Clinical Research Directory

THE EFFECTS OF CIRCADIAN RHYTHM-BASED PROGRESSIVE RELAXATION EXERCISES IN HEMODIALYSIS PATIENTS

The aim of this study is to determine the effect of Progressive Relaxation Exercise (PGE) applied according to the circadian rhythms of hemodialysis (HD) patients on symptom management, sleep quality, comfort and mental well-being levels and to examine the experiences of HD patients regarding PGE application. A sequential mixed method research design will be used in the study. The quantitative part of the study was planned as a randomized controlled double-blind experimental study. The qualitative part will be conducted as a qualitative research to be carried out with individual in-depth interview method in order to examine the opinions of the individuals in the intervention group regarding the 8-week PGE applied according to the circadian rhythm. In the collection of research data, the Introductory Information Form, Morningness-Eveningness Questionnaire (MEQ), Dialysis Symptom Index, Hemodialysis Comfort Scale - Version II, Pittsburg Sleep Quality Index (PSQI), Warwick-Edinburgh Mental Well-Being Scale (WEMIOÖ), Individual Follow-up Form, Progressive Relaxation Exercise Application Guideline (PGEUY) and In-Depth Interview Form with Individuals in the Intervention Group will be used.

Optimisation of Solute Removal and Water Usage in Paediatric Haemodialysis

Children receiving chronic haemodialysis are typically treated with dialysis machines designed for adult patients. As a result, some devices do not allow the ideal blood or dialysate flow rates to be set for paediatric use. In addition, the optimal dialysate-to-blood flow ratio for maximising solute removal while minimising water consumption remains poorly defined. The aim of this study is to quantify the dialyser extraction ratio and clearance across different dialysis modalities and a range of dialysate-to-blood flow ratios. Blood and dialysate samples are collected at the blood inlet, blood outlet, and dialysate outlet lines, and concentrations of various uraemic toxins-spanning a range of molecular weights-are measured to calculate solute clearances.

The Effectiveness of Education in Diabetic Hemodialysis Patients

Diabetes is a significant health problem affecting approximately half a billion people worldwide, reaching alarming levels. Diabetic foot ulcers are among the most common and serious complications of diabetes. Diabetes is the most common cause of end-stage renal failure, and diabetic nephropathy is identified as a major risk factor for foot ulcers and amputation. The health belief model is a model that explains behavior. Focusing on the necessary motivational resources for the development of positive health behaviors in individuals is crucial for positive patient outcomes in the education of diabetic hemodialysis patients. It is necessary for hemodialysis nurses to educate diabetic patients on foot care knowledge, improve foot care behaviors, and prevent the development of foot ulcers and lower extremity amputations. However, the lack of studies in the literature on nurse-led foot care education interventions based on the health belief model for diabetic patients undergoing hemodialysis constitutes the strength and unique aspect of this study. The research will be conducted using a randomized controlled pretest-posttest design.

AI-Integrated Mobile Education and Self-Management in Hemodialysis

This randomized controlled trial aims to evaluate the effectiveness of an Artificial Intelligence-supported mobile education application designed to enhance self-care behaviors, arteriovenous fistula (AVF) care practices, and key biochemical parameters among adult hemodialysis (HD) patients. Chronic Kidney Disease (CKD) and its most common renal replacement therapy, hemodialysis, impose a substantial physical, psychological, and socioeconomic burden on patients. HD patients frequently experience fatigue, pain, cramping, sleep disturbances, thirst and fluid restriction challenges, dietary limitations, AVF-related complications, and emotional distress. These difficulties highlight the importance of strengthening patients' self-care abilities and promoting active involvement in disease management. Despite the prevalence of mobile health (mHealth) technologies in chronic disease management, existing applications for HD patients remain limited, and none have integrated personalized artificial intelligence-based educational support. The absence of AI-driven patient education represents a significant gap in nursing science and digital health innovation. This project addresses that gap by developing and testing a structured, evidence-based mobile education program supported by artificial intelligence, designed specifically for HD patients. The study will enroll 76 eligible hemodialysis patients from Bitlis State Hospital and Bitlis Tatvan State Hospital. Participants will be randomly assigned to either the intervention group or the control group using simple randomization. The intervention group will receive access to the AI-supported mobile application for six weeks, which includes modules on kidney function, CKD and treatment options, symptom management, dietary adherence, fluid management, treatment adherence, and AVF care. Each module incorporates written content, videos, visuals, voice-supported reading features, and an integrated "Ask a Question" function allowing patients to communicate directly with the research team. The control group will receive routine clinical care without additional intervention. The artificial intelligence component will assist with content personalization, monitoring of patient engagement, data storage, automated reminders for non-active users, and supportive feedback based on learning progress and biochemical trends. The development of the mobile application will be guided by expert opinions from nephrology specialists, dialysis nurses, academicians, and dietitians. Readability of educational materials will be assessed using the Ateşman Readability Formula. A pilot study will be conducted prior to the trial to evaluate usability using the Web Analysis and Measurement Inventory (WAMMI). Data collection will include a Patient Identification Form, the Hemodialysis Arteriovenous Fistula Self-Care Behavior Scale, the Hemodialysis Self-Management Scale, and a Biochemical Parameters Tracking Form. Pre-test data will be collected before the intervention; post-test data will be collected at the end of the six-week intervention period. Biochemical parameters will include BUN, creatinine, albumin, potassium, phosphorus, hemoglobin, uric acid levels, Kt/V, and dry weight, obtained from routine clinical records without additional blood sampling. The primary outcomes will assess changes in self-care and self-management behaviors based on validated scales. Secondary outcomes will examine changes in biochemical parameters between the intervention and control groups. Data analysis will be performed using SPSS, employing descriptive statistics, normality testing, and appropriate statistical comparison tests, with significance set at p \< 0.05. Ethical approval will be obtained from the appropriate institutional ethics committee, and written informed consent will be secured from all participants. Data confidentiality will be ensured using encrypted login systems and secure storage processes. This trial is expected to contribute significantly to the scientific literature by being the first AI-supported mobile education intervention tailored for hemodialysis patients. Anticipated benefits include improved self-care behaviors, increased patient autonomy, reduced AVF complications, better adherence to dietary and fluid restrictions, and improved biochemical outcomes. Broader impacts of the project include the potential reduction of hospitalization rates, decreased healthcare costs, increased quality of life for HD patients, and the establishment of a digital model that can be adapted for other chronic disease populations. Ultimately, this study aims to demonstrate that integrating artificial intelligence with mobile health education can create a transformative approach to patient empowerment, clinical care, and chronic disease management within the field of nephrology and nursing.

