Determinants of sleep quality and fatigue in patients undergoing hemodialysis

Abstract

Aim:

This research aimed to evaluate sleep quality and fatigue among individuals undergoing hemodialysis and to explore the determinants affecting these variables.

Methods:

This observational investigation was carried out among 78 who were regularly receiving hemodialysis therapy. The research was carried out between May and October 2025 in three different public hospitals among individuals undergoing hemodialysis treatment. Data were gathered using the Patient Information Form (PIF), the Fatigue Severity Scale (FSS), and the Pittsburgh Sleep Quality Index (PSQI).

Results:

The mean score of the hemodialysis patients on the FSS is 4.97 ± 1.11, and the mean PSQI value is 7.76 ± 3.64. A moderately positive and statistically noteworthy relation was observed between the PSQI and FSS scores. Additionally, a low negative meaningful correlation was seen between ferritin levels and the FSS scores, as well as between calcium levels and the PSQI scores. The use of medications related to chronic disease and the PSQI scores were identified as significant predictors of the FSS scores.

Conclusion:

Fatigue and sleep quality in individuals receiving hemodialysis treatment are related to each other, as well as to biochemical balance and treatment adherence.

Keywords

Chronic kidney failure hemodialysis sleep fatigue quality of life

Introduction

The commonness of poor sleep quality among dialysis patients has been reported to be considerably high, ranging from 11% to 97.5%. Low sleep quality has been shown to correlate not only with adverse physiological indicators, but also with depression, smoking, and stimulating behaviors.¹ In another study,² variables such as female gender, the type of primary renal disease, elevated systolic blood pressure, the presence and severity of pruritus, depression, restless leg syndrome and anxiety were shown to be connected with poor sleep quality. These conclusions imply that impairments in sleep quality may be linked to the presence of kidney failure and may be improved through appropriate interventions. Hence, describing and targeting risk factors connected with sleep quality in dialysis patients may represent a critical step in enhancing overall quality of life.

Another frequently encountered symptom that negatively impacts the lives of hemodialysis patients is fatigue. This is a multidimensional phenomenon that encompasses physical, emotional and psychological parts.³ In addition to chronic fatigue, two specific fatigue patterns associated with the dialysis process have been identified in this patient group: (1) intradialytic fatigue (IDF), which begins before dialysis and persists throughout the treatment session,⁴ and (2) post-dialysis fatigue (PDF), which emerges after the session and may last for several hours.⁵ Indeed, fatigue has been identified as the most commonly reported symptom in 72% of patients undergoing hemodialysis treatment.⁶

Although sleep disturbance and fatigue may appear to be independent conditions, they are thought to be interrelated through two primary mechanisms. The first involves sleep disturbances leading to excessive daytime sleepiness, and the second pertains to the biological mechanisms associated with various sleep disorders. Excessive daytime sleepiness, insomnia, sleep apnea and restless leg syndrome are commonly observed in patients undergoing hemodialysis.⁷ Impairments in sleep initiation, adequacy and maintenance have been significantly connected with lower levels of vitality in patients.^8,9 Furthermore, in a large-scale study involving 894 dialysis patients, symptoms of restless leg syndrome were found to be associated notably with poorer physical and mental health, reduced vitality, increased bodily pain, and poor sleep quality.¹⁰ This study aims to examine the contributors to sleep quality and fatigue levels in patients undergoing chronic hemodialysis, who frequently experience multiple interrelated symptoms during the treatment process. In doing so, it is intended to contribute to the systematic evaluation of these symptoms in clinical follow-up and to support the development of strategies aimed at improving patients’ quality of life. Accordingly, the study seeks to answer the subsequent fundamental question: “Which factors influence sleep quality and fatigue levels in hemodialysis patients?”

Methods

Study design

The main goal of this cross-sectional research is to focus on the factors linked to sleep quality and fatigue levels in patients undergoing hemodialysis, and to contribute to improving patient well-being by emphasizing the importance of monitoring these symptoms within clinical follow-up procedures.

