The concept of health-related quality of life (HRQoL) is complex and focuses on how patients' well-being is affected by their health. For individuals with end-stage renal disease (ESRD), a low HRQoL is associated with higher risks of mortality and hospitalization.1–8 Assessing HRQoL is crucial for evaluating treatment outcomes in chronic kidney disease (CKD) patients undergoing kidney replacement therapies (KRT). Various tools are being tested to improve patient outcomes by measuring HRQoL, which is significantly impacted by lifestyle changes, emotional disturbances, and physical and psychosocial symptoms.8–12

Kidney transplantation (KT) greatly improves HRQoL,9,13 with patients often achieving scores similar to those of healthy individuals.9 However, dialysis patients typically experience a compromised HRQoL, facing challenges similar to those with other chronic conditions like cancer and heart failure.2 While medications have improved health and HRQoL,14 their extensive use has also led to a rise in adverse side effects, known as negative outcomes associated with medications (NOM).15,16

Several factors influence HRQoL in ESRD patients, including country, ethnicity, and demographic characteristics. Studies on HRQoL have included patients undergoing hemodialysis (HD)3–5,12,17 or peritoneal dialysis (PD)3,6 across various countries.3,11 Understanding these factors can lead to better dietary, lifestyle, and educational recommendations, integrating HRQoL assessment into patient-centered care to enhance symptom relief, patient care, and rehabilitation.10,11

There is limited literature on HRQoL and NOM in KRT patients, with most studies focusing on the relationship between KRT modality and HRQoL.3,5,6,8–11 The present study aims to characterize HRQoL among KRT patients and explore the associated factors to provide a comprehensive understanding that can inform healthcare practices and patient management.

An observational study was conducted at the Nephrology Department of Virgen de las Nieves University Hospital in Granada, Spain. The research period extended from February 2, 2021, to July 31, 2023, spanning 29 months, and focused on patients with ESRD undergoing KRT.

All outpatient individuals who met the following criteria were included in the study: being over 18 years of age, undergoing KRT such as HD, PD, or KT at the nephrology department during the study period, and expressing a willingness to participate. Patients with cognitive impairments were excluded.

Eligible patients consulting the Nephrology Department at Virgen de las Nieves University Hospital were invited to participate. Informed consent was obtained from all participants, and variables were collected from medical records and through personal interviews. These interviews were used to gather information on HRQoL and symptoms not available in medical records. Patients meeting the inclusion criteria were recruited by nephrology experts.

HRQoL was assessed using the Kidney Disease Quality of Life Short Form (KDQOL-SF) Questionnaire, a 36-item tool specifically designed to evaluate quality of life in patients with chronic renal disease, including those undergoing dialysis. Although originally designed for dialysis patients, it has also been validated for use in transplant patients. The questionnaire includes domains such as the Physical Component Score (PCS), Mental Component Score (MCS), Symptoms and Problems of Kidney Disease (SPKD), Burden of Kidney Disease (BKD), and Effect of Kidney Disease (EKD). Scores were standardized on a scale from 0 to 100, with higher scores indicating better quality of life.18 Medication adherence was assessed using the Simplified Medication Adherence Questionnaire (SMAQ), a brief and reliable tool for evaluating adherence to medication regimens.19 Both questionnaires have been validated in the Spanish population.19,20

Data were collected using a combination of methods, including electronic medical record reviews, semi-structured interviews, and questionnaires administered through face-to-face interviews. The Dáder Method, developed by the Pharmaceutical Care Research Group at the University of Granada, was used to identify and classify DRP/ NOM according to the Granada Consensus.15 Pharmacists facilitated discussions with nephrology experts to ensure comprehensive data collection. The pharmacist conducted thorough reviews of electronic medical records and interviews to assess prescribed medications, baseline demographics, comorbidities, clinical laboratory data, allergies, and the number of NOM or DRP.

The stage of kidney disease was determined using the estimated glomerular filtration rate, calculated from serum creatinine levels using the Chronic Kidney Disease Epidemiology Collaboration equation, as documented in electronic medical records. Laboratory tests were recorded as part of routine clinical practice.

