Integrative approaches to depression in end-stage renal disease: insights into mechanisms, impacts, and pharmacological strategies

Abstract

Depression is a frequently overlooked psychiatric symptom in patients with end-stage renal disease (ESRD), seriously affecting their quality of life, risk of death, adherence to treatment, cognitive abilities, and overall health outcomes. The study investigates the prevalence of depression is in ESRD patients, along with the methods for assessment, diagnostic guidelines, underlying factors, consequences, and management strategies. The Beck Depression Inventory (BDI), with an optimal diagnostic cutoff score greater than 14, has been identified as the most accurate for diagnosing depression in ESRD, while emerging tools such as vacancy-driven high-performance metabolic assays show promise for evaluation. Depression contributes to adverse health outcomes by increasing risks of treatment withdrawal, suicide, and cognitive impairment, as well as serving as a predictor of mortality and poor treatment adherence. Even though tricyclic antidepressants and selective serotonin reuptake inhibitors are commonly used, the effectiveness of treatment remains unpredictable because clinical studies often have limitations such as small sample sizes, no randomization, and missing control groups. Innovative approaches, such as nanomaterials and traditional Chinese medicine, have shown therapeutic potential with reduced side effects. Future research should focus on specific high-risk populations, particularly older adults and women under the age of 45, to better tailor interventions. The goal of this research is to improve understanding of depression in ESRD, leading to better patient care, improved quality of life, and superior clinical results.

Main contents

1 Depression and its impact on end-stage renal disease patients

Depression is widely recognized as a complex comorbid condition associated with various chronic diseases, including renal disease, cancer, diabetes, digestive disorders, and obesity. The occurrence of depression in these groups has been associated with hindered recovery and higher death rates. For patients undergoing maintenance hemodialysis (HD), the survival rates are 83.0% at 1 year, 78% at 2 years, 69% at 3 years, and 57% at 5 years (Chi et al., 2017). These statistics highlight the importance of addressing the psychological health of individuals with end-stage renal disease (ESRD), particularly in light of the rising prevalence and essential nature of dialysis therapies.

The etiology of depression in ESRD is multifactorial and complex. Patients with ESRD face both physical and psychological burdens that contribute to the development and exacerbation of depression. Physiologically, the progression of kidney disease leads to the accumulation of uremic toxins and increased inflammatory cytokines, such as interleukin-6 (IL-6), which negatively affect brain function and mood regulation, thereby linking kidney disease to depressive symptoms (Jayakumar et al., 2023; Yuan et al., 2021; Bugnicourt et al., 2013; Liu et al., 2024a). Psychologically, ESRD patients face significant challenges, including dialysis, frequent hospitalizations, declining kidney function, and physical limitations, all of which contribute to emotional distress, helplessness, and depression (Natale et al., 2019a). Reduced life expectancy and economic burden further exacerbate these mental health risks, highlighting the need for research into their psychological wellbeing (Halen et al., 2012; Yang et al., 2020).

A two-decade bidirectional cohort study found a reciprocal link between depression and chronic kidney disease (CKD): depressive symptoms increased the risk of CKD (Liu et al., 2022), and impaired kidney function raised the risk of depression. This highlights the need for careful management of both conditions to prevent progression. Since both are modifiable risk factors, early interventions by healthcare providers are crucial. Additionally, depression predicts mortality in ESRD patients, necessitating further research to understand its impact on disease progression and survival, with the goal of enhancing both psychological and clinical outcomes in this group.

This review aims to provide a comprehensive synthesis of the current understanding of depression in patients with ESRD, focusing on its prevalence, underlying factors, and management strategies. A thorough literature search was conducted across major databases, including PubMed, Scopus, and Google Scholar. The search focused on studies relevant to depression in ESRD patients, with no restrictions on publication date. Studies were included if they (i) examined depression in adult ESRD patients, (ii) provided data on depression prevalence, diagnostic methods, or underlying factors, and (iii) discussed treatment strategies or management approaches for depression in this population. Studies were excluded if (i) they were not published in English, (ii) focused on other psychiatric conditions. This review is based on a synthesis of these selected studies to provide a comprehensive overview of depression in ESRD, its consequences, and potential therapeutic interventions.

2 Prevalence of depression in pre-dialysis, dialysis, and peritoneal dialysis (PD)

Research has shown varying prevalence rates of depression among patients with pre-dialysis CKD, HD, and peritoneal dialysis (PD) populations (Table 1). In eastern Turkey, 35.0% of 120 CKD patients not undergoing dialysis had depression scores exceeding the threshold, according to validated diagnostic tools (Cantekin et al., 2014). Similarly, a Chinese study involving 334 CKD patients, 77.5% of whom were in stages 1–3, found a depression prevalence of 22.2%, highlighting the presence of psychopathological issues even before dialysis initiation (Duan et al., 2021). Higher rates of depression have been documented in patients undergoing dialysis. A cross-sectional study in Lebanon, utilizing the Hospital Anxiety and Depression Scale (HADS), reported a depression prevalence of 40.8% among 83 HD patients at a tertiary medical center (Semaan et al., 2018). In Brazil, an investigation using the Beck Depression Inventory II (BDI-II) in 148 HD patients revealed a depression prevalence of 68.2%, with severity classified as mild (49.5%), moderate (41.5%), and severe (9%) (Silva Junior et al., 2014). Klein et al. (1981) estimated a 15% depression rate in ESRD patients, while other studies demonstrated that at least 25% of patients on HD and 30% of those on PD exhibit depressive symptoms (Juergensen et al., 1996; Kimmel et al., 1993; Kimmel et al., 1995). Foster et al. (1973) and Smith et al. (1985) independently reported a 47% prevalence of depression among ESRD and HD populations. Remarkably, Reichsman and Levy (1972) observed a 100% prevalence of depression in their HD cohort, further underscoring the widespread burden of this condition.

The association between depression and dialysis modality remains a topic of debate. Some studies indicate no significant difference in depression levels between HD and PD patients (He et al., 2021). However, other research suggests that patients receiving HD may experience a higher prevalence of depression compared to those on PD (30.6% versus 20.4%) (Adejumo et al., 2024). Further exploration is required to clarify the potential effects of dialysis modality on the mental wellbeing of ESRD patients, given these conflicting results.

3 Identification and measurements of depression in ESRD

Depression is often underrecognized and underestimated in patients with ESRD, primarily due to three factors. First, the symptomatology of depression frequently overlaps with uremic symptoms associated with ESRD. Individuals afflicted by both conditions commonly report experiencing fatigue, apathy, impaired concentration, motor tremors, reduced appetite, gastrointestinal disturbances, and sleep disorders. These symptoms are characteristic of both uremia and depression, complicating early diagnosis of depression and contributing to variability in its reported prevalence. Second, patients often deny their illness, potentially minimizing or obscuring symptoms, which challenges the accurate assessment of depression. Lastly, variability in the prevalence of depression is linked to various methodological issues. Therefore, accurate and reliable measures are essential to differentiate depressive symptoms from uremic symptoms in ESRD patients.

Among the available diagnostic tools, the Beck Depression Inventory (BDI) has demonstrated high accuracy in this population, with an optimal diagnostic cutoff score greater than 14. Depression severity is categorized as follows: 0–13 (Minimal), 14–19 (Mild), 20–28 (Moderate), and 29–63 (Severe). Table 2 summarizes common assessment tools used for diagnosing depression in ESRD. In addition to the BDI, significant advancements in diagnostic methods have been made. Recent evidence suggests that multiple assessments of depression over time may provide a more accurate prediction of mortality compared to single evaluations. For example, proton magnetic resonance spectroscopy (¹H-MRS) has shown promise in detecting metabolite changes in the brains of ESRD patients with depression, offering a foundation for early diagnosis and assessment of depression severity in this population (Wang et al., 2020). This underscores the urgent need for early and effective diagnostic tools for depression in ESRD.

Beyond traditional methods, new diagnostic technologies are being investigated. Chen et al. (2024) developed a high-performance metabolite-based test using vacancy-engineered cobalt oxide (Vo-Co₃O₄) with laser desorption/ionization mass spectrometry. These optimized nanoparticles enhance signals and allow for strong plasma metabolic fingerprint recordings. This progress contributes to the development of diagnostic tools for assessing depression and provides new insights for its management in ESRD patients.

Artificial intelligence (AI) has also become a promising tool in interventions for behavioral health. Payam and colleagues developed a chatbot for depression analysis, using Dialogflow as the conversational platform. This comprehensive mass screening method can detect early depression and assist in facilitating automated and nuanced communication. Although it is not meant to substitute mental health experts, the chatbot shows promise in improving early detection using validated scoring methods. Collectively, these cutting-edge diagnostic tools and technologies offer potential for enhancing the early detection and treatment of depression in patients with ESRD.

An effective team is crucial for evaluating and treating depression in ESRD patients, ensuring precise assessments and successful management. When the diagnosis of depression is unclear, it is recommended to consult a mental health professional before starting any medication. Not every ESRD patient suspected of having depression requires a referral to a psychiatrist. A comprehensive depression screening should be conducted first. Tools like the BDI, Patient Health Questionnaire (PHQ-9), and Center for Epidemiological Studies Depression Scale (CES-D) are frequently used for screening. Diagnosing depression in uremic patients is challenging due to overlapping symptoms. Self-reported scales like the BDI may lead to overdiagnosis by placing too much on physical symptoms (Hedayati et al., 2006). In HD patients, the BDI (cutoff ≥14) showed 62% sensitivity and 81% specificity, while the PHQ-9 (cutoff ≥10) had the best performance with 92% sensitivity and specificity. The CES-D (cutoff ≥18) had 69% sensitivity and 83% specificity (King-Wing Ma and Kam-Tao Li, 2016). These results highlight the need for careful selection and integration of screening tools in a multidisciplinary approach for managing depression in ESRD patients.

