield different results)

RESPONSE: Thank you for this helpful comment. As suggested, the effects of several confounding factors, such as age, BMI, employment status and serum creatinine, on the presence or severity of fatigue differed depending on the scales. Additionally, the associations between the scores of POMS, VAS and our original scale of fatigue were significant but weak. These discrepancies indicate the fact that different measures could yield different results. We have added this information to the Discussion.

- Discussion on the interventions for fatigue seems out of place – link the results of this study back to what the implications are for future research aiming to look at interventions for fatigue across different modalities

RESPONSE: Thank you for this helpful comment. We completely agree with the opinion that discussion on the interventions for fatigue was not necessary. As the Editor also pointed, we deleted the description of this discussion and focused more on the outcome of fatigue.

- 4th limitation is noted as the fact that ‘convergent and discriminant validity, test-retest reliability or social desirability could not be clarified using this study design’. This is a major flaw of this study, as using a measure that has not been adequately validated runs the risk of yielding not only inconclusive but also misleading results. I would advise that the authors rethink the true aim of this study

RESPONSE: Thank you for raising this important point. As mentioned before, the aim of our study was to compare the prevalence or severity of fatigue among patients receiving different dialysis modalities, including HD, online HDF, PD, and combined therapy with PD and HD. We could not validate the effectiveness of our original scale of fatigue using this study design. We have clarified the aims of this study in the Introduction. In this study, we employed our original scale of fatigue as a complementary test for direct patient-reported outcome, because it is easy to use, and its simplicity free usage. We used this test both dialysis and dialysis-free day and found that there were significant differences. The result may indicate the different diurnal and weekly profiles of fatigue between HD and PD, despite the equivalent levels of fatigue on dialysis day in PD and HD. We added this point in the revised manuscript, and we think this needs to be clarified in future study by using POMS, VAS and SF-36.

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Decision Letter 1

Andrea K Viecelli

22 Oct 2020

PONE-D-20-17573R1

Comparisons of fatigue between dialysis modalities: A cross-sectional study

PLOS ONE

Dear Dr. Maruyama,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The authors have addressed previous comments. However, the manuscript needs significant editing to comply with standard English. There are too many typographical or grammatical errors to list here. The manuscript is not publishable in the current state and will require major editing and revisions. The original data set referred to under “supporting information” was not available to the editor or reviewer and will need to be accessible in order to comply with publication criteria. In addition to the reviewer’s comment, there are additional issues identified that require clarification:

Abstract:

Please avoid vague statements in the abstract like “The scores of the POMS, VAS, and our original scale of fatigue were weakly but significantly inter-related”. The actual results would be more helpful.  

“In the fatigue scales of on dialysis day by 3 tests, there were no statistical differences by modalities.” The meaning of this sentence is unclear. Please clarify and revise.

“The similar result was obtained in 122 patients without depression.” “The” should be removed.

The conclusion of the abstract and manuscript is unclear and needs rephrasing. What do the authors mean with “The results indicated the least impact of dialysis modalities on fatigue in dialysis patients including HD, online HDF, PD and combined therapy with PD and HD.”?

Methods: “All participants read and wrote questionnaires for themselves”. Participants presumably did not write the questionnaires but responded to the questions without assistance.

The references need reformatting.

Please submit your revised manuscript by Dec 06 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Andrea K. Viecelli

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I read with interest this new version of the manuscript “Comparisons of fatigue between dialysis modalities: A cross-sectional study” by Maruyama and colleagues.

The questions and concerns raised in the first review process have been answered and addressed. However, I have a few additional comments about this new version.

1) The main aim of this study was to evaluate fatigue across different dialysis modalities. When adjusted for patient characteristics, no association was found between occurrence and severity of fatigue and dialysis modality. The authors should review the conclusions section in the abstract and the main article as the current wording is hard to understand and does not clearly describe the findings.

2) In the second paragraph of the Introduction, the authors refer to “patients on” HD and PD and the different hypotheses for the mechanisms of fatigue of each modality. The causes described seem to refer to the modality themselves, and not the patients.

3) At the end of the Introduction section, the aim is described as the comparison of prevalence OR severity. This should be modified to “and” as the authors evaluated both the prevalence and the severity with 2 different regression models.

4) The last sentence of the introduction is misleading as the authors state that the findings could “indicate the different pathophysiology of fatigue by dialysis modalities”. Although the findings might raise new questions and hypotheses on the pathophysiology of fatigue across modalities (with the differences seen between on and off dialysis days in HD and HDF), this study is not designed to evaluate the pathophysiology of fatigue.

