Abstract
BACKGROUND:
Due to the rapid rise of common risk factors such as diabetes and hypertension, chronic kidney disease (CKD) has become a public health concern around the world and it is linked to an increased risk of cardiovascular morbidity and mortality, as well as a significant reduction in Quality of life (QoL). This study was aimed to assess the preintervention QoL and biochemical parameters as well as determine the effectiveness of the dialysis compliance module on biochemical parameters and QoL among CKD patients.
MATERIALS AND METHODS:
The researcher adopted a pre- and post-test design to conduct a study among 130 CKD patients admitted to three dialysis units using a purposive sampling technique. The tools used in the present study were demographic and clinical proforma, medical outcomes study short questionnaire form 36 health survey (SF-36) and blood specimen for biochemical tests. The Statistical Package for Social Sciences 20 (SPSS 20) was used to analyze the data. Descriptive and inferential statistics were used in the data analysis.
RESULTS:
Among 130 patients with chronic kidney disease, 61 (46.2%) had aged above 50 years. Males 89 (68.46%) were more affected than females 41 (31.54%). A t-test was used to find the effectiveness of the compliance module. It shows that on QoL of CKD patients was improved after the administration of the compliance module.
CONCLUSION:
CKD has a profound effect on QoL, A better understanding of the problems that CKD patients face would allow providers to deliver more patient-centered care and improve the patient’s overall well-being.
Keywords: Biochemical parameters, chronic kidney disease, compliance module, hemodialysis, quality of life
Introduction
Chronic kidney disease has become a global public health issue due to the rapid rise of common risk factors such as diabetes and hypertension.[1] It has been stated that kidney disease is the most untreated chronic condition.[2] As a result, developing countries with limited resources will face a significant threat. CKD is linked to an increased risk of cardiovascular morbidity and mortality, as well as a significant reduction in quality of life (QoL).[1] Dialysis patients are subjected to a painful, long-term treatment and its complications, which have an impact on their quality of life and the quality of life of their families.[3,4]
The World Health Organization defines QoL as a person’s perception of their position in life in relation to their goals, expectations, standards, and concerns, as well as the culture and value systems in which they live. Physical health, psychological state, personal beliefs, social relationships, and a person’s relationship to salient features of their environment all influence it in a complex way. QoL must also be considered in the context of the patient’s cultural environment.[5]
Kidney disease is linked to a high rate of morbidity and mortality, emphasizing the importance of early detection and treatment. Due to the numerous etiologies and the assays’ ability to detect the disease at the earliest possible occurrence, determining the presence of kidney disease can be difficult. Prerenal, as with hypovolemia; intrinsic renal disease, such as diabetic nephropathy; and postrenal, as with benign prostatic hyperplasia, due to obstruction. To this end, a variety of biochemical markers, mostly found in blood and urine, can be used as indicators of renal function or injury.[6] Patients with chronic kidney disease have abnormal biochemical parameters. The evaluation of these parameters on a regular basis is beneficial in the treatment of these patient[7] Health-related Quality of Life (HQoL) is linked to a higher risk of progression to end-stage renal disease (ESRD) and it an important outcome measure such as mortality among ESRD patients. Because of its importance, research on HOoL in CKD has grown over time. HOoL is positively correlated with hemodialysis patients’ reported satisfaction with their personal health. Depression, high psychological distress, and psychiatric disorders, all of which are prevalent among CKD patients, are negative predictors of HQL in CKD.[8,9,10] Moreover, it is crucial to pay attention to CKD patients’ quality of life as some evidence shows that it is linked to medical outcomes such as reduced hospitalization and a lower mortality rate due to hospitalization. The lack of compliance with hemodialysis is one of the issues that has been reported among CKD patients. All patient behaviors (diet, fluids, and medications) aimed at following health care providers’ recommendations are referred to as compliance.[11]
The usefulness of predialysis education among pre-ESRD patients has been well investigated and proven to be effective; however, the group with end-stage failure is still understudied and disregarded despite improved patient outcomes.[12]
The assessment of QoL is an essential element of health care and helps suggest suitable measures to improve the QoL of patients with end-stage renal disease. Therefore, this study aimed to evaluate the effectiveness of the dialysis compliance module on the quality of life and biochemical parameters among CKD patients in the dialysis unit at Mangalore.
Materials and Methods
Study design and setting
This study adopted a quantitative approach with a one-group pre- and post-test design to evaluate the impact of a dialysis compliance module on the quality of life (QoL) and biochemical parameters of patients with chronic kidney disease (CKD). The study was conducted at Justice K. S. Hegde Charitable Hospital (KSHEMA), including its satellite centers in Karkala and Puttur, located in Mangalore, Karnataka, India. This tertiary care hospital is renowned for its specialized dialysis unit and comprehensive care for CKD patients. The single-group design was chosen to assess changes in QoL and biochemical outcomes before and after the intervention within the same cohort, ensuring consistency in participant characteristics.
Study participants and sampling
The sample size was calculated using the nmaster software, based on a standard deviation derived from prior studies and an anticipated effect size to achieve adequate statistical power. A minimum sample size of 130 participants was determined to be necessary for the study. Participants were selected based on specific inclusion and exclusion criteria. Eligible participants were adults aged 18–60 years diagnosed with CKD and undergoing hemodialysis at the study hospital. Exclusion criteria included patients with multiple organ failure, critically ill or unconscious patients, those uninterested in the counseling program, individuals with retroviral infections, hepatitis, or those preparing for kidney transplantation. This ensured a homogeneous sample suitable for evaluating the dialysis compliance module.
Data collection tools and techniques
Data were collected using three validated tools. Tool 1 was a demographic and clinical proforma capturing patient characteristics such as age, gender, and clinical history. Tool 2 consisted of the Medical Outcomes Study Short Form 36 Health Survey (SF-36), a widely used instrument to assess QoL across physical and mental health domains. Tool 3 involved biochemical analysis of blood samples to measure blood urea nitrogen (BUN), serum potassium, serum albumin, hemoglobin, serum phosphorus, calcium, sodium, and creatinine levels. The dialysis compliance module, comprising a video, pamphlet, flip chart, and tailored diet plan, was administered to all participants for one week. Patients were encouraged to review the materials and clarify doubts. Blood samples were collected at baseline and subsequently on the 30th, 60th, 120th, and 150th days to monitor biochemical changes. A post-test using the SF-36 was conducted after six months to reassess QoL, with participants requiring approximately 40 minutes to complete the questionnaire.
Ethical considerations
Ethical clearance was obtained from the Central Ethics Committee of Nitte (Deemed to be University), Deralakatte, under reference number NU/CEC/2017-2018/0142, prior to study commencement. Written informed consent was secured from each participant or their legally acceptable representative before enrollment. A participant information sheet was provided to explain the study’s purpose, procedures, and voluntary nature. Confidentiality of personal and clinical data was maintained throughout the study, adhering to ethical guidelines for human research.
Statistical analysis
Methods: Data were analyzed using SPSS version 20. Descriptive statistics, including means, standard deviations, and frequencies, were used to summarize patient characteristics, QoL scores from the SF-36, and biochemical parameters. To evaluate the effectiveness of the dialysis compliance module, repeated measures analysis of variance (ANOVA) was employed to assess changes in biochemical parameters over time. This statistical approach accounted for the longitudinal nature of the data, enabling the detection of significant differences in outcomes before and after the intervention. A P-value of less than 0.05 was considered statistically significant.
Results
A total of 130 enrolled patients. Out of that, 32.31% of patients were between 51 and 60 years of age. Most dialysis patients were males (68.5%) and 31.54% were female. According to the educational status majority, 44.6% had completed primary school education, whereas 35.4% had high school education. Only 0.7% patients had postgraduation education. Analysis of marital status revealed that most dialysis patients (73.1%) were married, and 25.4% were unmarried. Most patients (49.2%) had an income of Rs. 5000–10,000 and 28.5% had an income less than 5000. As per the duration of dialysis, in most patients (53.1%) had a duration of 1–5 years, and only 5% had a duration of dialysis of 11–15 years?
Based on any history of systemic illness, the distribution of patients revealed that most dialysis patients (52.3%) had hypertension, and 38.5% had diabetes mellitus. Most patients (60.1%) were undergoing dialysis twice per week, and 21.6% were undergoing dialysis three times per week for treatment.