4 Mechanism of depression in ESRD

The mechanism of depression in patients with ESRD is multifactorial, as these individuals often face numerous comorbid conditions (Gerogianni et al., 2018). The contributing factors can be summarized in Figure 1 as follows: 1) Comorbid Diseases: Depression in ESRD is frequently influenced by coexisting conditions, such as cardiovascular disease (CVD), diabetes, and immune dysfunction (Fan et al., 2014); 2) Malnutrition and Chronic Inflammation: These factors are prevalent in ESRD patients and significantly contribute to depressive disorders (Guenzani et al., 2019; Choi et al., 2012); 3) Chronic Pain and Sleep Disorders: Persistent pain and disrupted sleep are common and associated with high rates of depression in ESRD (Liu et al., 2021; Pandi-Perumal et al., 2020); 4) Non-Adherence: Non-adherence to treatment regimens is both a consequence and a contributing factor to depression (Gebrie and Ford, 2019); 5) Uremia: The accumulation of uremic toxins negatively impacts the central nervous system, exacerbating depressive symptoms; 6) Decreased Sexual Function: Impaired sexual health is a significant psychological burden for many ESRD patients; 7) Fear of Death: The existential threat posed by ESRD and its life-sustaining treatments can lead to profound anxiety and depression; 8) Low Family Support: Limited familial support may impair patients’ self-care abilities and worsen their emotional wellbeing; 9) Reduced Physical Performance: Decreased motivation and physical limitations further contribute to depressive symptoms; 10) COVID-19 and the Kidney-Brain Axis: The recent COVID-19 pandemic has added an additional layer of stress, potentially affecting the kidney-brain axis and exacerbating depression in ESRD patients.

FIGURE 1

Among these factors, the impact of COVID-19 on depression is particularly noteworthy. Patients with ESRD are more vulnerable to COVID-19 infection due to their compromised immune systems and the high-risk environment of HD centers during viral outbreaks. Studies have shown that the prevalence of depression in patients with COVID-19 can be as high as 45% (Deng et al., 2021). Moreover, depression and stress induced by COVID-19 can disrupt the immune system, exacerbating the severity of the infection (2021). The mechanisms underlying COVID-19-induced depression include elevated levels of pro-inflammatory cytokines, increased cortisol levels, mitochondrial dysfunction, and deficiencies in vitamin D3 and nutrition (Mohammadkhanizadeh and Nikbakht, 2021; Mazza et al., 2020). Additionally, ESRD patients with comorbidities are at heightened risk of mortality from COVID-19. A comprehensive understanding of the mechanisms and factors contributing to depression in COVID-19 patients is crucial for developing effective therapeutic strategies, which may help enhance preparedness for future pandemics, especially among vulnerable populations such as HD patients.

The kidney-brain axis has garnered attention due to shared features between the brain and kidneys, linking CKD-related issues like white matter injury and vascular dysfunction to neurodegenerative diseases such as depression (Ariton et al., 2021; Xie et al., 2022; Miranda et al., 2017). Altered cerebral hemodynamics in CKD patients is tied to cognitive impairment. Understanding these interactions is crucial for creating targeted treatments for depression in CKD patients (Viggiano et al., 2020; Kim et al., 2022).

Additionally, uremic toxins from renal failure contribute to depression in ESRD (Duranton et al., 2012), as PD and HD only partially remove these toxins, which cause oxidative stress and inflammation, affecting the central nervous system (CNS) and disrupting neurotransmitter function (Miller and Raison, 2016). Furthermore, depression is strongly associated with stress-related mechanisms, including the hypothalamic-pituitary-adrenal (HPA) axis, which can be greatly affected by the composition of the gut microbiome (Sudo et al., 2004). Imbalances in gut microbiota play a role in depression by affecting systemic inflammation, disrupting the HPA axis, and changing neurotransmitter signaling (Peirce and Alviña, 2019).

Depression in ESRD can also be conceptualized within the framework of perceived loss. This includes such losses as renal function, dietary and fluid restrictions, financial difficulties, uncertainty about the future, and social isolation. Research shows that over 70% of patients are unaware of their depressive symptoms and fail to recognize the need for help (Johnson and Dwyer, 2008). Therefore, understanding the intricate relationship between depression and health outcomes, including mortality in ESRD, is of paramount importance to improving patient care and quality of life.

5.Depression affects health outcomes in ESRD

Previous research has focused primarily on medical and physiological factors influencing health outcomes in patients with ESRD, often overlooking the significant role of mental health. However, emerging evidence suggests that the use of mental health medications is associated with improved survival rates in ESRD patients. Table 3 summarizes the key factors contributing to adverse health outcomes in this population, including impaired immune responses, heightened inflammation, malnutrition, poor adherence to treatment, and decreased physical activity.

Notably, patients with depression who are undergoing HD have been found to experience significantly higher rates of hospitalization (Lacson et al., 2014). van Dijk et al. (2013) found that depression is associated with both increased mortality risk and a higher prevalence of comorbidities in HD patients. Among the various risk factors affecting health outcomes in ESRD, depression is one of the most influential. Its pervasive impact underscores the need for mental health evaluation and intervention as an integral component of ESRD management.

Current guidelines for the management of ESRD emphasize the importance of assessing depression as part of routine clinical evaluations. By addressing depression alongside traditional clinical factors, healthcare providers can potentially improve overall patient outcomes, reduce hospitalizations, and enhance quality of life for individuals with ESRD.

5.1 Depression increases the risks of withdrawal and suicide in ESRD

In a 20-year study with 716 participants, 18.5% of all deaths were due to dialysis withdrawal (Mailloux et al., 1993). Patients who withdrew from dialysis were generally older, with 65.1% being over 61 years old. Several factors contributed to dialysis withdrawal, including cancer, catabolism, malnutrition, financial strain, and dissatisfaction with life. Notably, the rate of withdrawal was higher among white and male patients compared to Black and female patients (Nelson et al., 1994). Furthermore, older age and diabetic kidney disease were recognized as key factors affecting the choice to stop dialysis.

Alarmingly, the suicide rate among dialysis patients is 50 times that of the general population, according to Levy (2000). A comparable study utilizing the Taiwan National Health Insurance Research Database found that ESRD patients receiving HD had a notably elevated suicide risk compared to controls (Liu et al., 2017). The suicide risk was especially high in the initial 0–3 months after starting dialysis. Even with extensive national health insurance for dialysis in Taiwan, the suicide risk for ESRD patients on dialysis was still about 140% higher than that of the general population (Chen et al., 2018).

Dialysis patients use various methods of suicide, with consuming potassium-rich foods and severing HD vascular access being common (Leggat et al., 1997). A study in Taiwan found that most suicides involved severing HD vascular access. This highlights the need to address suicide risks in chronic disease patients (Shulman et al., 1989). Early diagnosis and management of depression are crucial, and healthcare providers should regularly check for suicidal thoughts in ESRD patients. If present, immediate mental health intervention is necessary. Proactive mental healthcare and strong psychosocial support can enhance quality of life and reduce mortality in these patients.

5.2 Depression accounts for cognitive impairment

The mechanisms behind cognitive impairment in CKD and ESRD are not well understood (Kim et al., 2022). Recent studies reveal a complex interplay between depression and cognitive impairment in ESRD, where depression can be both a symptom and a response to early cognitive decline (Chan et al., 2022; Kim et al., 2022; Tian et al., 2022; Feng et al., 2022). The main connections between depression and cognitive impairment include: 1) depression as a common symptom of cognitive dysfunction, 2) a reaction to early cognitive deficits, 3) depression’s own detrimental effects on cognitive function, and 4) its role as a risk factor or early indicator of cognitive decline. Key mechanisms linking the two include vascular injury, changes in glucocorticoid steroids, hippocampal atrophy, and increased β-amyloid plaque deposition, systemic and neuroinflammation and deficiencies in nerve growth factors or neurotrophins (Byers and Yaffe, 2011).

Vascular disease is a key link between depression and cognitive impairment, contributing to both conditions. Typically, reduced cerebral blood flow leads to cognitive issues, but CKD patients often have higher-than-normal blood flow due to anemia-induced hyperperfusion. This compensatory mechanism may temporarily offset vascular dysfunction but doesn't prevent long-term brain damage. Understanding these interactions highlights the importance of targeted treatments for CKD and ESRD patients to address these interconnected issues.

5.3 Depression predicts the mortality in ESRD

Kimmel et al. (2000) first showed that persistent depression increases mortality risk in HD patients, with repeated depression assessments being more reliable predictors of survival than baseline depression alone. Studies confirm depression’s link to higher death risk in dialysis patients (Burton et al., 1986), with Young et al. (2010) noting its prediction of both all-cause and CVD mortality in HD patients. While chronic depression affects ESRD mortality, the impact of depression severity is unclear. Some research links severe depression to higher hospitalization and death risks (Lopes et al., 2002; Kimmel et al., 2000). Some research links severe depression to higher hospitalization and death risks (Kimmel et al., 2000, 1998; Christensen et al., 1994).

In summary, depression significantly increases mortality risk in ESRD patients, especially through its connection to cardiovascular disease, which remains the leading cause of death in this population (van Dijk et al., 2013); Additionally, depressive disorders contribute to severe immune dysfunction, which is the second leading cause of death in ESRD (Chilcot et al., 2008). Furthermore, depression promotes inflammation, a recognized risk factor for CVD, diabetes, and various age-related diseases (Jaremka et al., 2013). Given the high prevalence of untreated depression in ESRD patients and its profound implications for survival, further research is warranted to better define the levels and specific symptoms of depression that most strongly influence mortality. Early identification and targeted interventions may help mitigate the adverse effects of depression on survival outcomes in ESRD patients.