5) The authors indicate that their original fatigue scale has been previously used in other studies, but they do not indicate if it has been validated as an accurate scale. The authors could specify in the Methods section why they have also used their original scale (easy to use? readily available?) if the aim of the study was not to validate this new scale.

6) The authors have indicated in this new version of the manuscript that their original scale was used on both on- and off-dialysis days in HD and HDF, with differences in the scores obtained. However, the authors do not mention if the scale was also used on different days in the combination therapy (HD+PD) group. Since the study aimed to compare the modalities and seemed to raise differences in fatigue depending on the timing of dialysis session, it would have been relevant to test whether fatigue also varied depending on timing in the combination therapy group, in which patients are treated alternatively with PD and HD. As timing of assessment of fatigue is not mentioned in this group, it brings some doubts about the reliability of the findings in this group if the timing related to HD sessions was not the same for all patients (for example: a patient assessed on HD day vs. a patient assessed after 3 PD days and due for HD 3 days later). If timing of assessment was different across the groups, this should be mentioned in the discussion.

In conclusion, this study reports interesting findings on fatigue in dialysis. The use of the original scale is interesting, but needs validation. The aim of the study was to compare fatigue across modalities. The findings related to the original scale are therefore hard to interpret as this scale has not been formally validated/compared to other scales.

The differences seen between on- and off-dialysis days also raise hypotheses on differences in the pathophysiology of fatigue across dialysis modalities. The inclusion of patients on combination therapy in this study is interesting (as this modality is mostly used in Japan). However, the methodology described did not permit to fully evaluate the differences across modalities without major confounding (including the timing of assessment in that group). Perhaps this would warrant further research in this group of patients who alternate between HD and PD.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 Feb 10;16(2):e0246890. doi: 10.1371/journal.pone.0246890.r004

Author response to Decision Letter 1

1 Dec 2020

Response to Reviewers

The authors have addressed previous comments. However, the manuscript needs significant editing to comply with standard English. There are too many typographical or grammatical errors to list here. The manuscript is not publishable in the current state and will require major editing and revisions. The original data set referred to under “supporting information” was not available to the editor or reviewer and will need to be accessible in order to comply with publication criteria. In addition to the reviewer’s comment, there are additional issues identified that require clarification:

RESPONSE: Thank you for revising our manuscript. The comments were very helpful. We have worked through each of the comments to address the issues raised, and a native English speaking editor has checked our revised manuscript. We have attached "S1 Table Original data set" as Supporting Information. We can release the data set used during the current study if requested.

Abstract:

Please avoid vague statements in the abstract like “The scores of the POMS, VAS, and our original scale of fatigue were weakly but significantly inter-related”. The actual results would be more helpful.

RESPONSE: As suggested, we have added the actual results as follows: "(rho =0.58, P<0.01; rho=0.47, P<0.01, and rho=0.42, P<0.01 between POMS and VAS, POMS and our original scale for fatigue, and VAS and our original scale for fatigue, respectively)."

“In the fatigue scales of on dialysis day by 3 tests, there were no statistical differences by modalities.” The meaning of this sentence is unclear. Please clarify and revise.

RESPONSE: Thank you for this helpful comment. In the Methods, we clarified that we measured our original scale of fatigue both on dialysis and dialysis-free day among patients on HD and online HDF. Additionally, we revised this sentence as follows: “The scores of these 3 tests showed no significant differences among the 4 modalities.”.

“The similar result was obtained in 122 patients without depression.” “The” should be removed.

RESPONSE: As suggested, we removed “The” from this sentence.

The conclusion of the abstract and manuscript is unclear and needs rephrasing. What do the authors mean with “The results indicated the least impact of dialysis modalities on fatigue in dialysis patients including HD, online HDF, PD and combined therapy with PD and HD.”?

RESPONSE: Thank you for this helpful comment. As suggested, we clarified and revised this sentence as follows: “The results showed that the types of dialysis modality had no significant effect on fatigue”.

Methods: “All participants read and wrote questionnaires for themselves”. Participants presumably did not write the questionnaires but responded to the questions without assistance.

RESPONSE: As suggested, we revised the word from “wrote” to “responded”.

The references need reformatting.

RESPONSE: As suggested, we have reformat the references using Endnote.

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I read with interest this new version of the manuscript “Comparisons of fatigue between dialysis modalities: A cross-sectional study” by Maruyama and colleagues.

The questions and concerns raised in the first review process have been answered and addressed. However, I have a few additional comments about this new version.

RESPONSE: Thank you for revising our manuscript. The comments were very helpful.