NOM were defined as health outcomes affecting the patients that are, or may be, associated with medication use. A DRP was defined as an event or circumstance involving drug therapy that interferes, or potentially interferes, with desired health outcomes.15

Statistical analyses were conducted at a 5% significance level using R software version 4.3.2 (©2023 The R Foundation for Statistical Computing, R Studio 2023.09.1 © 2009–2023 Posit Software, PBC). Microsoft Excel was used for data entry and preliminary editing before analysis. Descriptive statistics, including frequency distributions, percentages, means, standard deviations (SD), and medians, were calculated for continuous data.

The association between independent variables (clinical and demographic factors) and dependent variables (PCS or MCS) was explored using linear regression. Additionally, relationships between independent variables (clinical, demographic, PCS, or MCS) and the dependent variable (medication adherence) were assessed using univariate and multivariate logistic regression methods.

Institutional Review Board approval was obtained from the Andalusian Biomedical Research Ethics Committee (FIS-IRB-2020-01) on July 28, 2020. Written informed consent was obtained from all study participants, ensuring adherence to ethical standards and respect for participant autonomy.

A cohort of 91 out of 117 patients undergoing KRT was included in the study. Throughout the study period, five patients from the cohort passed away due to causes related to kidney disease or complications of their health conditions. The sociodemographic and clinical characteristics of the study population are shown in Table 1.

The main causes of ESRD were as follows: glomerulonephritis (26 cases; 28.57%), unknown etiology (20 cases; 21.98%), polycystic kidney disease (12 cases; 13.19%), and diabetic nephropathy (11 cases; 12.09%).

The principal comorbidities among the group of patients undergoing KRT were mineral and bone disorder (80 cases; 87.91%), anemia (81 cases; 89.01%), and hypertension (77 cases; 84.62%).

Overall, the group of patients used 1093 medications: 951 medications at home and 152 at the dialysis unit. Table 1 displays the principal types of medications used in the treatment of patients.

Overall, we identified 1875 NOM and 2578 DRP during the study period, with a rate of 20.6 NOM per patient and 28.3 DRP per patient. The principal types of NOM and DRP are presented in Table 1.

Table 2 shows the distribution of scores for the five components of KDQOL-SF.

Moreover, we examined the relationship between independent variables and dependent variable (PCS or MCS) through the application of linear regression method.

The linear regression analysis (Table 3) showed that factors such as number of comorbid conditions, number of medication administered in dialysis, SPKD, BKD, or Vitamin D (25OH) are associated with PCS.

Table 3 shows that factors such as calcium, age, number of medication administered at home, EKD, or SPKD are associated with MCS.

We examined the relationship between independent variables and the dependent variable (adherence to medications) using univariate and multivariate logistic regression methods.

The univariate logistic regression analysis showed that the PCS, number of medications, number of medications administered at home, albumin, and creatinine were associated with adherence to medications.

Variables with a p-value <0.05 in bivariate analysis were subsequently included in the multiple logistic regression. Table 4 shows the results of the multivariate analysis.

Furthermore, we examined the relationship between the type of KRT (KT or dialysis) and BKD or EKD (univariate logistic regression analysis). The BKD (OR = 1.024; 95%CI = 1.003–1.051; p < 0.05) and EKD (OR = 1.038; 95%CI = 1.004–1.088; p < 0.05) were found to be associated with the type of KRT.

The present study explores the HRQoL among individuals undergoing KRT and its associated factors, including NOM. HRQoL has emerged as a recommended clinical tool for evaluating patients on KRT, serving as a primary endpoint in various studies aimed at elucidating the effectiveness of comprehensive disease management.20

In the present study, low HRQoL was found within the sample, as evidenced by a mean PCS of 40.89 (SD: 9.02) and MCS of 47.19 (SD: 11.37). Our findings align with other studies that have reported low HRQoL among individuals with ESRD undergoing KRT.3,9,11,12

We found that the PCS and MCS exhibited the lowest scores, aligning with findings from a prior study11 that used the KDQOL-SF questionnaire. Specifically, the previously identified most affected dimensions, namely the PCS and the BKD, has also demonstrated significant impacts in our study. Notably, the dimension of SPKD consistently yielded the lowest scores, indicating a substantial degree of impairment in this specific facet of health-related QoL.11

Several factors were identified as contributors to these lower HRQoL scores. The PCS was associated with variables such as the number of comorbid conditions, the total number of medications administered during dialysis, the presence of SPKD, the BKD, and Vitamin D (25OH) levels.