5.4 Depression leads to non-adherence in ESRD

Depression is a well-recognized factor contributing to non-adherence in ESRD patients, which exacerbates mortality risks. A study showed that renal patients with depression are three times more likely to have reduced adherence to their treatment regimens compared to those without depression (Ossareh et al., 2014). This non-adherence includes failure to follow prescribed medication, dietary, fluid, and treatment regimens, all of which are essential components of dialysis prescriptions. Non-adherence directly contributes to adverse health outcomes and increased mortality rates.

Adherence to treatment is assessed using various laboratory-based and behavioral adherence indices, all of which are closely associated with patient health outcomes. For example, transplant centers often consider adherence to HD treatment as a key factor in evaluating candidates for renal transplantation. Patients with depression, however, are more likely to struggle with adherence to these regimens. Specifically, non-adherence to medications such as calcium carbonate has been associated with elevated serum phosphorus concentrations and parathyroid hormone (PTH) levels, further complicating the management of ESRD.

Effective management of depression can significantly improve medication adherence and, by extension, enhance overall patient care. Adherence to prescribed treatments is predominantly correlated with depressive symptom scores, highlighting the importance of addressing depression as part of a comprehensive care plan for ESRD patients. Early recognition and treatment of depression may mitigate the risks associated with non-adherence and improve clinical outcomes for patients with ESRD.

5.5 Depression predict sarcopenia in advanced CKD and dialysis

Sarcopenia, a muscle disorder characterized by reduced muscle mass, diminished quality, and impaired muscle function (e.g., strength), commonly occurs in individuals with advanced CKD or those undergoing dialysis. This condition often develops as a secondary complication of aging or the inflammatory processes related to organ failure. The progression of sarcopenia in these populations is closely linked to increased mortality and hospitalization rates (Pereira et al., 2015; Giglio et al., 2018). Notably, studies have identified a significant association between depression and sarcopenia in CKD and dialysis patients, including elderly HD patients (Kim et al., 2014) and participants in a multicenter cohort study (Kurita et al., 2021a).

The strong link between depression and sarcopenia can be explained by several factors. Depressed individuals often engage less in physical activities essential for muscle maintenance (Biddle and Asare, 2011; Heissel et al., 2023; Pearce et al., 2022). Additionally, depression is linked to higher levels of pro-inflammatory cytokines like interleukin-6, leading to chronic inflammation, protein breakdown, and muscle wasting (Chang et al., 2024; Colasanto et al., 2020; Dantzer et al., 2008). These inflammatory processes exacerbate muscle wasting and the progression of sarcopenia (Noce et al., 2021; Pan et al., 2021). Early detection and treatment of depression in CKD and dialysis patients is vital for reducing muscle loss and improving outcomes (Li et al., 2024; Liu et al., 2024b; Kurita et al., 2021b). Addressing both physical activity and inflammation may effectively alleviate sarcopenia in these patients.

6 Therapies for depression in ESRD

Managing depression in ESRD is complex and requires a multidisciplinary team, including nephrologists, psychiatrists, dialysis nurses, and physiotherapists. Treatment strategies are divided into non-pharmacological and pharmacological approaches.

6.1 Non-pharmacological treatments

Non-pharmacological treatments, such as cognitive behavioral therapy (CBT) and exercise, are vital. CBT helps restructure negative thoughts and behaviors, effectively reducing depressive symptoms in CKD patients. Exercise, in particular, is an important non-pharmacological approach for alleviating depression in ESRD patients (Mitrou et al., 2013; Grigoriou et al., 2015). It not only reduces depressive symptoms but also enhances cardiovascular health, reduces pain, and improves overall wellbeing (Grigoriou et al., 2024; Mafra and Fouque, 2014). When combined with pharmacological treatments, non-pharmacological therapies, such exercise and CBT, are essential components of a comprehensive treatment plan for depression in this population.

6.2 Pharmacological treatments

Pharmacological treatments are complex because renal dysfunction affects drug absorption, protein binding, and metabolism, resulting in higher drug levels. Dialysis can further reduce drug concentrations, causing potential rebound effects. These challenges complicate dosing and necessitate further research for optimization.

Tricyclic antidepressants (TCAs) and selective serotonin reuptake inhibitors (SSRIs) are commonly used to treat depression in ESRD patients. The European Renal Best Practice Guidelines recommend SSRIs as the first choice for CKD patients with moderate to severe depression (King-Wing Ma and Kam-Tao Li, 2016; Cukor and Kimmel, 2018). However, evidence for the effectiveness of SSRI is limited, with many studies lacking randomization and control. For example, a trial found fluoxetine ineffective in improving depression scores in HD patients compared to placebo (Blumenfield et al., 1997). Conversely, another study showed that 20 mg/day of fluoxetine was effective and safe for both HD patients and those with normal kidney function (Levy et al., 1996). Additionally, a trial demonstrated that the 12-week sertraline treatment significantly improved depression symptoms in 47.5% of HD patients (Taraz et al., 2013). Paroxetine combined with psychotherapy showed significant therapeutic effects, leading to improvements in depressive symptoms and increases in several nutritional markers in HD patients (Koo et al., 2005). Wuerth et al. also studied antidepressant treatment in 44 ESRD patients on peritoneal dialysis (PD). They found that sertraline, citalopram, bupropion, nefazodone, or paroxetine led to significant improvements in depressive symptomatology in 23 patients who completed the treatment (Wuerth et al., 2003). Table 4 summarizes the commonly used antidepressants and their recommended dosages for ESRD patients. Table 5 provides an overview of various studies evaluating SSRIs for depression in ESRD patients, highlighting the mixed results and the need for more controlled trials. Although antidepressants show positive results, their safety and efficacy in dialysis patients remain unclear. A systematic review on SSRIs in these patients was inconclusive due to the limited number of studies and short follow-up periods (Palmer et al., 2016). More clinical trials are necessary to determine the best antidepressant therapy for dialysis patients.

Vitamin D deficiency is a potential depression risk factor in ESRD patients, and some studies suggest that vitamin D supplementation might help boost serotonin and modulating inflammation (Somoza-Moncada et al., 2023; Jahan-Mihan et al., 2024). Depression and suicide are both linked to low serotonin levels and systemic inflammation (Grudet et al., 2014). However, a trial with 746 dialysis patients in Southeast China found that high-dose vitamin D3 did not significantly alleviate depressive symptoms in those with vitamin D deficiency (Wang et al., 2016). This highlights the need for more research to understand how vitamin D contributes to depression management in ESRD patients.

6.3 Challenges in antidepressant use for ESRD patients

Treating depression in ESRD patients is challenging due to side effects like arrhythmias and dry mouth, which result from polypharmacy and altered drug metabolism, requiring careful dose adjustments. Physical activity is crucial for reducing depressive symptoms and offers benefits like improved cardiovascular function and enhanced cerebral blood flow. Treatment should be guided by specialists using a multidisciplinary approach involving nephrologists, psychiatrists, social workers, and dialysis staff. More research is needed on safer antidepressants for ESRD patients, as there is currently a lack of clinical trials. Moving forward, integrating suitable medication with regular physical exercise should be encouraged as a comprehensive strategy for managing depression in ESRD. In summary, treating depression in ESRD involves careful management of both medications and non-pharmacological therapies. Antidepressants should be personalized based on kidney function, while also incorporating physical activity and possibly vitamin D. Caution is necessary due to altered drug metabolism and potential side effects. More research is needed to improve treatment and outcomes.

7 Nanomaterials for the treatment of depression

Current antidepressants can cause significant side effects and interactions, underscoring the need for new treatments. Nanoparticle-based drug delivery systems show promise in improving drug delivery across the blood-brain barrier, controlling release, and altering pharmacokinetics (van den Broek et al., 2022; Tosi et al., 2020). They can target specific sites and safely deliver drugs, offering a potential solution for challenging brain diseases. Table 6 provides a summary of nanomaterials used in depression treatment. Further research is needed to assess the efficacy of these treatments for ESRD.

Oral drug administration for depression is common but has drawbacks, such as first-pass metabolism and adherence issues, leading to variable plasma levels and side effects (Andrade, 2019). Intranasal delivery offers a promising alternative by bypassing the blood-brain barrier and first-pass metabolism, thereby reducing side effects (Alberto et al., 2022). Future psychiatric treatments may increasingly rely on non-oral methods, such as implants and transdermal systems. These options offer the potential for more regulated and prolonged drug release, with fewer side effects, thereby enhancing the overall therapeutic effectiveness for conditions such as depression.

8 Traditional Chinese medicine (TCM) in the treatment of depression in ESRD

Rencently, there has been a significant focus on exploring herbal remedies from Traditional Chinese Medicine (TCM) as possible treatments for depression. Certain TCM formulas have shown great effectiveness, targeting multiple areas with minimal toxicity. These formulas make promising choices for treating depression, even though the exact molecular mechanisms are not yet understood (Table 7). In TCM, depression is classified as an “emotional disease,” whith depressive symptoms historically described in various terms such as “epilepsy,” “insomnia,” “hysteria,” “lily disease,” and “sensation of gas rushing” in ancient Chinese medical texts. Based on the emotional mutual-restriction theory, the idea of “joy counteracting sadness” was employed to improve low spirits. Furthermore, ancient Chinese texts, such as the Shen Nong Ben Cao Jing, recommended the use of herbs like “pipistrelle” and “albizzia” to help restore both physical function and emotional balance. Although these treatments show promise, depression remains a major challenge in modern medicine due to the incomplete understanding of its pathogenesis. Currently, no existing treatments can completely stop or reverse the early progression of depression.

9 Special population

In recent decades, the aging global population has contributed to a rise in chronic diseases among the elderly, with older adults showing the highest rates of CKD. Depression, linked to higher mortality and reduced quality of life, increases their vulnerability (Farrokhi et al., 2014). However, studies on elderly ESRD patients are limited. Research by Alencar et al. (2020) found high depression rates in older HD patients, which correlated with lower quality of life, reduced serum albumin, and higher parathyroid hormone levels. This suggests that assessing depression and quality of life should be key components in managing these patients.