1) The main aim of this study was to evaluate fatigue across different dialysis modalities. When adjusted for patient characteristics, no association was found between occurrence and severity of fatigue and dialysis modality. The authors should review the conclusions section in the abstract and the main article as the current wording is hard to understand and does not clearly describe the findings.

RESPONSE: Thank you for this helpful comment. As editor had also suggested, we clarified and revised this sentence as follows: “The results showed that the types of dialysis modality had no significant effect on fatigue”.

2) In the second paragraph of the Introduction, the authors refer to “patients on” HD and PD and the different hypotheses for the mechanisms of fatigue of each modality. The causes described seem to refer to the modality themselves, and not the patients.

RESPONSE: We completely agree with this comment. We revised the word from “patient on HD (or PD) could induce fatigue” to “HD (or PD) per se could induce fatigue”.

3) At the end of the Introduction section, the aim is described as the comparison of prevalence OR severity. This should be modified to “and” as the authors evaluated both the prevalence and the severity with 2 different regression models.

RESPONSE: As suggested, we revised the word from “OR” to “AND”.

4) The last sentence of the introduction is misleading as the authors state that the findings could “indicate the different pathophysiology of fatigue by dialysis modalities”. Although the findings might raise new questions and hypotheses on the pathophysiology of fatigue across modalities (with the differences seen between on and off dialysis days in HD and HDF), this study is not designed to evaluate the pathophysiology of fatigue.

RESPONSE: We completely agree with this comment that we could not clarify the pathophysiology of fatigue using this study design. We have deleted this sentence.

5) The authors indicate that their original fatigue scale has been previously used in other studies, but they do not indicate if it has been validated as an accurate scale. The authors could specify in the Methods section why they have also used their original scale (easy to use? readily available?) if the aim of the study was not to validate this new scale.

RESPONSE: Thank you for raising this important point. Although our original scale of fatigue has been previously used in other studies, we could not validate the effectiveness of this scale using this study design, as we described in the Limitation. The reasons why we used this scale were usability and a lower cost than other scales. As suggested, we have added following sentences to the Materials and methods section: “Although the effectiveness of this scale has not yet been validated, we used this scale because of its usability and lower cost than other scales”.

6) The authors have indicated in this new version of the manuscript that their original scale was used on both on- and off-dialysis days in HD and HDF, with differences in the scores obtained. However, the authors do not mention if the scale was also used on different days in the combination therapy (HD+PD) group. Since the study aimed to compare the modalities and seemed to raise differences in fatigue depending on the timing of dialysis session, it would have been relevant to test whether fatigue also varied depending on timing in the combination therapy group, in which patients are treated alternatively with PD and HD. As timing of assessment of fatigue is not mentioned in this group, it brings some doubts about the reliability of the findings in this group if the timing related to HD sessions was not the same for all patients (for example: a patient assessed on HD day vs. a patient assessed after 3 PD days and due for HD 3 days later). If timing of assessment was different across the groups, this should be mentioned in the discussion.

RESPONSE: Thank you for pointing out a serious flaw. As we described in the Materials and methods section, patients receiving combined therapy with PD and HD answered all self-reported questionnaires not at day of HD session but at regular outpatient visits. Therefore, as the reviewer concerned, impact of HD on the score of questionnaires was unclear, because timing of assessment related to HD sessions differed among patients in this group. We have added following sentences to the Limitation: “Since patients receiving combined therapy with PD and HD answered all self-reported questionnaires not on the HD session days but at regular outpatient visits, the impact of HD on the questionnaire scores was unclear, because the timing of assessment related to HD sessions differed among patients in this group.”

In conclusion, this study reports interesting findings on fatigue in dialysis. The use of the original scale is interesting, but needs validation. The aim of the study was to compare fatigue across modalities. The findings related to the original scale are therefore hard to interpret as this scale has not been formally validated/compared to other scales.

RESPONSE: We completely agree with this comment. Most serious limitation of this study was the lack of validity of our original scale. However, association between the prevalence and severity of fatigue and dialysis modalities were similar among three different scale of fatigue, including our original scale. Further studies will be needed to clarify not only the difference of fatigue by dialysis modalities, but also validity of the effectiveness of our original scale.

The differences seen between on- and off-dialysis days also raise hypotheses on differences in the pathophysiology of fatigue across dialysis modalities. The inclusion of patients on combination therapy in this study is interesting (as this modality is mostly used in Japan). However, the methodology described did not permit to fully evaluate the differences across modalities without major confounding (including the timing of assessment in that group). Perhaps this would warrant further research in this group of patients who alternate between HD and PD.