Effect of Autogenic Training on Hemodialysis Patients

goal of this interventional study to investigate the effect of autogenic training on sleep disturbance , restless leg syndrome and fatigue on hemodialysis patient Is there any significant effect of autogenic training on restless leg syndrome, sleep disturbance and fatigue in patients with hemodialysis? The intervention will include structured autogenic training sessions, and outcomes such as sleep quality and RLS severity and fatigue will be evaluated after 8 weeks of autogenic training on hemodialysis patients .

The Effects of an App-based Acupressure on Alleviating Fatigue, Pruritus, and Sleep Quality Among Hemodialysis Patients

Objectives: To evaluate the effectiveness of an app-based self-guided acupressure intervention in alleviating fatigue and pruritus, and in improving sleep quality among hemodialysis patients. Design and subjects: The parallel randomized controlled trial will be employed in one hospital. Block randomization in a 1:1 ratio will be used to assign the patients to the intervention and control groups. It is estimated that 50 to 100 participants receiving hemodialysis will be recruited. Instrument: The demographic and health-related information questionnaire, the Post-dialysis Fatigue (PDF), 5-D Itch, and Pittsburgh Sleep Quality Index will be used in this study. Interventions: The intervention group will use an app-based self-guided acupressure program to do the acupressure by themselves once daily for 4 weeks. Participants in the control group will receive usual care and no other intervention. Data analysis: Both intention-to-treat and per-protocol analysis approaches will be performed. Generalized Estimating Equations (GEE) analysis will be used to assess the effectiveness of the interventions. Sensitivity analysis will be conducted to assess the impact of missing data on the treatment effect if necessary. Expected outcomes: Participants in the intervention group will know how to do the self-guided acupressure by themselves. If the intervention is effective, the App can be introduced to the hemodialysis patients who need it.

High Neutrophil-to-Lymphocyte Ratio and Patients With Hemodialysis

To explore the role of neutrophil-to-lymphocyte ratio ( NLR ) and platelet-to-lymphocyte ratio ( PLR ) in predicting mortality in hemodialysis (HD) patients.

The Effect of Arteriovenous Fistula Care Training Given to Hemodialysis Patients on Quality of Life, Comfort and Self-Care Behaviours

This study will be conducted to evaluate the effect of Arterio-Venous Fistula (AVF) care training given to hamodialysis patients on quality of life, comfort and self-care behaviours. Patient education is one of the practices that help patients to gain self-care behaviours as well as reducing the cost of health expenditures. Nurses are health professionals who play an important role in patient education. Nurses provide patient education by using different materials. These materials can sometimes be mobile phones, videos, web-based applications, sometimes face-to-face interviews with patients, brochures or written materials. In this study, a training programme for AVF care will be developed. In addition, it is expected that the AVF care training to be given to HD patients will increase the quality of life and comfort areas, and increase the awareness and well-being levels of patients in self-care behaviours. The effectiveness of the study will be expanded by presenting the results of the research as a paper in an international comprehensive congress. An article of the study will be published in a journal scanned in international indexes and will be included in the literature.