Another significant concern is the notably elevated mortality rates in women under the age of 45. Within these populations, various female hormonal disorders can result in menstrual irregularities, anovulation, infertility, sexual abnormalities, early menopause, accelerated bone loss, and a potentially heightened risk of cardiovascular complications (Guglielmi, 2013). Sexual disorders are prevalent in this demographic, often correlating with depression and a decline in quality of life. Khaira et al. (2012) conducted a study examining depression and marital dissatisfaction among Indian HD patients and their spouses. The study found that male spouses experienced greater marital stress than their female counterparts. Despite the high prevalence of depression among female patients, it remains underdiagnosed and undertreated. It is well-established that women generally have a longer life expectancy than men. Therefore, gender-specific medical and psychosocial conditions significantly impact female patients with ESRD, warranting increased attention and tailored care.

10 Conclusion and prospection

Depression is common in ESRD patients and is linked to higher mortality and worsening kidney function. Poor kidney function is associated with a higher likelihood of depression. Early and accurate depression assessment is vital for improving patients’ quality of life. Factors such as malnutrition, pain, sleep disorders, cardiovascular disease, and unemployment can trigger depression in ESRD patients. Depression worsens health outcomes, raising the risk of treatment withdrawal, suicide, and cognitive issues. This study is the first to highlight the significant benefits of nanomaterials and traditional Chinese medicine in treating depression, with minimizing side effects. It's important to focus on specific groups, especially older adults and women under 45, to enhance intervention strategies.

Nonetheless, there are still several obstacles: 1) To confirm these associations, thorough randomized controlled trials need to be designed and conducted. 2) Additionally, patients should be formally screened when starting HD treatment. 3) A thorough examination of the risk factors for depression in ESRD is urgently required. 4) Future treatments for depression in ESRD should prioritize the development of medications with minimal side effects.

References

• 1

  Adejumo O. A. Edeki I. R. Sunday Oyedepo D. Falade J. Yisau O. E. Ige O. O. et al (2024). Global prevalence of depression in chronic kidney disease: A systematic review and meta-analysis. J. Nephrol.37, 2455–2472. 10.1007/s40620-024-01998-5

  • CrossRef
  • Google Scholar

• 2

  Alberto M. Paiva-Santos A. C. Veiga F. Pires P. C. (2022). Lipid and polymeric nanoparticles: successful strategies for nose-to-brain drug delivery in the treatment of depression and anxiety disorders. Pharmaceutics14 (12), 2742. 10.3390/pharmaceutics14122742

  • CrossRef
  • Google Scholar

• 3

  Alencar S. B. V. de Lima F. M. Dias L. do A. Dias V. d. A. Lessa A. C. Bezerra J. M. et al (2020). Depression and quality of life in older adults on hemodialysis. Rev. Bras. Psiquiatr.42 (2), 195–200. 10.1590/1516-4446-2018-0345

  • CrossRef
  • Google Scholar

• 4

  Andrade C. (2019). Oral ketamine for depression, 2: Practical considerations. J. Clin. Psychiatry80 (2), 19f12838. 10.4088/JCP.19f12838

  • CrossRef
  • Google Scholar

• 5

  Ariton D. M. Jiménez-Balado J. Maisterra O. Pujadas F. Soler M. J. Delgado P. (2021). Diabetes, albuminuria and the kidney-brain Axis. J. Clin. Med.10 (11), 2364. 10.3390/jcm10112364

  • CrossRef
  • Google Scholar

• 6

  Ataei M. Gumpricht E. Kesharwani P. Jamialahmadi T. Sahebkar A. (2023). Recent advances in curcumin-based nanoformulations in diabetes. J. Drug Target.31 (7), 671–684. 10.1080/1061186X.2023.2229961

  • CrossRef
  • Google Scholar

• 7

  Biddle S. J. Asare M. (2011). Physical activity and mental health in children and adolescents: A review of reviews. Br. J. Sports Med.45 (11), 886–895. 10.1136/bjsports-2011-090185

  • CrossRef
  • Google Scholar

• 8

  Blumenfield M. Levy N. B. Spinowitz B. Charytan C. Beasley C. M. Jr Dubey A. K. et al (1997). Fluoxetine in depressed patients on dialysis. Int. J. Psychiatry Med.27 (1), 71–80. 10.2190/wq33-m54t-xn7l-v8mx

  • CrossRef
  • Google Scholar

• 9

  Bugnicourt J. M. Godefroy O. Chillon J. M. Choukroun G. Massy Z. A. (2013). Cognitive disorders and dementia in ckd: the neglected kidney-brain Axis. J. Am. Soc. Nephrol.24 (3), 353–363. 10.1681/asn.2012050536

  • CrossRef
  • Google Scholar

• 10

  Burton H. J. Kline S. A. Lindsay R. M. Heidenheim A. P. (1986). The relationship of depression to survival in chronic renal failure. Psychosom. Med.48 (3-4), 261–269. 10.1097/00006842-198603000-00011

  • CrossRef
  • Google Scholar

• 11

  Butt M. D. Ong S. C. Butt F. Z. Sajjad A. Rasool M. F. Imran I. et al (2022). Assessment of health-related quality of life, medication adherence, and prevalence of depression in kidney failure patients. Int. J. Environ. Res. Public Health19 (22), 15266. 10.3390/ijerph192215266

  • CrossRef
  • Google Scholar

• 12

  Byers A. L. Yaffe K. (2011). Depression and risk of developing dementia. Nat. Rev. Neurol.7 (6), 323–331. 10.1038/nrneurol.2011.60

  • CrossRef
  • Google Scholar

• 13

  Cantekin I. Curcani M. Tan M. (2014). Determining the anxiety and depression levels of pre-dialysis patients in eastern Turkey. Ren. Fail.36 (5), 678–681. 10.3109/0886022X.2014.890009

  • CrossRef
  • Google Scholar

• 14

  Cao X.-J. Huang X.-C. Wang X. (2019). Effectiveness of Chinese herbal medicine granules and traditional Chinese medicine-based psychotherapy for perimenopausal depression in Chinese women: a randomized controlled trial. Menopause26 (10), 1193–1203. 10.1097/GME.0000000000001380

  • CrossRef
  • Google Scholar

• 15

  Caruana L. Nichols L. Kelly L. (2022). Malnutrition, symptom burden and predictive validity of the patient-generated subjective global assessment in central Australian haemodialysis patients: a cross sectional study. Nutr. and Dietetics J. Dietitians Assoc. Aust.79 (5), 555–562. 10.1111/1747-0080.12763

  • CrossRef
  • Google Scholar

• 16

  Chan F. H. F. Goh Z. Z. S. Zhu X. Tudor Car L. Newman S. Khan B. A. et al (2022). Subjective cognitive complaints in end-stage renal disease: a systematic review and meta-analysis. Health Psychol. Rev.17, 614–640. 10.1080/17437199.2022.2132980

  • CrossRef
  • Google Scholar

• 17

  Chang J. Jiang T. Shan X. Zhang M. Li Y. Qi X. et al (2024). Pro-inflammatory cytokines in stress-induced depression: novel insights into mechanisms and promising therapeutic strategies. Prog. Neuropsychopharmacol. Biol. Psychiatry131, 110931. 10.1016/j.pnpbp.2023.110931

  • CrossRef
  • Google Scholar

• 18

  Chen I. M. Lin P. H. Wu V. C. Wu C. S. Shan J. C. Chang S. S. et al (2018). Suicide deaths among patients with end-stage renal disease receiving dialysis: A population-based retrospective cohort study of 64,000 patients in Taiwan. J. Affect. Disord.227, 7–10. 10.1016/j.jad.2017.10.020

  • CrossRef
  • Google Scholar

• 19

  Chen S. Conwell Y. Jiang X. Li L. Zhao T. Tang W. et al (2022). Effectiveness of integrated care for older adults with depression and hypertension in rural China: A cluster randomized controlled trial. PLoS Med.19 (10), e1004019. 10.1371/journal.pmed.1004019

  • CrossRef
  • Google Scholar

• 20

  Chen X. Wang Y. Pei C. Li R. Shu W. Qi Z. et al (2024). Vacancy-driven high-performance metabolic assay for diagnosis and therapeutic evaluation of depression. Adv. Mater.36 (28), e2312755. 10.1002/adma.202312755

  • CrossRef
  • Google Scholar

• 21

  Chi X. Guo Y. Tan Y. (2017). Retrospective analysis of 7-year maintenance hemodialysis in a single center. Guangdong Med. J.38 (11), 1731–1733. 10.13820/j.cnki.gdyx.2017.11.012

  • CrossRef
  • Google Scholar

• 22

  Chilcot J. Wellsted D. Da Silva-Gane M. Farrington K. (2008). Depression on dialysis. Nephron. Clin. Pract.108 (4), c256–c264. 10.1159/000124749

  • CrossRef
  • Google Scholar

• 23

  Chiou C.-P. Bai Y.-L. Lai L.-Y. Hsieh H.-C. Chang S.-T. (2023). Hierarchical multiple regression investigating factors associated with depressive symptoms in the middle-aged and elderly undergoing haemodialysis. BMC Public Health23 (1), 237. 10.1186/s12889-023-15140-w

  • CrossRef
  • Google Scholar

• 24

  Choi M.-J. Seo J.-W. Yoon J.-W. Lee S. K. Kim S. J. Lee Y. K. et al (2012). The malnutrition-inflammation-depression-arteriosclerosis complex is associated with an increased risk of cardiovascular disease and all-cause death in chronic hemodialysis patients. Nephron. Clin. Pract.122 (1–2), 44–52. 10.1159/000348509

  • CrossRef
  • Google Scholar

• 25

  Christensen A. J. Wiebe J. S. Smith T. W. Turner C. W. (1994). Predictors of survival among hemodialysis patients: effect of perceived family support. Health Psychol. Official J. Div. Health Psychol.13 (6), 521–525. 10.1037//0278-6133.13.6.521