Sample and setting

The population of this investigation comprised patients undergoing hemodialysis at Bitlis State Hospital, Tatvan State Hospital, and Kelkit State Hospital. Conducted between May and October 2025, the study included all individuals who consistently participated in scheduled hemodialysis sessions at the aforementioned hospitals during this timeframe.

The sample consisted of individuals from the aforementioned population who were 18 years of age or older, literate, had been receiving hemodialysis treatment continuously for at least 3 months, and voluntarily agreed to participate in the study. Individuals who were not literate in Turkish, who had additional medical conditions that could influence symptoms of fatigue or weakness (e.g. heart failure, liver failure, malignancy, active infection, or malnutrition), or those who declined participation were excluded from the study. In line with these criteria, the aim was to reach all eligible individuals, and the research was completed with a total of 78 hemodialysis patients.

Data collection forms

Researchers personally administered the PIF, FSS, and the PSQI to collect the study data. The duration of data collection per participant averaged between 5 and 10 min.

PIF: Drawing from relevant literature, the researchers created this form, which includes 18 questions pertaining to the sociodemographic profiles and medical backgrounds of the participants.¹¹

FSS: The scale was first introduced by Krupp et al.,¹² and the adaptation of the scale into Turkish, along with its validity and reliability testing, was carried out by Armutlu et al. The scale consists of nine items arranged in a 7-point Likert format, yielding a total score ranging from 9 to 63, with higher scores reflecting more severe fatigue levels. The internal reliability of the instrument was confirmed with a Cronbach’s alpha of 0.94,¹³ reflecting excellent consistency among the items.

PSQI: The approach quantifies sleep quality within the previous month through 19 items distributed across seven sections: self-reported sleep quality, time to sleep onset, overall sleep duration, sleep efficiency, sleep-related disturbances, utilization of sleep-inducing medication, and impairment in daytime functioning. The scale demonstrated a Cronbach’s alpha reliability coefficient of 0.77, and its Turkish adaptation, including validity and reliability testing, was performed by Buysse et al.¹⁴ and Agargun.¹⁵ Higher scores on the scale indicate poorer sleep quality.¹⁵

Ethical considerations

The study received ethical approval from the Bitlis Eren University Ethics Committee for Non-Interventional Clinical Research (dated 16.04.2025, reference no: E.7177). Furthermore, institutional authorization was obtained from the hospitals in which the research was implemented (E-39320161-770-273727912; E-60037490-044-285270227). Received a full explanation of the goals and significance of the study, and the voluntary nature of their involvement was emphasized. Individuals who consented to participate were included after signing informed consent forms, and the research procedures were carried out in compliance with the ethical guidelines of the Declaration of Helsinki.

Statistical analysis

Statistical analyses were performed using IBM SPSS v27. Continuous variables were expressed as minimum–maximum and mean ± standard deviation, and categorical variables as frequencies and percentages. Statistical significance was set at p < 0.05. Skewness values within ±1 indicated normal distribution¹⁶; therefore, parametric tests were used for scale scores. Pearson correlation was applied for normally distributed laboratory variables, and Spearman correlation for non-normally distributed variables. Multiple linear regression was conducted to determine the extent to which predictor variables explained variance in the dependent scale scores.

Results

The demographic and clinical attributes of the study’s hemodialysis cohort are summarized carefully in Table 1.

Table 1.

Demographic and clinical characteristics of patients undergoing hemodialysis (N = 78).