The present study results show that the overall preintervention QoL score was 79.45 ± 13.51, and the postintervention QoL score (82.46 ± 11.59) was slightly higher than the preintervention QoL score [Table 1].
Table 1.
The mean and standard deviation of pre- and postintervention QoL among CKD patients—domain wise
| Domains (n=130) | Preintervention QoL | Postintervention QoL | ||||||
|---|---|---|---|---|---|---|---|---|
|
|
|
|||||||
| Mean | SD | Mean | SD | |||||
| Vitality | 12.79 | 3.98 | 12.85 | 3.60 | ||||
| General health | 13.70 | 3.34 | 12.83 | 2.63 | ||||
| Physical function | 17.52 | 5.19 | 18.06 | 2.50 | ||||
| Role of physical health | 5.10 | 1.20 | 5.62 | 0.991 | ||||
| Body pain | 5.36 | 1.88 | 6.17 | 1.40 | ||||
| Mental health | 16.10 | 4.95 | 15.68 | 4.46 | ||||
| Social function | 5.12 | 1.27 | 5.67 | 1.27 | ||||
| Role in emotional problems | 3.76 | 0.99 | 4.32 | 1.25 | ||||
| Overall QOL | 79.45 | 13.54 | 82.46 | 11.59 | ||||
SD=Standard deviation, QoL=Quality of life
Table 2 shows the distribution of biochemical parameters among CKD patients. Around 96.9% patients had hemoglobin between 9–11 gm/dL. All the patients had creatinine levels between 0.5 and 1.4 mg/dL and urea levels between 10 and 50 mg/dL.
Table 2.
Frequency (f) and percentage (%) distribution of biochemical parameters among CKD patients
|
Table 3 shows that the calculated table value was (−0.774) and the P-value was < 0.001. Hence, the research hypothesis was accepted and concluded a significant difference between the mean pre- and post-test quality of life scores. Thus. The dialysis compliance module was effective in improving the quality of life of hemodialysis patients.
Table 3.
Effectiveness of dialysis compliance module on QOL and biochemical parameters among CKD patients
| QOL Domain (n = 130) | Mean | SD | t value | df | P | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| QOL-Pre | 79.74 | 13.51 | −0.774 | 129 | 0.441 | |||||||||
| QOL-Post | 82.46 | 13.78 | ||||||||||||
|
| ||||||||||||||
| Biochemical parameter (n=130) | Mean | SD | Sum of squares | Mean square | F value | P | ||||||||
|
| ||||||||||||||
| Hemoglobin | Pretest | 9.43 | 1.55 | 42.90 | 12.09 | 4.57 | 0.002* (Green) | |||||||
| Post-test 1 | 9.04 | 1.81 | 1200.55 | 2.64 | ||||||||||
| Post-test 2 | 9.24 | 1.57 | ||||||||||||
| Post-test 3 | 9.56 | 1.51 | ||||||||||||
| Post-test 4 | 9.74 | 1.41 | ||||||||||||
| Post-test 5 | 9.60 | 1.79 | ||||||||||||
| Creatinine | Pretest | 9.05 | 1.83 | 368.97 | 238.04 | 2.53 | 0.096 (Green house Geisser) | |||||||
| Post-test 1 | 9.99 | 2.86 | 18681.33 | 94.16 | ||||||||||
| Post-test 2 | 10.33 | 2.97 | ||||||||||||
| Post-test 3 | 11.41 | 11.83 | ||||||||||||
| Post-test 4 | 10.09 | 3.19 | ||||||||||||
| Post-test 5 | 10.26 | 3.29 | ||||||||||||
| Potassium | Pretest | 4.28 | 0.81 | 81.76 | 16.76 | 28.29 | 0.000* (Huynh-Feldt) | |||||||
| Post-test 1 | 5.09 | 0.80 | 367.05 | 0.59 | ||||||||||
| Post-test 2 | 5.19 | 0.75 | ||||||||||||
| Post-test 3 | 5.17 | 0.72 | ||||||||||||
| Post-test 4 | 5.17 | 0.84 | ||||||||||||
| Post-test 5 | 5.11 | 0.76 | ||||||||||||
| Urea | Pretest | 109.38 | 28.55 | 8710.72 | 1875.09 | 1.89 | 0.09 | |||||||
| Post-test 1 | 114.07 | 28.11 | 587100.15 | 987.35 | ||||||||||
| Post-test 2 | 114.87 | 27.66 | ||||||||||||
| Post-test 3 | 116.16 | 28.94 | ||||||||||||
| Post-test 4 | 110.18 | 31.59 | ||||||||||||
| Post-test 5 | 106.74 | 35.61 | ||||||||||||
*P<0.05: Significant difference
Repeated-measures ANOVA was used to find the effectiveness of the compliance module on biochemical parameters before intervention and subsequent observation after each month till the sixth month of postintervention [Table 4].
Table 4.
Friedman’s ANOVA
| Biochemical parameters | Mean Rank | Chi-Square | df | P | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Albumin | Pretest | 4.10 | 20.93 | 5 | 0.001* | |||||
| Post-test 1 | 3.57 | |||||||||
| Post-test 2 | 3.21 | |||||||||
| Post-test 3 | 3.48 | |||||||||
| Post-test 4 | 3.17 | |||||||||
| Post-test 5 | 3.47 | |||||||||
| Calcium | Pretest | 1.78 | 136.11 | 5 | 0.001* | |||||
| Post-test 1 | 3.81 | |||||||||
| Post-test 2 | 3.68 | |||||||||
| Post-test 3 | 3.95 | |||||||||
| Post-test 4 | 3.87 | |||||||||
| Post-test 5 | 3.91 | |||||||||
| Phosphorus | Pretest | 5.10 | 117.93 | 5 | 0.001* | |||||
| Post-test 1 | 3.29 | |||||||||
| Post-test 2 | 3.06 | |||||||||
| Post-test 3 | 3.19 | |||||||||
| Post-test 4 | 3.34 | |||||||||
| Post-test 5 | 3.02 | |||||||||
| Sodium | Pretest | 3.33 | 11.78 | 5 | 0.04 | |||||
| Post-test 1 | 3.52 | |||||||||
*P<0.05: Significant difference
Discussion
The higher prevalence of chronic kidney disease is attributed to rising rates of diabetes and hypertension (CKD). Many cardiovascular deaths take place in the shadows of CKD. ESRD is a well-noted public health issue, and since Type 2 diabetes mellitus and hypertension are predicted to climb in prevalence from 336 million in 2012 to 522 million in 2030, ESRD prevalence is also expected to rise.[4] The current study results show that most dialysis patients (52.31%) had hypertension, and 38.46% had diabetes mellitus.
Dialysis patients are a unique population in terms of treatment compliance due to a highly complicated treatment regimen that affects multiple aspects of their lives.[13] Due to the fact that hemodialysis is a long-term condition, people with renal failure must adjust numerous aspects of their lifestyle in order to manage their condition and its complications. Because of this, a patient’s QoL encompasses more than just their general state of health, such as the patient’s family and social status, medical and financial situation, and emotional health.[14]
The present study results shows that the overall pretest QoL score was 79.45 ± 13.54 the mean score of physical function domain 17.52 ± 5.19, followed by mental health 16.10 ± 4.95, general health 13.70 ± 3.34, vitality domain 12.79 ± 3.98, bodily pain 5.36 ± 1.88, social function 5.12 ± 1.27 role physical health 5.10 ± 1.20 and emotional problems 3.76 ± 0.99, whereas a study conducted by Kefale et al.[1] shows that the lowest scores were found in stage 5 CKD patients, except emotional role functioning in stage 4 (P = 0.005). Moreover, the results showing highest and least scores were emotional role functioning (78 ± 34.7) and bodily pain (59.3 ± 22.6) in stages 1 and 2, social functioning (68 ± 24.6) and physical role functioning (48.6 ± 40.4) in stage 3, mental health (55.6 ± 18.9), and physical role functioning (38.2 ± 40.2) in stage 4 and emotional role functioning (56.1 ± 45.6) physical role functioning (26.6 ± 40.4) in stage 5, respectively.
In the present study, the mean QoL in patients treated with hemodialysis was 79.74 ± 13.51 before intervention and 82.46 ± 13.78 after intervention. The mean QoL score of the individuals enrolled in the study conducted by Oliveira et al.[15] was (60.53 ± 14.10), whereas the reported mean total score was 48.73 ± 22.65.[16] In the current study mean quality of life after implementing the educational plan significantly increased and indicating that the provided education was effective. The various published literature suggested that it is essential to conduct self-care education programs, such as group teaching and counseling, to promote hemodialysis patients’ quality of life.[14,17,18]
The present study shows that the mean and SD of the potassium and albumin biochemical parameters were 4.27 ± 0.813 and 4.61 ± 1.4 during preintervention. Whereas calcium (6.0441 ± .697), phosphorus (9.0203 ± 507), hemoglobin (9.431.5 ± 5), creatinine (9.050 ± 1.83), blood urea (109.380 ± 28.55), and sodium (133.938 ± 0.59). The study was supported by another study by Bahadori et al. shows the mean and SD of the study patients’ laboratory test results before and after the intervention, i.e., sodium 140.18 ± 19.83 and 138.66 ± 4.66 (P < 0.001), potassium 7.49 ± 1.53 5.89 ± 1.92 (P < 0.001), phosphorus 5.69 ± 1.82 and 4.44 ± 1.66 (P < 0.001), calcium 9.19 ± 1.53 and 7.88 ± 1.38 (P < 0.001), sugar 126.59 ± 70.29 and 105.46 ± 37.11 (P < 0.001), hemoglobin 10.13 ± 1.32 and 11.35 ± 1.42 (P < 0.001), hematocrit 31.64 ± 4.59 and 35.56 ± 4.10 (P < 0.001), urea 122.87 ± 26.40 and 98.43 ± 28.05 (P < 0.001), creatinine 11.64 ± 5.99 and 9.22 ± 4.59.66.[18]
Durose et al. suggested that educating hemodialysis patients about nutrition, diet, and fluid intake could lead to fluid restriction and eventually weight loss.[19] Furthermore, it was suggested that hemodialysis service providers should have an ongoing quality-of-life assessment plan and implement appropriate measures as needed to improve it.[20] A study by Wiser et al.[21] show that patients in both groups had significantly improved albumin levels from prestudy to poststudy. Nutrition knowledge scores improved in the GNEP cohort but were not statistically significant. The GNEP had significantly improved composite scores on the SF-36 form preassessment to postassessment. There was no significant difference between the control and GNEP cohorts in any of the parameters measured. It shows that group education may be an effective and efficient method for providing nutrition education to hemodialysis patients.[22]
Research study states that a multidisciplinary and interdisciplinary approach consisting of a dialysis technician, nurse, doctor, nutritionist, physiotherapist, and clinical psychologist to plan and carry out an exercise program such as intradialytic exercise, dietetic tactics, yoga and meditation, and counseling for psycho emotional problems to prevent further deterioration of health status and improve quality of life among hemodialysis patients.[16]
Limitation and recommendation
This study was limited to hemodialysis patients willing to participate and fluent in the study language, using purposive sampling, limiting generalizability. Self-reported quality of life and coping data may reflect dialysis experiences without observational validation. Future studies should involve larger, diverse samples, explore other chronic illnesses, use multiple assessment tools, and apply qualitative methods to examine the physiological and psychological quality of life correlates in CKD patients.
Conclusion
CKD has a significant impact on diminishing the HQoL of patients. A better understanding of the issues would allow health care providers to provide more patient-centered care and improve the patient’s overall well-being. For example, QoL decreased in CKD patients in the early stages of the disease. In addition, patients with lower income and low hemoglobin levels were considered to have the worst quality of life in physical and mental component summaries.
Author’s contributions
STF, FD and NK: Study design. STF and NK: Data collection. STF, FD, NK and SM: Data analysis. STF, FD, NK, SM: Manuscript writing.
Conflicts of interest
There are no conflicts of interest.
Using Al
As the author, I confirm that this study was conducted without the use of AI tools. All data analysis, writing, and interpretations were performed by the research team, ensuring originality and adherence to ethical research standards
Acknowledgement
We thank Nitte (Deemed to be University), Deralakatte, Mangalore, for funding this study, and all participants for their cooperation. We also appreciate our colleagues’ valuable advice, which greatly contributed to this manuscript’s development.
Funding Statement
Nil.
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