Similarly, the MCS exhibited associations with factors including calcium levels, age, the number of medications administered at home, the EKD, and the manifestation of SPKD. These insights underscore the multifaceted nature of HRQoL in individuals undergoing KRT for ESRD and emphasize the importance of considering various health-related factors in assessing their well-being.

Previous research has indicated that factors such as depression, sleep quality, and lower calcium levels are associated with a negative impact on mental well-being.20

Furthermore, within this cohort of patients, we identified NOM, notably characterized by the prevalence of untreated health problems (98.9%) and quantitative ineffectiveness (95.6%), where the prescribed quantity or dosage of a medication was deemed insufficient. These findings are consistent with the existing literature, which consistently reports low HRQoL in patients with NOM.16

Patients undergoing KRT often experience high rates of undertreated conditions due to the complexity of their comorbidities, the primary focus on managing their kidney disease, and the overlap of symptoms which can lead to misattribution. Frequent healthcare visits, medication management challenges, and specialized provider focus contribute to gaps in holistic care. Additionally, logistical barriers, limited patient education, and psychosocial factors like depression further complicate comprehensive treatment. Improving care for these patients requires a multidisciplinary approach, better coordination among healthcare providers, and enhanced patient education to address both their renal and non-renal health needs effectively.11–13

Identifying specific patterns of NOM sheds light on critical aspects of healthcare delivery, emphasizing the imperative to address gaps in treatment and optimize medication regimens to enhance overall patient well-being.

Understanding the risk factors associated with poor HRQoL is crucial for identifying vulnerable ESRD patients and developing targeted interventions to support them. Determinants of HRQoL in ESRD extend beyond clinical factors to include mental factors. Importantly, these mental factors are potentially modifiable, presenting an opportunity for interventions addressing the physical and mental aspects of well-being in this patient population. This comprehensive approach holds promise for improving the overall QoL for individuals with ESRD.3

Our study revealed a significant association between vitamin D levels and the PCS, and between calcium levels and the MCS. These findings align with prior research investigating the relationship between laboratory values—such as hematocrit, potassium, phosphorus, and calcium—and patient attributes in the context of HRQoL.17,21

Some limitations of the present study include the relatively small sample size, which may hinder our ability to detect significant differences in the type of KRT and PCS or MCS. Additionally, the study design only allows us to establish associations between variables and prevents the identification of causal relationships.

In conclusion, our study reveals that patients undergoing KRT exhibit a low percentage of MCS and PCS scores as measured by the KDQOL-SF questionnaire and demonstrate instances of NOM.

Various factors emerge as significant contributors to HRQoL, including age, the prevalence of comorbid conditions, the quantity of medications administered during dialysis or at home, the manifestation of kidney disease symptoms, the overall burden of kidney disease, and clinical parameters such as vitamin D (25OH) and calcium levels.

Identifying these influencing factors underscores the complexity of HRQoL in KRT patients.

This study contributes to the existing body of knowledge on health-related quality of life and negative outcomes associated with medications in nephrology.

Recognizing the health-related quality of life among patients undergoing kidney replacement therapies and identifying the predominant influencing factors could pave the way for recommending healthy dietary practices, lifestyle adjustments, and educational interventions. Additionally, evaluating health-related quality of Life in individuals with end-stage renal disease is a valuable tool for healthcare professionals, integrating seamlessly into patient-centered care.

Financial support received as a Doctoral Grant [reference number OAICE-143-2020] from the Office of International Affairs and External Cooperation, University of Costa Rica.

Congress of the Andalucian Society of Nephrology, 2024. Organised by the Sociedad Andaluza de Nefrología. Location: Sevilla, Spain.

For Data supporting reported results contact corresponding author.

Alfonso Pereira-Céspedes: Writing – review & editing, Writing – original draft, Visualization, Validation, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Alberto Jiménez-Morales: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization. Aurora Polo-Moyano: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Conceptualization. Elizabeth Spruce-Esparza: Writing – review & editing, Writing – original draft, Investigation, Formal analysis. Magdalena Palomares-Bayo: Writing – review & editing, Writing – original draft, Validation, Supervision, Software, Project administration, Methodology, Formal analysis. Fernando Martínez-Martínez: Writing – original draft, Supervision, Resources, Project administration, Methodology, Investigation, Formal analysis, Conceptualization. Miguel Ángel Calleja-Hernández: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization.