Efficacy and safety of difelikefalin in the treatment of hemodialysis patients with pruritus: A meta-analysis and systematic review.

BACKGROUND: The incidence of pruritus associated with hemodialysis (HD) patients can be as high as 70%, and ~ 40% of patients suffer from moderate to severe systemic pruritus. Difelikefalin (CR845), a peripheral restrictor κ-opioid receptor agonist, activates opioid receptors on peripheral neurons and immune cells to relieve pruritus in patients. However, the clinical effect of difelikefalin on HD-related pruritus is unclear. Therefore, the purpose of this meta-analysis and systematic review was to investigate the safety and efficacy of difelikefalin in the treatment of HD-associated pruritus. OBJECTIVE: This study explored the efficacy and safety of difelikefalin in the treatment of pruritus in HD patients by systematic review and meta-analysis. MATERIALS AND METHODS: Randomized controlled trials on difelikefalin in the treatment of pruritus in HD patients were retrieved from PubMed, Embase, Cochrane Library, and Web of Science electronic databases. The retrieval deadline was January 1, 2023. Stata 15.0 software was used for data analysis of the included studies. RESULTS: A total of 4 randomized controlled trials were included, totaling 1,268 patients (736 patients in the experimental group and 532 patients in the control group). Results of the meta-analysis showed that, compared with the control group, difelikefalin could significantly improve the Worst Itch Numeric Rating Scale score (improvement > 3; risk ratio (RR) = 1.28, 95% confidence interval (CI) (1.07, 1.53)), decrease the 5-D itch score (standardized mean difference = -0.43, 95% CI (-0.55, -0.30)), and significantly improve adverse events (RR = 1.33, 95% CI (1.13, 1.56)). CONCLUSION: Although difelikefalin can improve itching symptoms in HD patients, it can also increase adverse reactions based on the current literature. Therefore, more studies are needed to further explore the safety and efficacy of difelikefalin treatment.

A machine learning-based assistant tool for early frailty screening of patients receiving maintenance hemodialysis.

PURPOSE: To develop an assistant tool based on machine learning for early frailty screening in patients receiving maintenance hemodialysis. METHODS: This is a single-center retrospective study. 141 participants' basic information, scale results and laboratory findings were collected and the FRAIL scale was used to assess frailty. Then participants were divided into the frailty group (n = 84) and control group (n = 57). After feature selection, data split and oversampling, ten commonly used binary machine learning methods were performed and a voting classifier was developed. RESULTS: The grade results of Clinical Frailty Scale, age, serum magnesium, lactate dehydrogenase, comorbidity and fast blood glucose were considered to be the best feature set for early frailty screening. After abandoning models with overfitting or poor performance, the voting classifier based on Support Vector Machine, Adaptive Boosting and Naive Bayes achieved a good screening performance (sensitivity: 68.24% ± 8.40%, specificity:72.50% ± 11.81%, F1 score: 72.55% ± 4.65%, AUC:78.38% ± 6.94%). CONCLUSION: A simple and efficient early frailty screening assistant tool for patients receiving maintenance hemodialysis based on machine learning was developed. It can provide assistance on frailty, especially pre-frailty screening and decision-making tasks.

Prevalence, associated factors and clinical implications of medication literacy linked to frailty in hemodialysis patients in China: a cross-sectional study.

BACKGROUND: Maintenance hemodialysis (MHD) patients have complex medication regimens that require a high level of skill to interpret medication information. However, there is currently a lack of research evaluating the ability to read and understand medication labels in Chinese MHD patients. In addition, the relationship between frailty and medication literacy among MHD patients remains unclear. Therefore, this study aims to assess the potential factors affecting medication literacy in MHD patients and to explore the relationship between frailty and medication literacy. METHODS: This cross-sectional study was conducted using convenience sampling in West China Hospital of Sichuan University, China. Using a general questionnaire, we collected demographic, clinical and laboratory data. Medication literacy was assessed by the Chinese Medication Literacy Scale, and frailty was assessed by the FRAIL Scale. Univariate analyses examined potential factors associated with medication literacy. An ordered logistic regression was used to analyze the relationships between medication literacy and these factors. Spearman's correlation was used to assess the association between medication literacy and frailty. RESULTS: A total of 290 MHD patients were included in the analysis. Inadequate, marginal, and adequate medication literacy was found in 56 (19.3%), 153 (52.8%), and 81 (27.9%) patients, respectively. Ordered logistic regression revealed factors associated with inadequate medication literacy: age (OR = 0.281, 95% CI = 0.139-0.565, p < 0.001 for < 65 years); education (OR = 8.612, 95% CI = 3.524-21.046, p < 0.001 for ≤ primary school education; OR = 3.405, 95% CI = 1.683-6.887, p = 0.001 for junior high school education); presence of caregiver medication assistance (OR = 2.302, 95% CI = 1.173-4.516, p = 0.015); frailty (OR = 0.440, 95% CI = 0.216-0.893, p = 0.023 for frail patients); and high ß2-microglobulin (ß2-MG) (OR = 1.010, 95% CI = 1.002-1.019, p = 0.012). Spearman's analysis showed that medication literacy was negatively correlated with frailty in MHD patients (R=-0.189, p = 0.001). CONCLUSIONS: Medication literacy levels in MHD patients needed improvement and were associated with certain patient characteristics, including age, education level, presence of caregiver support, ß2-microglobulin levels, and risk of frailty. This study identified subgroups of MHD patients, such as those who were older, had lower education, had caregiver assistance, had high ß2-microglobulin levels, or were frail, to have inadequate medication literacy. These findings underscore the need for routine screening and targeted interventions to improve medication literacy in this population.

Use machine learning to help identify possible sarcopenia cases in maintenance hemodialysis patients.

BACKGROUND: Maintenance hemodialysis (MHD) patients often suffer from sarcopenia, which is strongly associated with their long-term mortality. The diagnosis and treatment of sarcopenia, especially possible sarcopenia for MHD patients are of great importance. This study aims to use machine learning and medical data to develop two simple sarcopenia identification assistant tools for MHD patients and focuses on sex specificity. METHODS: Data were retrospectively collected from patients undergoing MHD and included patients' basic information, body measurement results and laboratory findings. The 2019 consensus update by Asian working group for sarcopenia was used to assess whether a MHD patient had sarcopenia. Finally, 140 male (58 with possible sarcopenia or sarcopenia) and 102 female (65 with possible sarcopenia or sarcopenia) patients' data were collected. Participants were divided into sarcopenia and control groups for each sex to develop binary classifiers. After statistical analysis and feature selection, stratified shuffle split and Synthetic Minority Oversampling Technique were conducted and voting classifiers were developed. RESULTS: After eliminating handgrip strength, 6-m walk, and skeletal muscle index, the best three features for sarcopenia identification of male patients are age, fasting blood glucose, and parathyroid hormone. Meanwhile, age, arm without vascular access, total bilirubin, and post-dialysis creatinine are the best four features for females. After abandoning models with overfitting or bad performance, voting classifiers achieved good sarcopenia classification performance for both sexes (For males: sensitivity: 77.50% ± 11.21%, specificity: 83.13% ± 9.70%, F1 score: 77.32% ± 5.36%, the area under the receiver operating characteristic curves (AUC): 87.40% ± 4.41%. For females: sensitivity: 76.15% ± 13.95%, specificity: 71.25% ± 15.86%, F1 score: 78.04% ± 8.85%, AUC: 77.69% ± 7.92%). CONCLUSIONS: Two simple sex-specific sarcopenia identification tools for MHD patients were developed. They performed well on the case finding of sarcopenia, especially possible sarcopenia.

Middle-size molecule clearance as measured by ß2-microglobulin in high-flux versus low-flux dialysis and hemodiafiltration: A prospective randomized controlled trial.

BACKGROUND: Whereas most studies to date have mainly concentrated on the comparison between high-flux hemodialysis (HFHD) and hemodiafiltration (HDF), or HFHD and low-flux hemodialysis (LFHD) in relation to the clearance of ß2-microglobulin (ß2M) in HD patients, there have been few related to combined HFHD and HDF therapy. To compare the clearance of middle-sized molecules as measured by ß2M in HFHD versus LFHD and HDF. METHODS: A prospective, single-center, open-label, observer-blinded, randomized controlled trial was conducted at the West China Hospital of Sichuan University in China. Patients received either HFHD or LFHD and HDF 3 times a week with follow-ups at one and 3 months. The primary endpoint was the clearance of ß2M at 3 months. The secondary endpoints included hemodialysis-related adverse events, changes in anemia, states of nutrition, and inflammatory indices. RESULTS: After 3 months of treatment, the HFHD+HDF group achieved a higher satisfaction level than the LFHD+HDF group, with decreased serum ß2M concentrations (34.493 ± 7.257 vs. 43.593 ± 9.036 mg/L, p < 0.001) and elevated red blood cell counts (3.959 ± 0.742 vs. 3.602 ± 0.578 × 1012 /L, p = 0.015). Compared with baseline, both kinds of treatment led to increases in serum urea (t = -3.623, p = 0.001 vs. t = -4.240, p < 0.001), cholesterol (t = -2.511, p = 0.016 vs. t = -4.472, p < 0.001), and magnesium (t = -2.648, p = 0.011 vs. t = -3.561, p = 0.001). An elevated level of serum albumin (t = -2.683, p = 0.010) was observed only in the HFHD+HDF group. CONCLUSIONS: Combined therapy with HFHD and HDF has a beneficial effect on improving ß2M clearance, red blood cell management, and nutrition status in HD patients.

Relationship between modifiable lifestyle factors and chronic kidney disease: a bibliometric analysis of top-cited publications from 2011 to 2020.

BACKGROUND: Chronic kidney disease (CKD) affects 8 to 16% of the world's population and is one of the top ten important drivers of increasing disease burden. Apart from genetic predisposition, lifestyle factors greatly contribute to the incidence and progression of CKD. The current bibliometric analysis aims to characterize the current focus and emerging trends of the research about the impact of modifiable lifestyle factors on CKD. METHODS: We searched articles addressing the impact of modifiable lifestyle factors on the incidence and/or progression of CKD, published between 2011 and 2020, from the Science Citation Index Expanded (SCIE) database. An adjusted citation index, which considered both the original citation count and publication year, was derived for the selection of most-cited publications. Publishing trends, co-authorship network, keywords, and research hotspots were analyzed and visualized. RESULTS: Among the top 100 most influential articles, 32 were narrative reviews, 16 systematic reviews and/or meta-analysis, 44 clinical research, and 8 basic research. The United States occupied a dominant position in the perspective of article numbers and international partnerships, followed by European countries. The modifiable factors that drew the most and constant attention over the decade were diet or nutrition management reported in 63 papers, followed by obesity or body mass index (n = 27), and physical activity or exercises (n = 8). Alcohol consumption, fish oil, chain fatty-acids, and water-soluble vitamins were emerging hotspots identified in the recent most cited publications. CONCLUSIONS: Based on the bibliometric analysis of the most influential articles, our study provides a comprehensive description of publishing trends and research focus over a decade in the field of lifestyle factors' impact on CKD. Diet, obesity, and physical activity were factors receiving the most attention in this topic.

Exploring psychosocial factors associated with frailty incidence among patients undergoing maintenance hemodialysis.

AIM AND OBJECTIVE: We investigated the correlation between the frailty status of maintenance haemodialysis (MHD) patients and psychosocial factors. BACKGROUND: Varying degrees of frailty have been reported in MHD patients, which affect their quality of life. DESIGN: We adopted a cross-sectional design in this study. METHODS: Clinical data of 187 patients at our centre were collected from December 2017-June 2018 using a cross-sectional survey. Psychosocial factors were measured using the Pittsburgh Sleep Quality Index (PSQI), Hospital Anxiety and Depression Scale, 10-item Connor-Davidson Resilience Scale (CD-RISC), Chronic Disease Self-Efficacy Scales and Perceived Social Support Scale. Frailty status was estimated using the fatigue, resistance, ambulation, illnesses and loss of weight (FRAIL) scale. Spearman's correlation and multiple logistic regression analysis were conducted to identify the risk factors for frailty. This study complied with the STROBE checklist. RESULTS: Of 187 patients, 11 cases (5.9%) of frailty were identified. Patient's age, comorbidities, parathyroid hormone level, sleep quality and depression were positively correlated with frailty (p < .05), while psychological resilience and social support were negatively correlated with frailty (p < .05). Logistic regression analysis revealed four risk factors for frailty among MHD patients, including age (p = .004), comorbidities (p = .023), depression (p = .023) and sleep disorders (p = .029). Conversely, protective factors included high psychological resilience (p = .019) and social support (p = .039). CONCLUSION: Among MHD patients, the risk factors for frailty included age, comorbidity, depression and sleep disturbance, whereas the protective factors included psychological resilience and social support. RELEVANCE TO CLINICAL PRACTICE: Frailty is not only common among older patients, but also among people of all age groups suffering from chronic diseases. Therefore, it is important to consider the health status of MHD patients and adopt targeted nursing strategies to alleviate symptoms of frailty and improve physical condition by the following ways: postpone the progress of comorbidities, improve sleep quality, control the symptoms of depression, foster psychological resilience and facilitate support from social and family.

The health-related quality of life among patients on maintenance haemodialysis: Evaluation using the "EQ-5D".

PURPOSE: We conducted a cross-sectional investigation of health-related quality of life (HRQOL) among maintenance haemodialysis (MHD) patients, and determined important predictive factors of HRQOL in these patients. METHODS: Psychological factors were evaluated with the Hospital Anxiety and Depression Scale (HADS), the Pittsburgh Sleep Quality Index (PSQI) and the General Self-Efficacy Scale (GSES). HRQOL was evaluated with the EQ-5D. Laboratory data (albumin, haemoglobin and C-reactive protein) were collected for medical evaluation. We also collected participants' demographic data, including gender, age, et al. This study was in compliance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. RESULTS: The mean EQ-5D score was 0.86 ± 0.12, mean HADS-anxiety score was 5.27 ± 3.41, mean HADS-depression score was 5.29 ± 3.58, mean PSQI score was 7.00 ± 4.23 and mean GSES score was 6.86 ± 2.03. Participants' mean haemoglobin was 108.18 ± 16.45 g/L, mean albumin was 41.80 ± 4.61 g/L and mean C-reactive protein was 8.88 ± 18.50 mg/L. HRQOL was negatively correlated with HADS-anxiety (r = -0.390, p < 0.001), HADS-depression (r = -0.385, p < 0.001), PSQI (r = -0.285, p < 0.001) and C-reactive protein (r = -0.198, p = 0.034). HRQOL was positively correlated with GSES (r = 0.205, p = 0.007). Age (p < 0.001), anxiety (p < 0.001), depression (p = 0.002), and postdialysis unemployment (p < 0.001) were independent risk factors for HRQOL. CONCLUSION: Different health interventions should be implemented to improve patients' HRQOL. RELEVANCE TO CLINICAL PRACTICE: The results will provide evidence for establishing healthcare interventions to maintain or improve HRQOL among this patient population.

Moderating Effects of Forgiveness on Relationship Between Empathy and Health-Related Quality of Life in Hemodialysis Patients: A Structural Equation Modeling Approach.

CONTEXT: Health-related quality of life (QOL) is a recommended clinical tool to assess hemodialysis patients and a primary end point to observe the effectiveness of overall disease management. Empathy is associated with positive outcomes such as pain relief and reduced anxiety and distress. Numerous studies have tested the relationships among empathy, forgiveness, and QOL; however, a mechanism of forgiveness has not been fully explored in hemodialysis patients. OBJECTIVES: To test the relationship among empathy and health-related QOL and confirm the moderating effects of forgiveness on relationship between empathy and health-related QOL among hemodialysis patients. METHODS: In a descriptive cross-sectional study conducted from September to December 2017, 457 hemodialysis patients from five hospitals filled out the Heartland Forgiveness Scale, Interpersonal Reactivity Index-C, Kidney Disease Questionnaire, and general information. The data were analyzed using SPSS, and structural equation modeling was used to address the relationships among empathy, forgiveness, and health-related QOL. RESULTS: Empathy was significantly positively associated with health-related QOL. The proposed model had a good fit to the data. Forgiveness was found to play a partial mediating role between empathy and health-related QOL. CONCLUSION: The results imply that empathy significantly directly and indirectly influences health-related QOL. Empathy among hemodialysis patients should be monitored and effectively managed to improve positive effects on their health-related QOL. Nurses should consider implementing empathy interventions with an emphasis on building forgiveness strategies to help hemodialysis patients improve their health-related QOL.