RESPONSE: Thank you for this helpful comment. As we described before, patients receiving combined therapy with PD and HD answered all self-reported questionnaires not at day of HD session but at regular outpatient visits. Therefore, impact of HD on the score of questionnaires was unclear, because timing of assessment related to HD sessions differed among patients in this group. We have added this information to the Limitation. As the reviewer pointed, further research investigating the effects of PD and those of HD on fatigue among patients receiving combined therapy is warranted.

Decision Letter 2

Andrea K Viecelli

13 Jan 2021

PONE-D-20-17573R2

Comparisons of fatigue between dialysis modalities: A cross-sectional study

PLOS ONE

Dear Dr. Maruyama,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

The suggested minor revisions are included in the edited tracked version attached and relate predominantly to the conclusion of the abstract and the manuscript. Further minor edits and grammatical corrections have been made throughout the manuscripts.

==============================

Please submit your revised manuscript by Feb 27 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Andrea K. Viecelli

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachment

Submitted filename: Revised Manuscript with Track Changes PONE 20201201_Revised.docx

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PLoS One. 2021 Feb 10;16(2):e0246890. doi: 10.1371/journal.pone.0246890.r006

Author response to Decision Letter 2

14 Jan 2021

The suggested minor revisions are included in the edited tracked version attached and relate predominantly to the conclusion of the abstract and the manuscript. Further minor edits and grammatical corrections have been made throughout the manuscripts.

RESPONSE: Thank you for revising our manuscript. As suggested, we demonstrated data on age, gender and the proportion of diabetes only in the Result section. We revised the word from “native dialysis modality” to “preferred dialysis modality” in the third paragraph of the Discussion section. Additionally, we agree with the rephrased sentence in the last of this paragraph. We reformatted the list of references.

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Submitted filename: Response to Reviewers PONE D 20 17573 20210114.docx

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Decision Letter 3

Andrea K Viecelli

21 Jan 2021

PONE-D-20-17573R3

Comparisons of fatigue between dialysis modalities: A cross-sectional study

PLOS ONE

Dear Dr. Maruyama,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Suggested revisions have been attached (Edited revision 3) to ensure the conclusions are supported by the data (please note the current version implies a causal relationship rather than an association). Comments have been added in the manuscript version attached to outline further minor revisions including the limitation of the small sample size and improvement of the first paragraph in the discussion to reflect a concise summary of the findings. Without these amendments, the manuscript does not fulfil the publication standards. The editor encourages the authors to address the suggested edits and revisions.

Please submit your revised manuscript by Mar 07 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

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Andrea K. Viecelli

Academic Editor

PLOS ONE

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Submitted filename: Revised Manuscript with Track Changes PONE 20201201_RevisedV2.docx

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PLoS One. 2021 Feb 10;16(2):e0246890. doi: 10.1371/journal.pone.0246890.r008

Author response to Decision Letter 3

26 Jan 2021

Response to Reviewers

Suggested revisions have been attached (Edited revision 3) to ensure the conclusions are supported by the data (please note the current version implies a causal relationship rather than an association). Comments have been added in the manuscript version attached to outline further minor revisions including the limitation of the small sample size and improvement of the first paragraph in the discussion to reflect a concise summary of the findings. Without these amendments, the manuscript does not fulfil the publication standards. The editor encourages the authors to address the suggested edits and revisions.

RESPONSE: Thank you for revising our manuscript. As suggested, we amended our manuscript. First, we modified conclusion both of abstract and text to avoid any mention of causal relationship. Second, we modified the first paragraph of the Discussion. Third, we added limitation regarding the small sample size. Additionally, we approved all modifications.

Attachment

Submitted filename: Response to Reviewers PONE D 20 17573 20210126.docx

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Decision Letter 4

Andrea K Viecelli

28 Jan 2021

Comparisons of fatigue between dialysis modalities: A cross-sectional study

PONE-D-20-17573R4

Dear Dr. Maruyama,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Andrea K. Viecelli

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Andrea K Viecelli

1 Feb 2021

PONE-D-20-17573R4

Comparisons of fatigue between dialysis modalities: A cross-sectional study

Dear Dr. Maruyama:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Andrea K. Viecelli

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Data. Original data set.

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    Attachment

    Submitted filename: Response to Reviewers PONE D 20 17573.docx

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    Attachment

    Submitted filename: Revised Manuscript with Track Changes PONE 20201201_Revised.docx

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    Attachment

    Submitted filename: Response to Reviewers PONE D 20 17573 20210114.docx

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    Attachment

    Submitted filename: Revised Manuscript with Track Changes PONE 20201201_RevisedV2.docx

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    Attachment

    Submitted filename: Response to Reviewers PONE D 20 17573 20210126.docx

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    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.

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