  • CrossRef
  • Google Scholar

• 26

  Cohen S. D. Norris L. Acquaviva K. Peterson R. A. Kimmel P. L. (2007). Screening, diagnosis, and treatment of depression in patients with end-stage renal disease. Clin. J. Am. Soc. Nephrol. CJASN2 (6), 1332–1342. 10.2215/CJN.03951106

  • CrossRef
  • Google Scholar

• 27

  Colasanto M. Madigan S. Korczak D. J. (2020). Depression and inflammation among children and adolescents: a meta-analysis. J. Affect Disord.277, 940–948. 10.1016/j.jad.2020.09.025

  • CrossRef
  • Google Scholar

• 28

  COVID-19 Mental Disorders Collaborators (2021). Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the covid-19 pandemic. Lancet398 (10312), 1700–1712. 10.1016/S0140-6736(21)02143-7

  • CrossRef
  • Google Scholar

• 29

  Cukor D. Kimmel P. L. (2018). Treatment of depression in ckd patients with an ssri: why things don't always turn out as you expect. Clin. J. Am. Soc. Nephrol. CJASN13 (6), 943–945. 10.2215/CJN.14421217

  • CrossRef
  • Google Scholar

• 30

  Dam M. Weijs P. J. M. van Ittersum F. J. Hoekstra T. Douma C. E. van Jaarsveld B. C. (2022). Nocturnal hemodialysis leads to improvement in physical performance in comparison with conventional hemodialysis. Nutrients15 (1), 168. 10.3390/nu15010168

  • CrossRef
  • Google Scholar

• 31

  Dantzer R. O'Connor J. C. Freund G. G. Johnson R. W. Kelley K. W. (2008). From inflammation to sickness and depression: when the immune system subjugates the brain. Nat. Rev. Neurosci.9 (1), 46–56. 10.1038/nrn2297

  • CrossRef
  • Google Scholar

• 32

  Deng J. Zhou F. Hou W. Silver Z. Wong C. Y. Chang O. et al (2021). The prevalence of depression, anxiety, and sleep disturbances in covid-19 patients: a meta-analysis. Ann. N. Y. Acad. Sci.1486 (1), 90–111. 10.1111/nyas.14506

  • CrossRef
  • Google Scholar

• 33

  Duan D. Yang L. Zhang M. Song X. Ren W. (2021). Depression and associated factors in Chinese patients with chronic kidney disease without dialysis: a cross-sectional study. Front. Public Health9, 605651. 10.3389/fpubh.2021.605651

  • CrossRef
  • Google Scholar

• 34

  Duranton F. Cohen G. De Smet R. Rodriguez M. Jankowski J. Vanholder R. et al (2012). Normal and pathologic concentrations of uremic toxins. J. Am. Soc. Nephrol. JASN23 (7), 1258–1270. 10.1681/ASN.2011121175

  • CrossRef
  • Google Scholar

• 35

  Fan Li Sarnak M. J. Tighiouart H. Drew D. A. Kantor A. L. Lou K. V. et al (2014). Depression and all-cause mortality in hemodialysis patients. Am. J. Nephrol.40 (1), 12–18. 10.1159/000363539

  • CrossRef
  • Google Scholar

• 36

  Fang Z. Ye S. Lin X. (2020). Efficacy of caihushugansan Joint deanxit in the treatment of uremic patients with negative emotion and sleep behavior. World J. Sleep Med.7 (02), 237–238. 10.3969/j.issn.2095-7130.2020.02.021

  • CrossRef
  • Google Scholar

• 37

  Farrokhi F. Abedi N. Beyene J. Paul K. Jassal S. V. (2014). Association between depression and mortality in patients receiving long-term dialysis: a systematic review and meta-analysis. Am. J. Kidney Dis. Official J. Natl. Kidney Found.63 (4), 623–635. 10.1053/j.ajkd.2013.08.024

  • CrossRef
  • Google Scholar

• 38

  Feng J. Lu X. Wang S. Han L. (2022). The assessment of cognitive impairment in maintenance hemodialysis patients and the relationship between cognitive impairment and depressive symptoms. Seminars Dialysis35 (6), 504–510. 10.1111/sdi.13031

  • CrossRef
  • Google Scholar

• 39

  Foster F. G. Cohn G. L. McKegney F. P. (1973). Psychobiologic factors and individual survival on chronic renal hemodialysis. A two year follow-up. I. Psychosom. Med.35 (1), 64–82. 10.1097/00006842-197301000-00008

  • CrossRef
  • Google Scholar

• 40

  Gebrie M. H. Ford J. (2019). Depressive symptoms and dietary non-adherence among end stage renal disease patients undergoing hemodialysis therapy: systematic review. BMC Nephrol.20 (1), 429. 10.1186/s12882-019-1622-5

  • CrossRef
  • Google Scholar

• 41

  Gerogianni G. Kouzoupis A. Grapsa E. (2018). A holistic approach to factors affecting depression in haemodialysis patients. Int. Urology Nephrol.50 (8), 1467–1476. 10.1007/s11255-018-1891-0

  • CrossRef
  • Google Scholar

• 42

  Giglio J. Kamimura M. A. Lamarca F. Rodrigues J. Santin F. Avesani C. M. (2018). Association of sarcopenia with nutritional parameters, quality of life, hospitalization, and mortality rates of elderly patients on hemodialysis. J. Ren. Nutr.28 (3), 197–207. 10.1053/j.jrn.2017.12.003

  • CrossRef
  • Google Scholar

• 43

  Grigoriou S. S. Karatzaferi C. Giannaki C. D. Sakkas G. K. (2024). Emotional intelligence in hemodialysis patients: the impact of an intradialytic exercise training Program. Healthcare12 (9), 872. 10.3390/healthcare12090872

  • CrossRef
  • Google Scholar

• 44

  Grigoriou S. S. Karatzaferi C. Sakkas G. K. (2015). Pharmacological and non-pharmacological treatment options for depression and depressive symptoms in hemodialysis patients. Health Psychol. Res.3 (1), 1811. 10.4081/hpr.2015.1811

  • CrossRef
  • Google Scholar

• 45

  Grudet C. Malm J. Westrin A. Brundin L. (2014). Suicidal patients are deficient in vitamin D, associated with a pro-inflammatory status in the blood. Psychoneuroendocrinology50, 210–219. 10.1016/j.psyneuen.2014.08.016

  • CrossRef
  • Google Scholar

• 46

  Guenzani D. Buoli M. Caldiroli L. Carnevali G. S. Serati M. Vezza C. et al (2019). Malnutrition and inflammation are associated with severity of depressive and cognitive symptoms of old patients affected by chronic kidney disease. J. Psychosomatic Res.124, 109783. 10.1016/j.jpsychores.2019.109783

  • CrossRef
  • Google Scholar

• 47

  Guglielmi K. E. (2013). Women and esrd: modalities, survival, unique considerations. Adv. Chronic Kidney Dis.20 (5), 411–418. 10.1053/j.ackd.2013.05.003

  • CrossRef
  • Google Scholar

• 48

  Halen N. V. Cukor D. Constantiner M. Kimmel P. L. (2012). Depression and mortality in end-stage renal disease. Curr. Psychiatry Rep.14 (1), 36–44. 10.1007/s11920-011-0248-5

  • CrossRef
  • Google Scholar

• 49

  He H. Qin Q. Xu F. Chen Y. Rao S. Wang C. et al (2023). Oral polyphenol-armored nanomedicine for targeted modulation of gut microbiota-brain interactions in colitis. Sci. Adv.9 (21), eadf3887. 10.1126/sciadv.adf3887

  • CrossRef
  • Google Scholar

• 50

  He R. Tung T. H. Liu T. Chien C. W. (2021). A meta-analysis on the relationship between different dialysis modalities and depression in end-stage renal disease patients. Curr. Pharm. Des.27 (40), 4171–4178. 10.2174/1381612827666210521132737

  • CrossRef
  • Google Scholar

• 51

  Hedayati S. S. Bosworth H. B. Kuchibhatla M. Kimmel P. L. Szczech L. A. (2006). The predictive value of self-report scales compared with physician diagnosis of depression in hemodialysis patients. Kidney Int.69 (9), 1662–1668. 10.1038/sj.ki.5000308

  • CrossRef
  • Google Scholar

• 52

  Heissel A. Heinen D. Brokmeier L. L. Skarabis N. Kangas M. Vancampfort D. et al (2023). Exercise as medicine for depressive symptoms? A systematic review and meta-analysis with meta-regression. Br. J. Sports Med.57 (16), 1049–1057. 10.1136/bjsports-2022-106282

  • CrossRef
  • Google Scholar

• 53

  Hu C. Wang X. (2020). Observation on therapeutic effect of bushen shugan recipe for treatment of maintenance hemodialysis patients complicated with anxiety and depression. J. Guangzhou Univ. Trad. Chin. Med.37 (11), 2093–2098. 10.13359/j.cnki.gzxbtcm.2020.11.008

  • CrossRef
  • Google Scholar

• 54

  Hu Y. Zhao M. Wang H. Guo Y. Cheng X. Zhao T. et al (2023). Exosome-sheathed ros-responsive nanogel to improve targeted therapy in perimenopausal depression. J. Nanobiotechnol.21 (1), 261. 10.1186/s12951-023-02005-y

  • CrossRef
  • Google Scholar

• 55

  Jahan-Mihan A. Stevens P. Medero-Alfonso S. Brace G. Overby L. K. Berg K. et al (2024). The role of water-soluble vitamins and vitamin D in prevention and treatment of depression and seasonal affective disorder in adults. Nutrients16 (12), 1902. 10.3390/nu16121902

  • CrossRef
  • Google Scholar

• 56

  Jaremka L. M. Lindgren M. E. Kiecolt-Glaser J. K. (2013). Synergistic relationships among stress, depression, and troubled relationships: insights from psychoneuroimmunology. Depress. Anxiety30 (4), 288–296. 10.1002/da.22078

  • CrossRef
  • Google Scholar

• 57

  Jayakumar S. Jennings S. Halvorsrud K. Clesse C. Yaqoob M. M. Carvalho L. A. et al (2023). A systematic review and meta-analysis of the evidence on inflammation in depressive illness and symptoms in chronic and end-stage kidney disease. Psychol. Med.53 (12), 5839–5851. 10.1017/s0033291722003099

  • CrossRef
  • Google Scholar

• 58

  Johnson S. Dwyer A. (2008). Patient perceived barriers to treatment of depression and anxiety in hemodialysis patients. Clin. Nephrol.69 (3), 201–206. 10.5414/cnp69201

  • CrossRef
  • Google Scholar

• 59

  Juergensen P. H. Juergensen D. M. Wuerth D. B. Finkelstein S. H. Steele T. E. Kliger A. S. et al (1996). Psychosocial factors and incidence of peritonitis. Adv. Perit. Dial.12:196–198.

  • Google Scholar

• 60

  Kabra A. Garg R. Brimson J. Živković J. Almawash S. Ayaz M. et al (2022). Mechanistic insights into the role of plant polyphenols and their nano-formulations in the management of depression. Front. Pharmacol.13, 1046599. 10.3389/fphar.2022.1046599

  • CrossRef
  • Google Scholar

• 61

  Kalender B. Ozdemir A. C. Koroglu G. (2006). Association of depression with markers of nutrition and inflammation in chronic kidney disease and end-stage renal disease. Nephron. Clin. Pract.102 (3-4), c115–c121. 10.1159/000089669

  • CrossRef
  • Google Scholar

• 62

  Kaywan P. Ahmed K. Ibaida A. Yuan M. Gu B. (2023). Early detection of depression using a conversational ai bot: a non-clinical trial. PloS One18 (2), e0279743. 10.1371/journal.pone.0279743

  • CrossRef
  • Google Scholar

• 63

  Khaira A. Mahajan S. Khatri P. Bhowmik D. Gupta S. Agarwal S. K. (2012). Depression and marital dissatisfaction among Indian hemodialysis patients and their spouses: a cross-sectional study. Ren. Fail.34 (3), 316–322. 10.3109/0886022X.2011.647291

  • CrossRef
  • Google Scholar

• 64

  Kim D.-S. Kim S.-W. Gil H.-W. (2022). Emotional and cognitive changes in chronic kidney disease. Korean J. Intern. Med.37 (3), 489–501. 10.3904/kjim.2021.492

  • CrossRef
  • Google Scholar

• 65

  Kim J. K. Choi S. R. Choi M. J. Kim S. G. Lee Y. K. Noh J. W. et al (2014). Prevalence of and factors associated with sarcopenia in elderly patients with end-stage renal disease. Clin. Nutr.33 (1), 64–68. 10.1016/j.clnu.2013.04.002

  • CrossRef
  • Google Scholar

• 66

  Kim K. H. Lee M. S. Kim T.-H. Kang J. W. Choi T.-Y. Dong Lee J. (2016). Acupuncture and related interventions for symptoms of chronic kidney disease. Cochrane Database Syst. Rev.2016 (6), CD009440. 10.1002/14651858.CD009440.pub2

  • CrossRef
  • Google Scholar

• 67

  Kimmel P. L. Peterson R. A. Weihs K. L. Simmens S. J. Alleyne S. Cruz I. et al (1998). Psychosocial factors, behavioral compliance and survival in urban hemodialysis patients. Kidney Int.54 (1), 245–254. 10.1046/j.1523-1755.1998.00989.x

  • CrossRef
  • Google Scholar

• 68

  Kimmel P. L. Peterson R. A. Weihs K. L. Simmens S. J. Alleyne S. Cruz I. et al (2000). Multiple measurements of depression predict mortality in a longitudinal study of chronic hemodialysis outpatients. Kidney Int.57 (5), 2093–2098. 10.1046/j.1523-1755.2000.00059.x

  • CrossRef
  • Google Scholar

• 69

  Kimmel P. L. Peterson R. A. Weihs K. L. Simmens S. J. Boyle D. H. Verme D. et al (1995). Behavioral compliance with dialysis prescription in hemodialysis patients. J. Am. Soc. Nephrol. JASN5 (10), 1826–1834. 10.1681/ASN.V5101826

  • CrossRef
  • Google Scholar

• 70

  Kimmel P. L. Weihs K. Peterson R. A. (1993). Survival in hemodialysis patients: the role of depression. J. Am. Soc. Nephrol. JASN4 (1), 12–27. 10.1681/ASN.V4112

  • CrossRef
  • Google Scholar

• 71

  King-Wing Ma T. Kam-Tao Li P. (2016). Depression in dialysis patients. Nephrol. Carlt.21 (8), 639–646. 10.1111/nep.12742

  • CrossRef
  • Google Scholar

• 72

  Klein H. E. Benkert O. Berger S. Gröschl G. (1981). Psychometry of depression in patients undergoing haemodialysis. Arch. Fur Psychiatr. Und Nervenkrankh.230 (4), 339–349. 10.1007/bf00346105

  • CrossRef
  • Google Scholar

• 73

  Koo J. R. Yoon J. Y. Joo M. H. Lee H. S. Oh J. E. Kim S. G. et al (2005). Treatment of depression and effect of antidepression treatment on nutritional status in chronic hemodialysis patients. Am. J. Med. Sci.329 (1), 1–5. 10.1097/00000441-200501000-00001

  • CrossRef
  • Google Scholar

• 74

  Kurita N. Wakita T. Fujimoto S. Yanagi M. Koitabashi K. Suzuki T. et al (2021a). Hopelessness and depression predict sarcopenia in advanced ckd and dialysis: a multicenter cohort study. J. Nutr. Health Aging25 (5), 593–599. 10.1007/s12603-020-1556-4

  • CrossRef
  • Google Scholar

• 75

  Kurita N. Wakita T. Fujimoto S. Yanagi M. Koitabashi K. Suzuki T. et al (2021b). Hopelessness and depression predict sarcopenia in advanced ckd and dialysis: a multicenter cohort study. J. Nutr. Health and Aging25 (5), 593–599. 10.1007/s12603-020-1556-4

  • CrossRef
  • Google Scholar

• 76

  Lacson E. Bruce L. Li N.-C. Mooney A. Maddux F. W. (2014). Depressive affect and hospitalization risk in incident hemodialysis patients. Clin. J. Am. Soc. Nephrol. CJASN9 (10), 1713–1719. 10.2215/CJN.01340214

  • CrossRef
  • Google Scholar

• 77

  Lee C.-H. Giuliani F. (2019). The role of inflammation in depression and fatigue. Front. Immunol.10, 1696. 10.3389/fimmu.2019.01696

  • CrossRef
  • Google Scholar

• 78

  Leggat J. E. Bloembergen W. E. Levine G. Hulbert-Shearon T. E. Port F. K. (1997). An analysis of risk factors for withdrawal from dialysis before death. J. Am. Soc. Nephrol. JASN8 (11), 1755–1763. 10.1681/ASN.V8111755

  • CrossRef
  • Google Scholar

• 79

  Levy N. B. (2000). Psychiatric considerations in the primary medical care of the patient with renal failure. Adv. Ren. Replacement Ther.7 (3), 231–238. 10.1053/jarr.2000.8132

  • CrossRef
  • Google Scholar

• 80

  Levy N. B. Blumenfield M. Beasley C. M. Jr. Dubey A. K. Solomon R. J. Todd R. et al (1996). Fluoxetine in depressed patients with renal failure and in depressed patients with normal kidney function. Gen. Hosp. Psychiatry18 (1), 8–13. 10.1016/0163-8343(95)00073-9

  • CrossRef
  • Google Scholar

• 81

  Li Z. Liu B. Tong X. Ma Y. Bao T. Yue J. et al (2024). The association between sarcopenia and incident of depressive symptoms: a prospective cohort study. BMC Geriatr.24 (1), 74. 10.1186/s12877-023-04653-z

  • CrossRef
  • Google Scholar

• 82

  Liu C. H. Yeh M. K. Weng S. C. Bai M. Y. Chang J. C. (2017). Suicide and chronic kidney disease: a case-control study. Nephrol. Dial. Transplant.32 (9), 1524–1529. 10.1093/ndt/gfw244

  • CrossRef
  • Google Scholar

• 83

  Liu M. Hou T. Nkimbeng M. Li Y. Taylor J. L. Sun X. et al (2021). Associations between symptoms of pain, insomnia and depression, and frailty in older adults: a cross-sectional analysis of a cohort study. Int. J. Nurs. Stud.117, 103873. 10.1016/j.ijnurstu.2021.103873

  • CrossRef
  • Google Scholar

• 84

  Liu M. Zhang Y. Yang S. Wu Q. Ye Z. Zhou C. et al (2022). Bidirectional relations between depression symptoms and chronic kidney disease. J. Affect. Disord.311, 224–230. 10.1016/j.jad.2022.05.104

  • CrossRef
  • Google Scholar

• 85

  Liu W. Zhu Y. Liu Y. (2019). Effect of zhenyuan capsule on chronic heart failure and psychological disorder in hemodialysis patients. J. Shanxi Health Vocat. Coll.29 (05), 73–75.

  • Google Scholar

• 86

  Liu Y. Cui J. Cao L. Stubbendorff A. Zhang S. (2024a). Association of depression with incident sarcopenia and modified effect from healthy lifestyle: the first longitudinal evidence from the charls. J. Affect Disord.344, 373–379. 10.1016/j.jad.2023.10.012

  • CrossRef
  • Google Scholar

• 87

  Liu Y. Wang H. Sha G. Cao Y. Chen Y. Chen Y. et al (2024b). The covariant structural and functional neuro-correlates of cognitive impairments in patients with end-stage renal diseases. Front. Neurosci.18, 1374948. 10.3389/fnins.2024.1374948

  • CrossRef
  • Google Scholar

• 88

  Lopes A. A. Bragg J. Young E. Goodkin D. Mapes D. Combe C. et al (2002). Depression as a predictor of mortality and hospitalization among hemodialysis patients in the United States and europe. Kidney Int.62 (1), 199–207. 10.1046/j.1523-1755.2002.00411.x

  • CrossRef
  • Google Scholar

• 89

  Lu Y. Han M. Esmaeili Shahri E. Abbaspour S. Tayebee R. (2023). Delivery of anti-cancer and anti-depression doxepin drug by nickel oxide nanoparticles originated from the cressa nudicaulis plant extract. RSC Adv.13 (18), 12133–12140. 10.1039/d2ra07545h

  • CrossRef
  • Google Scholar

• 90

  Mafra D. Fouque D. (2014). Lower physical activity and depression are associated with hospitalization and shorter survival in ckd. Clin. J. Am. Soc. Nephrol. CJASN9 (10), 1669–1670. 10.2215/CJN.08400814

  • CrossRef
  • Google Scholar

• 91

  Mailloux L. U. Bellucci A. G. Napolitano B. Mossey R. T. Wilkes B. M. Bluestone P. A. (1993). Death by withdrawal from dialysis: a 20-year clinical experience. J. Am. Soc. Nephrol. JASN3 (9), 1631–1637. 10.1681/ASN.V391631

  • CrossRef
  • Google Scholar

• 92

  Mazza M. G. De Lorenzo R. Conte C. Poletti S. Vai B. Bollettini I. et al (2020). Anxiety and depression in covid-19 survivors: role of inflammatory and clinical predictors. Brain, Behav. Immun.89, 594–600. 10.1016/j.bbi.2020.07.037

  • CrossRef
  • Google Scholar

• 93

  McGrane I. R. Munjal R. C. Skauge S. L. Molinaro J. R. (2022). Successful electroconvulsive therapy after failed pharmacotherapies in an older female on hemodialysis with bipolar mania. Bipolar Disord.24 (5), 556–558. 10.1111/bdi.13188

  • CrossRef
  • Google Scholar

• 94

  Miller A. H. Raison C. L. (2016). The role of inflammation in depression: from evolutionary imperative to modern treatment target. Nat. Rev. Immunol.16 (1), 22–34. 10.1038/nri.2015.5

  • CrossRef
  • Google Scholar

• 95

  Miranda A. S. Cordeiro T. M. Soares T. M. D. S. L. Ferreira R. N. Silva A. C. S. E. (2017). Kidney-brain Axis inflammatory cross-talk: from bench to bedside. Clin. Sci.131 (11), 1093–1105. 10.1042/CS20160927

  • CrossRef
  • Google Scholar

• 96

  Mitrou G. I. Grigoriou S. S. Konstantopoulou E. Theofilou P. Giannaki C. D. Stefanidis I. et al (2013). Exercise training and depression in esrd: a review. Seminars Dialysis26 (5), 604–613. 10.1111/sdi.12112

  • CrossRef
  • Google Scholar

• 97

  Mohammadkhanizadeh A. Farnaz N. (2021). Investigating the potential mechanisms of depression induced-by covid-19 infection in patients. J. Clin. Neurosci. Official J. Neurosurg. Soc. Australasia91, 283–287. 10.1016/j.jocn.2021.07.023

  • CrossRef
  • Google Scholar

• 98

  Nadort E. Rijkers N. Schouten R. W. Hoogeveen E. K. Bos W. J. W. Vleming L. J. et al (2022). Depression, anxiety and quality of life of hemodialysis patients before and during the covid-19 pandemic. J. Psychosomatic Res.158, 110917. 10.1016/j.jpsychores.2022.110917

  • CrossRef
  • Google Scholar

• 99

  Natale P. Palmer S. C. Ruospo M. Saglimbene V. M. Rabindranath K. S. Strippoli G. F. (2019a). Psychosocial interventions for preventing and treating depression in dialysis patients. Cochrane Database Syst. Rev.12 (12), Cd004542. 10.1002/14651858.CD004542.pub3

  • CrossRef
  • Google Scholar

• 100

  Natale P. Palmer S. C. Ruospo M. Saglimbene V. M. Rabindranath K. S. Strippoli G.Fm (2019b). Psychosocial interventions for preventing and treating depression in dialysis patients. Cochrane Database Syst. Rev.12 (12), CD004542. 10.1002/14651858.CD004542.pub3

  • CrossRef
  • Google Scholar

• 101

  Nelson C. B. Port F. K. Wolfe R. A. Guire K. E. (1994). The association of diabetic status, age, and race to withdrawal from dialysis. J. Am. Soc. Nephrol. JASN4 (8), 1608–1614. 10.1681/ASN.V481608

  • CrossRef
  • Google Scholar

• 102

  Nguyen T. Shoukhardin I. Gouse A. (2019). Duloxetine uses in patients with kidney disease: different recommendations from the United States versus europe and Canada. Am. J. Ther.26 (4), e516–e519. 10.1097/MJT.0000000000000737

  • CrossRef
  • Google Scholar

• 103

  Noce A. Marrone G. Ottaviani E. Guerriero C. Di Daniele F. Pietroboni Zaitseva A. et al (2021). Uremic sarcopenia and its possible nutritional approach. Nutrients13 (1), 147. 10.3390/nu13010147

  • CrossRef
  • Google Scholar

• 104

  Ossareh S. Tabrizian S. Zebarjadi M. Joodat R. S. (2014). Prevalence of depression in maintenance hemodialysis patients and its correlation with adherence to medications. Iran. J. Kidney Dis.8 (6), 467–474.

  • Google Scholar

• 105

  Palmer S. C. Natale P. Ruospo M. Saglimbene V. M. Rabindranath K. S. Craig J. C. et al (2016). Antidepressants for treating depression in adults with end-stage kidney disease treated with dialysis. Cochrane Database Syst. Rev.2016 (5), CD004541. 10.1002/14651858.CD004541.pub3

  • CrossRef
  • Google Scholar

• 106

  Pan L. Xie W. Fu X. Lu W. Jin H. Lai J. et al (2021). Inflammation and sarcopenia: a focus on circulating inflammatory cytokines. Exp. Gerontol.154, 111544. 10.1016/j.exger.2021.111544

  • CrossRef
  • Google Scholar

• 107

  Pandi-Perumal S. R. Monti J. M. Burman D. Karthikeyan R. BaHammam A. S. Spence D. W. et al (2020). Clarifying the role of sleep in depression: a narrative review. Psychiatry Res.291, 113239. 10.1016/j.psychres.2020.113239

  • CrossRef
  • Google Scholar

• 108

  Pearce M. Garcia L. Abbas A. Strain T. Schuch F. B. Golubic R. et al (2022). Association between physical activity and risk of depression: a systematic review and meta-analysis. JAMA Psychiatry79 (6), 550–559. 10.1001/jamapsychiatry.2022.0609

  • CrossRef
  • Google Scholar

• 109

  Peirce J. M. Alviña K. (2019). The role of inflammation and the gut microbiome in depression and anxiety. J. Neurosci. Res.97 (10), 1223–1241. 10.1002/jnr.24476

  • CrossRef
  • Google Scholar

• 110

  Pereira R. A. Cordeiro A. C. Avesani C. M. Carrero J. J. Lindholm B. Amparo F. C. et al (2015). Sarcopenia in chronic kidney disease on conservative therapy: prevalence and association with mortality. Preval. Assoc. Mortal.30 (10), 1718–1725. 10.1093/ndt/gfv133

  • CrossRef
  • Google Scholar

• 111

  Poudel I. Annaji M. Wibowo F. S. Arnold R. D. Fasina O. Via B. et al (2022). Hispolon cyclodextrin complexes and their inclusion in liposomes for enhanced delivery in melanoma cell lines. Int. J. Mol. Sci.23 (22), 14487. 10.3390/ijms232214487

  • CrossRef
  • Google Scholar

• 112

  Raine A. Ling S. Streicher W. Liu J. (2022). The conduct and oppositional defiant disorder scales (codds) for disruptive behaviour disorders. Psychiatry Res.316, 114744. 10.1016/j.psychres.2022.114744

  • CrossRef
  • Google Scholar

• 113

  Reichsman F. Levy N. B. (1972). Problems in adaptation to maintenance hemodialysis. A four-year study of 25 patients. Archives Intern. Med.130 (6), 859–865. 10.1001/archinte.1972.03650060051009

  • CrossRef
  • Google Scholar

• 114

  Ren D. (2022). The effects of the xiaofeng zhiyang granules plus hemodialysis on uremia skin itching and its influence on calcium and phosphorus metabolism. Clin. J. Chin. Med.14 (01), 95–99. 10.3969/j.issn.1674-7860.2022.01.028

  • CrossRef
  • Google Scholar

• 115

  Santos D. G. M. D. Ferreira L. G. S. Pallone J. M. Ottaviani A. C. Santos-Orlandi A. A. Pavarini S. C. I. et al (2022). Association between frailty and depression among hemodialysis patients: a cross-sectional study. Sao Paulo Med. J. = Revista Paulista de Med.140 (3), 406–411. 10.1590/1516-3180.2021.0556.R1.14092021

  • CrossRef
  • Google Scholar

• 116

  Scirica B. M. Bohula E. A. Dwyer J. P. Qamar A. Inzucchi S. E. McGuire D. K. et al (2019). Lorcaserin and renal outcomes in obese and overweight patients in the camellia-timi 61 trial. Circulation139 (3), 366–375. 10.1161/CIRCULATIONAHA.118.038341

  • CrossRef
  • Google Scholar

• 117

  Semaan V. Noureddine S. Farhood L. (2018). Prevalence of depression and anxiety in end-stage renal disease: a survey of patients undergoing hemodialysis. Appl. Nurs. Res.43, 80–85. 10.1016/j.apnr.2018.07.009

  • CrossRef
  • Google Scholar

• 118

  Shulman R. Price J. D. Spinelli J. (1989). Biopsychosocial aspects of long-term survival on end-stage renal failure therapy. Psychol. Med.19 (4), 945–954. 10.1017/s0033291700005663

  • CrossRef
  • Google Scholar

• 119

  Silva Junior G. B. Daher E. F. Buosi A. P. Lima R. S. A. Lima M. M. Silva E. C. et al (2014). Depression among patients with end-stage renal disease in hemodialysis. Psychol. Health Med.19 (5), 547–551. 10.1080/13548506.2013.845303

  • CrossRef
  • Google Scholar

• 120

  Smith M. D. Hong B. A. Robson A. M. (1985). Diagnosis of depression in patients with end-stage renal disease. Comparative analysis. Am. J. Med.79 (2), 160–166. 10.1016/0002-9343(85)90004-x

  • CrossRef
  • Google Scholar

• 121

  Somoza-Moncada M. M. Turrubiates-Hernández F. J. Francisco Muñoz-Valle J. Gutiérrez-Brito J. A. Díaz-Pérez S. A. Aguayo-Arelis A. et al (2023). Vitamin D in depression: a potential bioactive agent to reduce suicide and suicide attempt risk. Nutrients15 (7), 1765. 10.3390/nu15071765

  • CrossRef
  • Google Scholar

• 122

  Suandika M. Chen S.-Y. Fang J.-T. Yang S. H. Tsai Y. F. Weng L. C. et al (2023). Effect of acupressure on fatigue in hemodialysis patients: a single-blinded randomized controlled trial. J. Integr. Complementary Med.29 (2), 111–118. 10.1089/jicm.2022.0644

  • CrossRef
  • Google Scholar

• 123

  Sudo N. Chida Y. Aiba Y. Sonoda J. Oyama N. Yu X. N. et al (2004). Postnatal microbial colonization programs the hypothalamic-pituitary-adrenal system for stress response in mice. J. Physiol.558 (Pt 1), 263–275. 10.1113/jphysiol.2004.063388

  • CrossRef
  • Google Scholar

• 124

  Taraz M. Khatami M. R. Dashti-Khavidaki S. Akhonzadeh S. Noorbala A. A. Ghaeli P. et al (2013). Sertraline decreases serum level of interleukin-6 (Il-6) in hemodialysis patients with depression: results of a randomized double-blind, placebo-controlled clinical trial. Int. Immunopharmacol.17 (3), 917–923. 10.1016/j.intimp.2013.09.020

  • CrossRef
  • Google Scholar

• 125

  Tian X. Xia X. Yu H. Chen H. Jiang A. Xin L. (2022). Cognitive dysfunction and its risk factors in patients undergoing maintenance hemodialysis. Neuropsychiatric Dis. Treat.18, 2759–2769. 10.2147/NDT.S380518

  • CrossRef
  • Google Scholar

• 126

  Tosi G. Duskey J. T. Kreuter J. (2020). Nanoparticles as carriers for drug delivery of macromolecules across the blood-brain barrier. Expert Opin. Drug Deliv.17 (1), 23–32. 10.1080/17425247.2020.1698544

  • CrossRef
  • Google Scholar

• 127

  van den Broek S. L. Shalgunov V. Herth M. M. (2022). Transport of nanomedicines across the blood-brain barrier: challenges and opportunities for imaging and therapy. Biomater. Adv.141, 213125. 10.1016/j.bioadv.2022.213125

  • CrossRef
  • Google Scholar

• 128

  van Dijk S. van den Beukel T. O. Kaptein A. A. Honig A. le Cessie S. Siegert C. E. et al (2013). How baseline, new-onset, and persistent depressive symptoms are associated with cardiovascular and non-cardiovascular mortality in incident patients on chronic dialysis. J. Psychosomatic Res.74 (6), 511–517. 10.1016/j.jpsychores.2013.03.001

  • CrossRef
  • Google Scholar

• 129

  Vangala C. Niu J. Montez-Rath M. E. Yan J. Navaneethan S. D. Winkelmayer W. C. (2020). Selective serotonin reuptake inhibitor use and hip fracture risk among patients on hemodialysis. Am. J. Kidney Dis. Official J. Natl. Kidney Found.75 (3), 351–360. 10.1053/j.ajkd.2019.07.015

  • CrossRef
  • Google Scholar

• 130

  Viggiano D. Wagner C. A. Martino G. Nedergaard M. Zoccali C. Unwin R. et al (2020). Mechanisms of cognitive dysfunction in ckd. Nat. Rev. Nephrol.16 (8), 452–469. 10.1038/s41581-020-0266-9

  • CrossRef
  • Google Scholar

• 131

  Vučković M. Radić J. Kolak E. Bučan Nenadić D. Begović M. Radić M. (2023). Body composition parameters correlate to depression symptom levels in patients treated with hemodialysis and peritoneal dialysis. Int. J. Environ. Res. Public Health20 (3), 2285. 10.3390/ijerph20032285

  • CrossRef
  • Google Scholar

• 132

  Wang J. Tong Z. Liu J. Shangguan J. Liu X. Li Z. et al (2020). Application of 1h-mrs in end-stage renal disease with depression. BMC Nephrol.21 (1), 225. 10.1186/s12882-020-01863-0

  • CrossRef
  • Google Scholar

• 133

  Wang Q. (2018). Effects of addition and subtraction suanzaoren decoction treatment on clinical symptoms and sleep quality for patients with maintenance hemodialysis complicated with depression. J. Sichuan Traditional Chin. Med.36 (09), 104–106.

  • Google Scholar

• 134

  Wang Y. Liu Y. Lian Y. Li N. Liu H. Li G. (2016). Efficacy of high-dose supplementation with oral vitamin D3 on depressive symptoms in dialysis patients with vitamin D3 insufficiency: a prospective, randomized, double-blind study. J. Clin. Psychopharmacol.36 (3), 229–235. 10.1097/jcp.0000000000000486

  • CrossRef
  • Google Scholar

• 135

  Widing L. Simonsen C. Flaaten C. B. Haatveit B. Vik R. K. Wold K. F. et al (2022). Premorbid characteristics of patients with dsm-iv psychotic disorders. Compr. Psychiatry115, 152310. 10.1016/j.comppsych.2022.152310

  • CrossRef
  • Google Scholar

• 136

  Wuerth D. Finkelstein S. H. Kliger A. S. Finkelstein F. O. (2003). Chronic peritoneal dialysis patients diagnosed with clinical depression: results of pharmacologic therapy. Semin. Dial.16 (6), 424–427. 10.1046/j.1525-139x.2003.16094.x

  • CrossRef
  • Google Scholar

• 137

  Xie Z. Tong S. Chu X. Feng T. Geng M. (2022). Chronic kidney disease and cognitive impairment: the kidney-brain Axis. Kidney Dis.8 (4), 275–285. 10.1159/000524475

  • CrossRef
  • Google Scholar

• 138

  Xiong J. Peng H. Yu Z. Chen Y. Pu S. Li Y. et al (2022). Daily walking dose and health-related quality of life in patients with chronic kidney disease. J. Ren. Nutr. Official J. Counc. Ren. Nutr. Natl. Kidney Found.32 (6), 710–717. 10.1053/j.jrn.2022.01.015

  • CrossRef
  • Google Scholar

• 139

  Xu D. Gao L.-N. Song X.-J. Dong Q. W. Chen Y. B. Cui Y. L. et al (2023). Enhanced antidepressant effects of bdnf-quercetin alginate nanogels for depression therapy. J. Nanobiotechnology21 (1), 379. 10.1186/s12951-023-02150-4

  • CrossRef
  • Google Scholar

• 140

  Yang C. Wang H. Zhao X. Matsushita K. Coresh J. Zhang L. et al (2020). Ckd in China: evolving spectrum and public health implications. Am. J. Kidney Dis. Official J. Natl. Kidney Found.76 (2), 258–264. 10.1053/j.ajkd.2019.05.032

  • CrossRef
  • Google Scholar

• 141

  Young B. A. Von Korff M. Heckbert S. R. Ludman E. J. Rutter C. Lin E. H. et al (2010). Association of major depression and mortality in stage 5 diabetic chronic kidney disease. General Hosp. Psychiatry32 (2), 119–124. 10.1016/j.genhosppsych.2009.11.018

  • CrossRef
  • Google Scholar

• 142

  Yu Qi (2019). Clinical study of tiaoxue shugan tang combined with western medicine for uremic hemodialysis depression with liver depression and spleen-kidney qi deficiency. New Chin. Med.51 (03), 169–172. 10.13457/j.cnki.jncm.2019.03.051

  • CrossRef
  • Google Scholar

• 143

  Yuan D. Kuan T. Ling H. Wang H. Feng L. Zhao Q. et al (2021). Serum metabolomics of end-stage renal disease patients with depression: potential biomarkers for diagnosis. Ren. Fail.43 (1), 1479–1491. 10.1080/0886022x.2021.1994995

  • CrossRef
  • Google Scholar

• 144

  Zhao W. Yujie H. Yin Y. D. X. Zhang P. Wang Y. Tian L. (2017). Clinical study on the treatment of depression in hemodialysis patients with combination of Chinese and western medicine. Acta Chin. Med.32 (08), 1523–1526. 10.16368/j.issn.1674-8999.2017.08.401

  • CrossRef
  • Google Scholar

• 145

  Zhu T.-T. Wang H. Gu H.-W. Ju L. S. Wu X. M. Pan W. T. et al (2023). Melanin-like polydopamine nanoparticles mediating anti-inflammatory and rescuing synaptic loss for inflammatory depression therapy. J. Nanobiotechnology21 (1), 52. 10.1186/s12951-023-01807-4

  • CrossRef
  • Google Scholar