Descriptive characteristics		N	%
Gender	Female	32	41.0
Gender	Male	46	59.0
Marital status	Married	61	78.2
	Single	14	17.9
	Widowed	3	3.8
Level of education	Literate	16	20.5
	Primary school	34	43.6
	Secondary school	18	23.1
	High school	6	7.7
	University	4	5.1
Socioeconomic status	Income below expenses	20	25.6
	Income equal to expenses	56	71.8
	Income above expenses	2	2.6
Occupation	Government employee	1	1.3
	Laborer	11	14.1
	Self-employed	5	6.4
	Retired	28	35.9
	Other	33	42.3
Health insurance	Yes	66	84.6
Health insurance	No	12	15.4
Cigarette use	Yes	11	14.1
Cigarette use	No	67	85.9
Alcohol consumption	No	78	100.0
Living arrangement	With family	75	96.2
Living arrangement	Living alone	3	3.8
Duration of chronic illness	Less than 1 year	4	5.1
	1–5 years	33	42.3
	6–10 years	25	32.1
	11 years and above	16	20.5
Chronic disease medication use	Yes	61	78.2
Chronic disease medication use	No	17	21.8
Anemia	Present	44	56.4
Anemia	Absent	34	43.6
Weekly dialysis duration (days)	2	6	7.7
Weekly dialysis duration (days)	3	72	92.3
	Min.	Max.	$\bar{x}$ ± SS
Age (years)	28	86	57.76 ± 12.50
Height (cm)	152	185	169.62 ± 8.47
Weight (kg)	45.0	107.8	74.54 ± 13.64
BMI (kg/m²)	12.2	36.6	25.21 ± 4.27

We see that the mean FSS score of the hemodialysis patients is 4.97 ± 1.11, which is above the scale’s midpoint. Next, the mean PSQI score is 7.76 ± 3.64, which is below the scale’s midpoint. Moreover, a moderate, positive, and statistically meaningful relation was found between the PSQI and the FSS scores (r = 0.310, p < 0.01). This result indicates that poorer sleep quality is associated with greater fatigue severity (please check Table 2).

Table 2.

Descriptive statistics and correlation analysis of fatigue severity and sleep quality scores among hemodialysis patients (N = 78).

Scale	Possible scale score			Patients’ obtained score
Scale	Min.	Max.	Mean	Min.	Max.	$\bar{x}$ ± SS
FSS	1	7	4	2.2	6.6	4.97 ± 1.11
PSQI^a	0	21	10.5	1	16	7.76 ± 3.64
	FSS
PSQI	r = 0.310, p = 0.006*

As the scores increase, sleep quality decreases. *p<0.01

A low, negative, and statistically noteworthy connection was identified between ferritin levels and the FSS scores (r = −0.252, p < 0.05). Similarly, a low, negative, and statistically significant correlation was observed between calcium levels and the PSQI scores (r = −0.236, p < 0.05). This finding indicates that higher calcium levels are associated with better sleep quality (please check Table 3).

Table 3.

Correlation analysis (N = 78).

Clinical and Demographic Features	FSS	PSQI
Age (years)	r = −0.033, p = 0.776	r = 0.082, p = 0.475
BMI (kg/m²)	r = −0.134, p = 0.241	r = −0.127, p = 0.269
Hemoglobin (Hb, g/dL)	r = 0.138, p = 0.229	r = 0.072, p = 0.530
Hematocrit (Htc, %)	r = −0.103^a, p = 0.371	r = 0.038^a, p = 0.742
Ferritin (ng/mL)	r = −0.252, p = 0.026*	r = 0.063, p = 0.585
Serum iron (µg/dL)	r = −0.076, p = 0.506	r = 0.062, p = 0.587
Blood urea nitrogen (BUN, µg/dL)	r = −0.008, p = 0.946	r = −0.085, p = 0.461
Creatinine (mg/dL)	r = −0.096, p = 0.404	r = −0.144, p = 0.209
Sodium (Na, mmol/L)	r = 0.140, p = 0.222	r = −0.176, p = 0.124
Potassium (K, mmol/L)	r = 0.104, p = 0.363	r = 0.023, p = 0.838
Calcium (Ca, mg/dL)	r = 0.090, p = 0.439	r = −0.236, p = 0.040*
Phosphorus (P, mg/dL)	r = 0.207, p = 0.070	r = −0.036, p = 0.753
Parathyroid hormone (PTH, pg/mL)	r = 0.125^a, p = 0.274	r = 0.017^a, p = 0.882
Albumin (g/dL)	r = −0.035, p = 0.759	r = −0.064, p = 0.580

The correlation coefficients presented in italics were calculated using Spearman’s rank-order correlation test. *p<0.05

The outcomes of the multiple linear regression analysis undertaken to examine the effects of the hemodialysis patients’ descriptive characteristics, blood parameters, and the PSQI scores on their FSS scores are presented inTable 4. The VIF values for the predictor variables were within acceptable limits (<5), leading no significant multicollinearity among the independent variables. The Durbin–Watson statistic was not significant (p > 0.05), suggesting the absence of autocorrelation. These results indicate that the regression model is reliable. The overall regression approach was statistically notable (p < 0.05), and the predictor variables explained 21.5% of the variance in the Fatigue Severity Scale scores. Chronic disease medication use and the PSQI scores were significant predictors. The effect of chronic disease medication use on fatigue severity was positive, such that individuals who did not use medication had higher fatigue scores compared to those who did (β = 0.86, 95% CI [0.17–1.56], p < 0.05). Additionally, the PSQI scores were found to be a positive and significant predictor of fatigue severity (β = 0.32, 95% CI: [0.06–0.57], p < 0.05), demonstrating that lower sleep quality corresponds to greater fatigue severity (the reader may check Table 4).

Table 4.

Analysis based on a multivariate linear regression (N = 78).

Model	B	SH	β	95% CI	t	p	VIF
Constant	0.35	9.39	-	-	0.04	0.970
Gender (RC: Male)							1.37
Female	0.21	0.32	0.19	−0.38 to 0.76	0.69	0.496
Marital status (RC: Married)							1.29
Single/widowed	0.06	0.35	0.06	−0.57 to 0.69	0.18	0.859
Educational status (RC: Literate)							1.30
Primary school	−0.32	0.38	−0.28	−0.96 to 0.40	−0.83	0.409
Secondary school	−0.15	0.47	−0.13	−0.98 to 0.71	−0.31	0.757
High school and above	−1.04	0.61	−0.93	−2.01 to 0.16	−1.72	0.093
Health Insurance (RC: Yes)							1.22
No	0.73	0.38	0.65	−0.03 to 1.33	1.91	0.062
Smoking status (RC: Yes)							1.22
No	0.12	0.40	0.11	−0.60 to 0.82	0.30	0.766
Duration of chronic illness (RC: 0–5 years)							1.25
6–10 years	−0.23	0.32	−0.21	−0.77 to 0.36	−0.73	0.470
11 years and above	−0.30	0.41	−0.27	−1.00 to 0.47	−0.73	0.467
Chronic disease medication use (RC: Yes)							1.42
No	0.97	0.39	0.86	0.17–1.56	2.50	0.016*
Anemia status (RC: Present)							1.33
Absent	−0.03	0.31	−0.02	−0.57 to 0.52	−0.09	0.929
Age (years)	−0.01	0.01	−0.10	−0.37 to 0.18	−0.71	0.481	1.33
BMI (kg/m²)	−0.03	0.04	−0.13	−0.40 to 0.15	−0.93	0.358	1.33
Hemoglobin (g/dL)	0.24	0.15	0.26	−0.06 to 0.58	1.64	0.107	1.56
Hematocrit (Htc, %)	−0.06	0.04	−0.21	−0.50 to 0.07	−1.49	0.142	1.39
Ferritin (ng/mL)	0.00	9.47e–4	−0.20	−0.48 to 0.08	−1.43	0.158	1.37
Serum iron (µg/dL)	−0.01	0.01	−0.07	−0.37 to 0.22	−0.51	0.615	1.45
Blood urea nitrogen (BUN, µg/dL)	0.01	0.01	0.28	−0.02 to 0.59	1.90	0.064	1.47
Creatinine (mg/dL)	−0.07	0.06	−0.16	−0.45 to 0.14	−1.07	0.290	1.42
Sodium (Na, mmol/L)	0.04	0.06	0.09	−0.18 to 0.37	0.69	0.495	1.34
Potassium (K, mmol/L)	−0.04	0.14	−0.04	−0.32 to 0.24	−0.28	0.777	1.36
Calcium (Ca, mg/dL)	0.03	0.05	0.09	−0.18 to 0.35	0.65	0.518	1.30
Phosphorus (P, mg/dL)	0.10	0.10	0.14	−0.12 to 0.40	1.05	0.299	1.27
Parathyroid hormone (PTH, pg/mL)	−1.61e−4	5.83e–4	−0.03	−0.29 to 0.22	−0.28	0.783	1.25
Albumin (g/dL)	−0.52	0.35	−0.19	−0.44 to 0.06	−1.51	0.137	1.23
PSQI	0.10	0.04	0.32	0.06–0.57	2.50	0.016*	1.23
R = 0.698, R² = 0.215, F_{(26, 49)} = 1.79, p = 0.039*, Durbin-Watson = 1.65, p = 0.104

RC: reference category; VIF: variance inflation factor; CI: confidence interval. *p<0.05

Discussions

In the present study, the fatigue severity and sleep quality levels of patients undergoing hemodialysis treatment were evaluated, and the factors influencing these conditions were examined. The findings indicate that fatigue is a significant and prevalent problem among individuals receiving hemodialysis. Consistently, the Kidney Disease Improving Global Outcomes (KDIGO) guidelines¹⁷ report that fatigue is the most common symptom experienced by individuals with chronic kidney disease, with a prevalence of approximately 70%.

In our investigation, the mean FSS score of the patients was found to be 4.97 ± 1.11. This value is above the midpoint of the scale, indicating that a considerable proportion of the patients experience moderate to high levels of fatigue. Consistent with our findings, the literature also reports high levels of fatigue among hemodialysis patients.^3,18–20 The differences between the findings of our study and those reported in the literature may be explained by several individual and treatment-related factors, such as the amount of ultrafiltration applied during hemodialysis sessions, session frequency and duration, age, coexisting chronic conditions, self-care capacity, life satisfaction, and muscle strength. In addition, our study revealed that patients who did not use medications related to their chronic condition had higher fatigue scores compared to those who did. The regression analysis also identified medication use as a significant predictor of fatigue. This finding is consistent with previous studies suggesting that regular medication use in chronic diseases may help maintain metabolic balance and consequently reduce fatigue levels.^3,21 However, it was observed that fatigue is associated not only with behavioral factors but also with biochemical parameters. When examining the biochemical variables related to fatigue, a low, negative, and statistically significant correlation was found between ferritin levels and the FSS scores. Ferritin is an indicator of iron storage, and low ferritin levels may indicate anemia. This finding is consistent with studies reporting that anemia is an important physiological factor contributing to the development of fatigue.^22–24 The reduction in oxygen-carrying capacity due to anemia leads to a decrease in cellular energy production, which in turn results in an increased sensation of fatigue.²⁵ Therefore, regular monitoring of ferritin levels and individualized planning of iron supplementation are clinically important in hemodialysis patients.

The mean PSQI score in the present study was 7.76 ± 3.64, indicating relatively favorable sleep quality among the participants. Nevertheless, previous research consistently shows that sleep quality is typically impaired in hemodialysis patients.^26–28 This discrepancy may be related to the patients’ consistent attendance in the dialysis program and the quality of care delivered in the hemodialysis unit. Furthermore, sleep quality appears to be influenced not only by behavioral and environmental factors but also by biochemical parameters. In our study, serum calcium levels showed a low but significant negative correlation with sleep quality, indicating that higher calcium levels were associated with better sleep quality. This finding aligns with previous research demonstrating a similar positive relationship between serum calcium and sleep quality.^29–31 The improvement in sleep quality associated with increased serum calcium levels may be explained by the role of calcium in melatonin synthesis and the regulation of circadian rhythm.³¹ The findings of this study indicate that biochemical balance and electrolyte levels are important physiological determinants in maintaining sleep quality among hemodialysis patients. Therefore, it is recommended that nursing care approaches aimed at supporting sleep quality be integrated with the regular monitoring of biochemical parameters.

In this study, a moderate, positive, and statistically significant relationship was found between the total PSQI score and fatigue severity. Similarly, Almutary et al. reported a moderate positive association between fatigue and sleep quality in patients undergoing hemodialysis.³² This finding supports the well-established link between sleep disturbances and fatigue in chronic disease populations and is consistent with previous studies in the literature.^32–34 Poor sleep quality may exacerbate fatigue, while persistent fatigue may, in turn, impair sleep quality, creating a vicious cycle that negatively affects the physical and psychosocial well-being of hemodialysis patients. Therefore, it is essential to assess both sleep quality and fatigue concurrently in clinical practice and to develop integrated interventions targeting both conditions. Moreover, longitudinal studies are needed to better elucidate the potential causal relationships among sleep disturbances, fatigue, and clinical outcomes in hemodialysis patients, and such research would provide valuable insights for future clinical strategies.

Conclusions

This study showed that fatigue and sleep quality are interrelated and clinically significant in patients undergoing hemodialysis. Patients had moderate to high fatigue levels, while sleep quality was generally favorable. Medication use predicted fatigue, and significant associations were found between ferritin and fatigue, and calcium and sleep quality. These findings suggest that biochemical balance and treatment adherence are crucial for both outcomes. Nursing care should therefore assess fatigue and sleep quality together and implement holistic, biopsychosocial interventions.

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Aysun Kazak Salti

References

Kennedy

Ryan

Kane

, et al. The impact of change of renal replacement therapy modality on sleep quality in patients with end-stage renal disease: a systematic review and meta-analysis. J Nephrol 2018; 31(1): 61–70.

Peng

Huang

Liao

, et al. Risk factors affecting the sleep quality of patients on dialysis: a single-center cross-sectional study. Medicine 2024; 103(13): e37577.

Bossola

Hedayati

Brys

ADH

, et al. Fatigue in patients receiving maintenance hemodialysis: a review. Am J Kidney Dis 2023; 82(4): 464–480.

Bossola

Tazza

Postdialysis fatigue: a frequent and debilitating symptom. In: Seminars in dialysis, 2016.

Unruh

Davison

, et al. Establishing a core outcome measure for fatigue in patients on hemodialysis: a Standardized Outcomes in Nephrology-hemodialysis (SONG-HD) Consensus Workshop Report. Am J Kidney Dis 2018; 72(1): 104–112.

Guerraoui

Prezelin-Reydit

Kolko

, et al. Patient-reported outcome measures in hemodialysis patients: results of the first multicenter cross-sectional ePROMs study in France. BMC Nephrol 2021; 22(1): 357.

Merlino

Piani

Dolso

, et al. Sleep disorders in patients with end-stage renal disease undergoing dialysis therapy. Nephrol Dial Transplant 2006; 21(1): 184–190.

McCann

Boore

JR.

Fatigue in persons with renal failure who require maintenance haemodialysis. J Adv Nurs 2000; 32(5): 1132–1142.

Yngman-Uhlin

Edéll-Gustafsson

Self-reported subjective sleep quality and fatigue in patients with peritoneal dialysis treatment at home. Int J Nurs Pract 2006; 12(3): 143–152.

10.

Unruh

Levey

D'Ambrosio

, et al. Restless legs symptoms among incident dialysis patients: association with lower quality of life and shorter survival. Am J Kidney Dis 2004; 43(5): 900–909.

11.

Canseven

. Causes of post-dialysis fatigue in hemodialysis patients. Meram Faculty of Medicine, Department of Internal Medicine, Necmettin Erbakan University, Konya, Turkiye, 2021.

12.

Krupp

Alvarez

LaRocca

, et al. Fatigue in multiple sclerosis. Arch Neurol 1988; 45(4): 435–437.

13.

Armutlu

Korkmaz

Keser

, et al. The validity and reliability of the Fatigue Severity Scale in Turkish multiple sclerosis patients. Int J Rehabil Res 2007; 30(1): 81–85.

14.

Buysse

Reynolds

Monk

, et al. Quantification of subjective sleep quality in healthy elderly men and women using the Pittsburgh Sleep Quality Index (PSQI). Sleep 1991; 14(4): 331–338.

15.

Agargun

Validity and reliability of the Pittsburgh Sleep Quality Index. Turk Psikiyatri Derg 1996; 7: 107–115.

16.

Hair

Black

Babin

, et al. Multivariate data analysis. Upper Saddle River, NJ: Pearson Education, 2013.

17.

KDIGO. KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease (CKD): Kidney Disease: Improving Global Outcomes, https://kdigo.org/wpcontent/uploads/2024/03/KDIGO-2024-CKD-Guideline.pdf. (2024, accessed 2 January 2026).

18.

Goërtz

YMJ

Braamse

AMJ

Spruit

, et al. Fatigue in patients with chronic disease: results from the population-based lifelines Cohort Study. Sci Rep 2021; 11(1): 20977.

19.

Laksmana

Indriyawati

Fatigue level of chronic kidney failure patients after undergoing hemodialysis therapy. JKG (JURNAL KEPERAWATAN GLOBAL) 2022; 7: 29–42.

20.

Ouyang

Yang

, et al. The effects of dialysis modality and emotional distress on fatigue in patients undergoing dialysis. Blood Purif 2023; 52(9-10): 751–758.

21.

Wang

Ding

, et al. Effects of sacubitril/Valsartan on resistant hypertension and myocardial work in hemodialysis patients. J Clin Hypertens 2022; 24(3): 300–308.

22.

van Haalen

Jackson

Spinowitz

, et al. Impact of chronic kidney disease and anemia on health-related quality of life and work productivity: analysis of multinational real-world data. BMC Nephrol 2020; 21(1): 88.

23.

Maisyaroh

Maslufin

Fibriyanti

, et al. Anemia and fatigue in patients with chronic kidney failure. Jurnal Kesehatan Manarang 2024; 10(1): 51–58.

24.

Supriyadi

Susanto

Ediati

Kadar Hemoglobin Berhubungan dengan Tingkat Kelelahan Pasien Penyakit Ginjal Kronis di Kota Semarang. Jurnal Keperawatan 2021; 13(4): 889–894.

25.

Arhamawati

Saryono

Awaluddin

. Correlation between the levels of urea serum, creatinine, and haemoglobin with fatigue in patient with chronic kidney disease at haemodialisa unit, dr. R. Goeteng Taroenadibrata General Hospital Purbalingga. J Bionurs 2019; 1(1): 34–46.

26.

Fletcher

Damery

Aiyegbusi

, et al. Symptom burden and health-related quality of life in chronic kidney disease: a global systematic review and meta-analysis. PLoS Med 2022; 19(4): e1003954.

27.

Huang

Cheng

Yen

Factors associated with poor sleep quality in patients with pre-dialysis chronic kidney disease: a systematic review. J Adv Nurs 2023; 79(6): 2043–2057.

28.

Panicker

Sivakarthik

Sleep quality in end stage renal disease patients undergoing hemodialysis in a tertiary care center in rural kanyakumari: a cross sectional study. Healthline 2022; 13(1):15-21.

29.

Çakir

Nişancı Kılınç

Özata Uyar

, et al. The relationship between sleep duration, sleep quality and dietary intake in adults. Sleep Biol Rhythms 2020; 18(1): 49–57.

30.

Isoda

Kiriya

Jimba

Is calcium intake associated with sleep quality?: a systematic review. BMJ Nutrition, Prevention & Health 2025; 8(2): 657-663.

31.

Jeon

Kim

, et al. Lower serum calcium levels associated with disrupted sleep and rest-activity rhythm in shift workers. Nutrition 2022; 14(15): 3021.

32.

Almutary

Alghamdi

Mezan

, et al. Sleep quality and fatigue among hemodialysis patients. Int J Noncommun Dis 2025; 10(1): 33–40.

33.

Hyun

MK.

How fatigue level is related to sleep disturbances: a large cross-sectional community study. Eur J Integr Med 2022; 49: 102097.

34.

Milrad

Hall

Jutagir

, et al. Poor sleep quality is associated with greater circulating pro-inflammatory cytokines and severity and frequency of chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) symptoms in women. J Neuroimmunol 2017; 303: 43–50.