Skip to main content
Download PDF

Drug-related problems and associated factors among patients with kidney dysfunction at a tertiary hospital in southwestern Uganda: a prospective observational study

BMC Nephrology volume 24, Article number: 375 (2023) Cite this article

Abstract

Background

Kidney dysfunction is a common, progressive condition that is increasingly becoming a global public health issue. Because the kidneys are the major route for drug excretion, impaired renal function can change the pharmacokinetics and pharmacodynamics of drugs that are renally excreted. Additionally, patients with kidney dysfunction often have co-morbidities and the associated use of multiple medications which increases the risk of drug-related problem (DRP) occurrence. This study aimed to determine the prevalence, types, and factors associated with DRPs in patients with kidney dysfunction.

Method

We conducted a prospective observational study over 3 months among hospitalized patients diagnosed with acute kidney injury or chronic kidney disease who were hospitalized in the medical ward, and patients attending the renal outpatient clinic at Mbarara Regional Referral Hospital. A total of 183 participants were enrolled through the use of a consecutive sampling technique. DRPs were classified according to the PCNE classification version 9.1. Data analysis was carried out using SPSS version 25.

Results

A total of 174 patients with kidney dysfunction were included in the study with a mean ± SD age of 50.34 ± 18.13 years. A total of 219 DRPs were incurred by 138 (79.3%) study participants. The most common DRPs were ‘Untreated symptoms or indication’ (35.6%) followed by ‘adverse event (possibly) occurring’ (28.3%), and ‘effect of drug treatment not optimal’ (23.3%). Antimicrobials were the most involved drugs in suboptimal drug treatment (31.3%) and unnecessary drug treatment (32.1%). The study showed that length of hospital stay ≥ 5 days (AOR = 6.39, 95% CI: 1.75–23.27; p-value = 0.005) significantly increased the risk of DRP occurrence.

Conclusion

The current results, in agreement with previous literature, showed a high burden of DRPs among patients with kidney dysfunction. Antimicrobials were the most involved drugs in suboptimal as well as in unnecessary drug treatment. Longer hospital stay significantly increased the risk of DRPs. The high prevalence of DRPs in patients with kidney dysfunction and the potential impact on antimicrobial resistance underscores the importance of regular medication reviews and close monitoring of patients with renal dysfunction.

Peer Review reports

Introduction

Kidney dysfunction is the inability of the kidneys to adequately filter toxins and waste products from the blood due to a reduction in the glomerular filtration rate. Functional abnormalities of the kidneys can be detected through various measures such as estimated glomerular filtration rate(eGFR), proteinuria/albuminuria, and urine output [1]. Kidney dysfunction is a common, progressive condition that is increasingly becoming a global public health issue [2, 3]. Kidney disease is the 10th leading cause of death worldwide accounting for 1.3 million deaths annually [4].

Over the last 30 years, the contribution of non-communicable diseases, particularly kidney dysfunction, to morbidity and mortality in Sub-Saharan Africa has increased [5]. A 2018 meta-analysis of 98,432 participants from 98 studies in Africa found a 15.8% overall prevalence of chronic kidney disease stages 1–5 [6], while a cross-sectional pilot study in Uganda found a high prevalence of proteinuria and a lower eGFR among urban Kampala residents, indicating some degree of kidney impairment [7].

Kidney dysfunction may present in several forms including acute kidney injury (AKI) or chronic kidney disease (CKD) both of which are significant global health challenges [8, 9]. Impaired kidney function can change the pharmacokinetics and pharmacodynamics of a drug that is largely removed by renal excretory systems. This results in the accumulation of toxic levels of the drug or its metabolites [10]. Comorbid conditions are also common in patients with kidney dysfunction, either as a cause or as a result of the dysfunction. Additionally, the management of kidney dysfunction is mostly based on long-term drug therapy to prevent disease progression, morbidity, and mortality [11]. This places patients with kidney dysfunction at a higher risk of encountering drug-related problems (DRPs) [12, 13].

According to Pharmaceutical Care Network Europe (PCNE), a DRP is “an event or circumstance involving drug therapy that actually or potentially interferes with desired health outcomes” [14]. DRPs have become common safety issues in hospitalized patients causing harm to the patient and increased healthcare costs in recent years [15, 16]. Kidney dysfunction is a significant risk factor for DRP occurrence not just because of the disease and its associated comorbidities, but also because of the medication use burden in these patients [11]. If not addressed DRPs may lead to poor health outcomes and disease progression in patients with kidney dysfunction [17].

Early detection and prevention of DRPs among patients with kidney dysfunction in developed countries has been made possible by the incorporation of clinical pharmacy services and the application of evidence-based guidelines [18, 19]. This has led to a comprehensive and interdisciplinary approach to identify, prevent and manage DRPs in these patients [19, 20]. In particular, pharmacist-led interventions have successfully identified and resolved DRPs in patients with kidney dysfunction [21]. The reduction of DRPs in patients with kidney dysfunction may improve the quality of life and reduce morbidity, mortality, and associated healthcare costs [22].

Although DRPs have been well-studied in patients with kidney dysfunction in high-income countries, there is a dearth of literature on the specific risk factors and impact of these problems in Sub-Saharan Africa. A few studies from these settings have identified varying prevalence rates of DRPs among CKD patients; 100% in Kenya [23], 78.6% in Ethiopia [24], and 70.03% in Nigeria [12]. These variations could be explained by differences in patient characteristics and healthcare practices.

This study aimed to assess the prevalence, types, and risk factors associated with DRPs in patients with kidney dysfunction at Mbarara Regional Referral Hospital (MRRH), using the PCNE classification tool.

Methods

Study design and setting

A prospective cross-sectional study was conducted among hospitalized patients with a confirmed diagnosis of AKI or CKD with eGFR of less than 60 mL/min/1.73m2 at the MRRH medical ward and renal clinic from October 2022 to January 2023. MRRH is a tertiary hospital and the largest referral center in southwestern Uganda, 280 km from the capital Kampala with a 350-bed capacity. The hospital serves a population of over four million people in its catchment area comprising 13 districts of southwestern Uganda. The medical in-patient ward has 50 beds and 300 patients are expected to be admitted each month. The hospital has a renal clinic which opened in 2011 and is part of the various units under the internal medicine department. There are currently two nephrologists and one nurse operating the clinic. The clinic offers outpatient services for patients with kidney diseases and conducts its operations once a week on a Monday. There is also a dialysis unit with seven dialysis machines that offer hemodialysis services to patients with end-stage renal disease (ESRD) and acute kidney injury.

Study participants

We included all patients of both genders aged 18 years and above admitted to the medical ward or attending the renal clinic of MRRH during the study period, with a confirmed diagnosis of AKI or CKD with eGFR of less than 60 mL/min/1.73m2, and willing to participate in the study. The eGFR was calculated using the CKD-EPI Creatinine Eq. (2021) [25]. Participants who were critically sick and unable to take an effective interview were excluded from this study.

Sample size

The sample size was calculated using Fisher’s formula [26] based on the estimated prevalence of 87% [16] and the assumptions of a 95% confidence interval, and a 5% margin of error. Thus, a sample size of 174 was required. By adding 5% non-response rate, the final computed sample size was 183 participants. A consecutive sampling technique was used during the study period and data collection continued until the sample size was achieved.

Data collection tools and procedures

A structured data collection tool was created based on carefully analyzed published articles in the literature. Part 1 of the tool is a questionnaire that was used to collect the patient’s sociodemographic and clinical characteristics, while part 2 is a data abstraction form that was used to collect disease, laboratory investigations, and drug-related data from the patient’s chart. The identified DRPs were then categorized using PCNE classification version 9.1 [14]. Discussions with treating physicians and residents provided further information and explanations on some patients’ medical information. Patients’ charts were also reviewed to obtain relevant disease and drug-related data. The clinical pharmacist through a review of the collected data and patient interaction was then able to evaluate for possible DRPs. The PCNE classification system version 9.1 was used primarily to categorize DRPs by problem type. While we also attempted to identify and categorize the causes of these problems where possible, our main focus was on the identification and categorization of the problems. The clinical pharmacists’ evaluations and recommendations were based on KDIGO guidelines for the management of AKI, CKD, comorbidities in AKI & CKD, and complications of AKI & CKD [27].

Data analysis

Data analysis was carried out using Statistical Package for Social Sciences (SPSS), version 25 (SPSS Inc., Cary, NC, USA). The sociodemographic and clinical characteristics of individuals were presented using descriptive statistics such as mean and percentages. The prevalence and types of DRPs are reported in percentages. We used binary logistic regression to determine the association between independent and dependent variables. Differences between variables with a p-value < 0.25 were adopted for multivariate analysis, and differences with a p-value < 0.05 were considered statistically significant.

Results

Participant enrolment

The study involved 183 adult participants and data from 9 of them was excluded due to incomplete or duplicate information. The final analysis was conducted on data from 174 participants.

Participants’ sociodemographic, clinical, and drug characteristics

The majority of the participants in this study were male 109 (62.6%) aged between 18 and 90 years with a mean ± SD of 50.3 ± 18.1 years. Only 27 (15.5%) participants reported a history of smoking while 79 (45.4%) reported an alcohol consumption history. About 112 (64.4%) participants were receiving five or more drugs and the majority of the participants 168 (96.6%) reported having received counseling on the use of their medication (Table 1).

Table 1 Sociodemographic and clinical characteristics of patients with kidney dysfunction at MRRH
Full size table

The most common comorbidity among the study participants was hypertension (46.6%) (Fig. 1) 19.5% had HIV, and 17.2% had diabetes mellitus (Table 1). The distribution of these chronic comorbidities also varied between patients with AKI and those with CKD as shown in Table 2. Anaemia 71 (35%) was the most common complication of kidney disease among the study participants followed by hyperkalemia 47 (23%) and hypertension 45 (22%) (Fig. 2).

Fig. 1
figure 1

Common comorbid conditions among patients with kidney dysfunction receiving care at MRRH. HIV = Human Immunodeficiency Virus *COPD, Malaria, Asthma, Pulmonary TB, Epilepsy, Hepatitis C, DVT, Brucellosis, medullary aplasia, Urinary Tract Infection, Esophagitis

Full size image
Table 2 Distribution of comorbidities across AKI and CKD
Full size table
Fig. 2
figure 2

Complications of kidney disease among patients with kidney dysfunction at MRRH. *Hypokalemia (2), Uremia (1), and Uremic gastropathy (1)

Full size image

Prevalence of drug-related problems

Out of 174 patients included, 138 participants had at least one drug-related problem making an overall prevalence of 79.3% (Fig. 3). The majority of the participants 80 (46.0%) had one DRP, 39 (22.4%) had two DRPs, and 19 (10.9%) had three or more DRPs.

Fig. 3
figure 3

Prevalence of drug-related problems among patients with kidney dysfunction at MRRH

Full size image

Types of drug-related problems among patients with kidney dysfunction at MRRH

A total of 219 DRPs were incurred by 138 patients; a mean of 1.26 DRPs per patient. ‘Untreated symptoms or indication’ was the most common DRP at 35.6%, followed by ‘adverse event (possibly) occurring’ at 28.3%, and ‘effect of drug treatment not optimal’ at 23.3% (Fig. 4). Several causes were identified for each type of DRP and presented in Table 3.

Fig. 4
figure 4

Types of drug-related problems identified among patients with kidney dysfunction at MRRH

Full size image
Table 3 Causes of the different DRPs identified among patients with kidney dysfunction at MRRH
Full size table

Medications used in the management of the study participants

Drugs used by the study participants are summarized in Fig. 5. The median number of drugs prescribed was 5 with an interquartile range of 4 to 7 drugs. The most commonly prescribed drugs among the study participants were antimicrobials 173, antihypertensives 171, supplements 135, and diuretics 118 respectively. Antimicrobial agents were the most involved drugs in DRPs ‘effect of drug treatment, not optimal’, ‘adverse event (possibly) occurring’, and ‘Unnecessary drug treatment’ as shown in Table 4.

Fig. 5
figure 5

Prescribed drugs among patients with kidney dysfunction at MRRH. *Adrenergics (5), Immunosuppressants (4), Antiepileptics (3), Antipsychotics (3) Cardiac glycosides (3), Cough and cold preparations (3), Antidepressants (2), Antihistamines (2), Albumin (2), Cardiac stimulants (2), Hormonal preparations (2), Antidiarrheals (1), Antigout preparations (1), Muscle relaxants (1)

Full size image
Table 4 Drugs involved with the different drug-related problems among patients with kidney dysfunction at MRRH
Full size table

Factors associated with drug-related problems

The association of independent variables with drug-related problems was investigated using both univariate and multivariate logistic regression techniques. In univariate logistic regression analysis, employment status (COR = 3.01, 95% CI: 0.79–11.48; p-value = 0.106), alcohol history (COR = 1.99, 95% CI: 0.81–4.91; p-value = 0.211), patients unable to afford prescribed medicine (COR = 5.93, 95% CI: 0.77–45.78; p-value = 0.088), HIV comorbidity (COR = 1.83, 95% CI: 0.78–4.28; p-value = 0.166), and length of hospital stay greater than 5 days (COR = 4.97, 95% CI: 1.63–15.10; p-value = 0.005) all had a p-value < 0.25 and were introduced into the multiple logistic regression.

One variable retained statistical significance in the multivariate analysis which is the length of hospital stay greater > = 5 days (AOR = 6.39, 95% CI: 1.75–23.27; p-value = 0.005) compared to 2 or fewer days (Table 5).

Table 5 Univariate and multivariate logistic regression of the factors associated with DRPs among patients with kidney dysfunction at MRRH
Full size table

Discussion

The current study identified a high prevalence (79.3%) of drug-related problems among patients with kidney dysfunction. This is comparable to that identified in studies conducted elsewhere: 89.2% in the United Arab Emirates [28], 70.3% in Nigeria [12], 78.6%, and 82.3% in Ethiopia [24, 29].

However, the current prevalence is considerably lower than 100% in Kenya [23] and 100% in Indonesia [30]. This discrepancy in these two findings could be attributed to the fact the studies were conducted only in CKD patients while our study included both CKD and AKI patients. DRPs are more prevalent in CKD patients because of long-term therapy to manage disease progression and associated complications [11]. Additionally, the study in Indonesia had more than 80% of the participants in stage 5 CKD in which patients are likely to have more complications and, therefore, require more drugs to manage these complications, thereby increasing the possibility of DRPs.

On the other hand, the current prevalence is much higher than that reported in other studies 41.63% in France [31], 51.35%, and 29.41% in India [32, 33]. This could be partly explained by the different study designs used and the characteristics of the participants in those studies. Savitha et al. (2020) and Mongaret et al. (2020) conducted interventional studies thereby helping to prevent the number of new DRPs as the study proceeded. The study by Joel et al. (2013) recruited only patients on hemodialysis while the current study recruited all patients with kidney dysfunction including those not on dialysis. Management of patients on hemodialysis usually involves strict adherence to treatment guidelines and this could explain the low prevalence of DRPs in their study [34].

‘Untreated symptoms or indication’ was the most common DRP (35.6%) which is similar to proportions reported in studies in Ethiopia (31%) and France (30%) [35]. However, ‘untreated symptoms or indication’ accounted for much lower proportions in other studies: 8.3% in Ethiopia [28], 8.6% and 13.6% in India [29, 36]. This difference can be explained by the different healthcare practices with some of the studies conducted in settings with better access to diagnostic equipment, medication, and stringent guidelines for the management of kidney dysfunction. This enables early detection and therefore treatment of symptoms or indications. The other possible explanation for the higher proportion of ‘untreated symptoms or indication’ in this study is its prospective nature where active follow-up of patients can reveal more untreated symptoms, unlike the cross-sectional study by Legesse et al. (2022). The most common untreated conditions were diseases of the blood or blood-forming organs (28.1%), followed by clinical findings of the genitourinary system (17.2%). Untreated conditions usually arise due to the failure of physicians to focus on minor patient disease conditions, such as low hemoglobin, headache, constipation, diarrhea, electrolyte abnormalities, and pain while treating other major conditions [36]. If left untreated, diseases of the blood or blood-forming organs like anemia can lead to an increased risk of cardiovascular disease, rapid progression of the disease, reduced quality of life, and increased hospitalizations in patients with kidney dysfunction [37].

‘Adverse drug event (possibly) occurring’, accounting for 28.3% of all DRPs, was the second most commonly encountered. These findings are consistent with those of a study in India, 19% of all DRPs were ADRs in patients with renal compromise [38]. Kidney dysfunction has previously been identified as a predictor of ADRs [39]. Patients with kidney dysfunction often take multiple medications, of which polypharmacy has also been attributed to the occurrence of ADEs [40]. However, this proportion is much higher compared to 7.07% in Ethiopia [29]. This could be explained by the tools used for data collection in this study. The PCNE classification tool is designed to also capture possible adverse drug events thereby increasing the proportion of ‘adverse drug event (possibly) occurring’. ‘Inappropriate drug according to the guidelines was the major cause of ‘adverse event (possibly) occurring’. Certain drugs are generally contraindicated in patients with kidney dysfunction while others are not recommended below certain eGFR levels because of their potential for rapid disease progress and their accumulation in the body leading to toxicity [10]. Additionally, ‘dosage regimen too frequent’ and ‘drug dose too high’ were also major causes of ‘adverse event (possibly) occurring’. This can be attributed to the failure to adjust doses for renally excreted drugs according to the eGFR levels of the patients. This presents an opportunity for health workers to pay more emphasis on drug doses during prescription in the management of patients with kidney dysfunction.

‘Effect of drug treatment not optimal’ accounted for approximately 23.3% of the identified drug-related problems. Suboptimal treatment may result in reduced effectiveness and thereby poor therapeutic outcomes, increased treatment costs, and disease resistance to drug treatment [41]. This particularly concerning given that antimicrobials were the most common drugs (31.3%) involved in suboptimal treatment as this may contribute to antimicrobial resistance. With the major causes of the ‘effect of drug treatment not optimal’ being incomplete drug treatment (27.8%) and low drug doses (24.1%), this presents an opportunity for healthcare workers involved in prescribing to pay more attention to treatment guidelines and appropriate medication doses.

‘Unnecessary drug treatment’ accounted for 10.2% of the total DRPs. This finding is in line with previous studies: 14.2% in Ethiopia [29], 12.8% in France [35], and 18% in Kenya [23]. Some of the causes of ‘unnecessary drug treatment’ include a lack of a clear indication for the drug, duplication of therapeutic groups, and medication reconciliation problems, among others. Antimicrobials were the most common drugs given unnecessarily (32.1%) and this could lead to the development of antibiotic resistance, increased healthcare costs, and potential adverse events to the patients.

The identification of risk factors for drug-related problems in patients with kidney dysfunction helps in the early detection and management of DRPs in high-risk individuals. This study showed that patients who stayed in the hospital for five or more days had 6.39 times higher odds of experiencing a DRP compared to those who stayed for two or fewer days. This is consistent with the findings of previous studies [42, 43]. This can be explained by the fact that longer hospital stay increases patients’ exposure to drugs, changes in regimen, medication errors, and adverse drug reactions [44]. Additionally, prolonged hospitalization may lead to physiological and health status changes in patients, such as bed sores and hospital-acquired infections, requiring additional medication to treat these conditions, thereby increasing the risk of DRP occurrence. Therefore, effective medication management and regular monitoring of patients during their hospital stay can help reduce the incidence of DRPs.

Despite the strengths, this study has some limitations. The study employed a consecutive sampling technique which involved selecting participants as they became available and this may limit the generalizability of the study findings.

Conclusion

The results of this study show a high burden of DRPs among patients with kidney dysfunction. Untreated indications and adverse events are the most frequent drug-related problems in this patient population. Additionally, antimicrobials are the most involved drugs in suboptimal drug treatment and unnecessary drug treatment posing a serious health challenge as a potential driver for antimicrobial resistance. Staying in the hospital for five or more days significantly increases the risk of drug-related problems among patients with kidney dysfunction. The high prevalence of DRPs in patients with kidney dysfunction and the potential impact on antimicrobial resistance underscores the importance of regular medication reviews and close monitoring of patients with renal dysfunction. Patients with renal dysfunction who stay longer in the hospital need to be closely monitored for prompt identification and management of DRPs.

Data availability

The data set and data collection tools used in this study are available upon reasonable request from the corresponding author.

Abbreviations

ADE:

Adverse Drug Event

ADR:

Adverse Drug Reaction

AKI:

Acute Kidney Injury

AOR:

Adjusted Odds Ratio

ATC:

Anatomical therapeutic chemical classification

CI:

Confidence interval

CKD:

Chronic Kidney Disease

COR:

Crude Odds Ratio

DRP:

Drug-Related Problem

eGFR:

estimated Glomerular Filtration Rate

ESKD:

End-Stage Kidney Disease

HIV:

Human Immunodeficiency Virus

ICD:

International Statistical Classification of Diseases

IQR:

Interquartile range

KDIGO:

Kidney Disease Improving Global Outcomes

MRRH:

Mbarara Regional Referral Hospital

MUST:

Mbarara University of Science and Technology

PCNE:

Pharmaceutical Care Network Europe

REC:

Research Ethics Committee

SD:

Standard deviation

SPSS:

Statistical Package for Social Sciences

References

  1. Levey AS, Levin A, Kellum JA. Definition and classification of kidney Diseases. Am J Kidney Dis. 2013;61:686–8.

    Article  PubMed  Google Scholar 

  2. Levey AS, Atkins R, Coresh J, Cohen EP, Collins AJ, Eckardt KU et al. Chronic kidney disease as a global public health problem: Approaches and initiatives - A position statement from Kidney Disease Improving Global Outcomes. Kidney Int [Internet]. 2007;72(3):247–59. https://doi.org/10.1038/sj.ki.5002343.

  3. Haileamlak A. Chronic Kidney Disease is on the rise. Ethiop J Health Sci. 2018;28(6):681–2.

    PubMed  PubMed Central  Google Scholar 

  4. World Health Organization. WHO - The top 10 causes of death [Internet]. 24 Maggio. 2020 [cited 2023 Mar 13]. p. 1–7. Available from: https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death.

  5. Matsha TE, Erasmus RT. Chronic kidney disease in sub-Saharan Africa. Lancet Glob Heal [Internet]. 2019;7(12):e1587–8. https://doi.org/10.1016/S2214-109X(19)30467-X.

  6. Kaze AD, Ilori T, Jaar BG, Echouffo-Tcheugui JB. Burden of chronic kidney disease on the African continent: A systematic review and meta-analysis [Internet]. BMC Nephrology. BioMed Central Ltd.; 2018. 2022;19:1–11. Available from: https://bmcnephrol.biomedcentral.com/articles/https://doi.org/10.1186/s12882-018-0930-5.

  7. Lunyera J, Stanifer JW, Ingabire P, Etolu W, Bagasha P, Egger JR, et al. Prevalence and correlates of proteinuria in Kampala, Uganda: a cross-sectional pilot study. BMC Res Notes. 2016;9(1):1–6.

    Article  Google Scholar 

  8. Hill NR, Fatoba ST, Oke JL, Hirst JA, O’Callaghan CA, Lasserson DS et al. Global prevalence of chronic kidney disease - A systematic review and meta-analysis [Internet]. PLoS ONE. Public Library of Science; 2016. 2021;11. p. e0158765. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0158765.

  9. Kerr M, Bedford M, Matthews B, O’donoghue D. The economic impact of acute kidney injury in England. Nephrol Dial Transplant. 2014;29(7):1362–8.

    Article  PubMed  Google Scholar 

  10. Pichai E, Lakshmanan M. Drug elimination. In: Introduction to Basics of Pharmacology and Toxicology: Volume 1: General and Molecular Pharmacology: Principles of Drug Action [Internet]. StatPearls Publishing; 2019 [cited 2022 Feb 18]. p. 117–29. Available from: https://www.ncbi.nlm.nih.gov/books/NBK547662/.

  11. Cardone KE, Bacchus S, Assimon MM, Pai AB, Manley HJ. Medication-related Problems in CKD. Adv Chronic Kidney Dis [Internet]. 2010 Sep 1 [cited 2022 May 19];17(5):404–12. https://doi.org/10.1053/j.ackd.2010.06.004.

  12. Adibe MO, Igboeli NU, Ukwe CV. Evaluation of drug therapy problems among renal patients receiving care in some tertiary hospitals in Nigeria. Trop J Pharm Res. 2017;16(3):697–704.

    Article  Google Scholar 

  13. Quintana-Bárcena P, Lord A, Lizotte A, Berbiche D, Lalonde L. Prevalence and management of drug-related problems in chronic Kidney Disease patients by severity level: a subanalysis of a cluster randomized controlled trial in community pharmacies. J Manag Care Spec Pharm. 2018;24(2):173–81.

    PubMed  Google Scholar 

  14. PCNE V9.1. Classification for Drug related problems V9.1. Pharm Care Netw Eur Assoc [Internet]. 2020;V 9.1:1–10. Available from: https://www.pcne.org/upload/files/334_PCNE_classification_V9-0.pdf.

  15. Adem F, Abdela J, Edessa D, Hagos B, Nigussie A, Mohammed MA. Drug-related problems and associated factors in Ethiopia: a systematic review and meta-analysis. J Pharm Policy Pract [Internet]. 2021 Dec 1 [cited 2021 Nov 16];14(1):1–24. https://doi.org/10.1186/s40545-021-00312-z.

  16. Alruqayb WS, Price MJ, Paudyal V, Cox AR. Drug-Related Problems in Hospitalised Patients with Chronic Kidney Disease: A Systematic Review [Internet]. Drug Safety. Springer; 2021 [cited 2021 Nov 29];44:1041–58. Available from: https://link.springer.com/article/https://doi.org/10.1007/s40264-021-01099-3.

  17. Westberg SM, Yarbrough A, Weinhandl ED, Adam TJ, Brummel AR, Reidt SL, et al. Drug Therapy Problem Severity Following Hospitalization and Association with 30-Day clinical outcomes. Ann Pharmacother. 2018;52(12):1195–203.

    Article  PubMed  Google Scholar 

  18. Roy DA, Shanfar I, Shenoy P, Chand S, Up N, Kc BR. Drug-related problems among chronic Kidney Disease patients: a clinical pharmacist led study. Int J Pharm Res. 2020;12(4):79–84.

    Google Scholar 

  19. Susilawati NM, Halimah E, Saidah S. Pharmacists’ strategies to detect, resolve, and prevent DRPs in CKD patients. Pharmacia. 2021;68(3):619–26.

    Article  Google Scholar 

  20. Salgado TM, Moles R, Benrimoj SI, Fernandez-Llimos F. Pharmacists’ interventions in the management of patients with chronic Kidney Disease: a systematic review. Nephrol Dial Transplant. 2012;27(1):276–92.

    Article  PubMed  CAS  Google Scholar 

  21. Manley HJ, Cannella CA, Bailie GR, St. Peter WL. Medication-related problems in ambulatory hemodialysis patients: A pooled analysis. Am J Kidney Dis [Internet]. 2005 Oct [cited 2021 Nov 19];46(4):669–80. Available from: https://pubmed.ncbi.nlm.nih.gov/16183422/.

  22. Haseeb A, Winit-Watjana W, Bakhsh ARR, Elrggal ME, Hadi MA, Mously AA et al. Effectiveness of a pharmacist-led educational intervention to reduce the use of high-risk abbreviations in an acute care setting in Saudi Arabia: A quasi-experimental study. BMJ Open [Internet]. 2016 Jun 1 [cited 2023 Apr 26];6(6). Available from: https://pubmed.ncbi.nlm.nih.gov/27311911/.

  23. Njeri LW, Ogallo WO, Nyamu DG, Opanga SA, Birichi AR. Medication-related problems among adult chronic kidney disease patients in a sub-Saharan tertiary hospital. Int J Clin Pharm [Internet]. 2018 May 1 [cited 2021 Nov 15];40(5):1217–24. Available from: https://link.springer.com/article/https://doi.org/10.1007/s11096-018-0651-7.

  24. Garedow AW, Mulisa Bobasa E, Desalegn Wolide A, Kerga Dibaba F, Gashe Fufa F, Idilu Tufa B et al. Drug-Related Problems and Associated Factors among Patients Admitted with Chronic Kidney Disease at Jimma University Medical Center, Jimma Zone, Jimma, Southwest Ethiopia: A Hospital-Based Prospective Observational Study. Int J Nephrol. 2019;2019.

  25. National Kidney Foundation. CKD-EPI Creatinine Eq, National Kidney Foundation. (2021) | National Kidney Foundation [Internet]. 2021 [cited 2023 Nov 27];241:2021–3. Available from: https://www.kidney.org/content/ckd-epi-creatinine-equation-2021.

  26. Sin‐Ho J. Stratified fisher’s exact test and its sample size calculation. Biom J. 2014;56(1):129–140. https://doi.org/10.1002/bimj.201300048.

  27. KDIGO. Guidelines | KDIGO [Internet]. 2018 [cited 2022 Feb 9]. Available from: https://kdigo.org/guidelines/.

  28. Shouqair TM, Rabbani SA, Sridhar SB, Kurian MT. Evaluation of Drug-Related Problems in Chronic Kidney Disease Patients. Cureus [Internet]. 2022 Apr 11 [cited 2023 Mar 15];14(4). Available from: http://www.pmc/articles/PMC9091809/.

  29. Legesse ES, Muhammed OS, Hamza L, Nasir BB, Nedi T. Medication related problems among ambulatory patients with chronic kidney disease at St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia. PLoS One [Internet]. 2022 Dec 1 [cited 2023 Mar 16];17(12 December). Available from: https://pubmed.ncbi.nlm.nih.gov/36455046/.

  30. Ramadaniati HU, Anggriani Y, Wowor VM, Rianti A. Drug-related problems in chronic kidneys Disease patients in an Indonesian hospital: do the problems really matter? Int J Pharm Pharm Sci. 2016;8(12):298–302.

    Article  Google Scholar 

  31. Mongaret C, Aubert L, Lestrille A, Albaut V, Kreit P, Herlem E et al. The Role of Community Pharmacists in the Detection of Clinically Relevant Drug-Related Problems in Chronic Kidney Disease Patients. Pharmacy [Internet]. 2020 May 22 [cited 2023 Mar 16];8(2):89. Available from: http://www.pmc/articles/PMC7355920/.

  32. Joel JJ, Shastry MMM. CS. A Study on Drug Related Problems and Pharmacist Intervention in Patients Undergoing Haemodialysis in a Tertiary Care Hospital. Int Res J Pharm Appl Sci (IRJPAS) [Internet]. 2013 Oct 31 [cited 2023 Mar 16];3(5):263–5. Available from: https://www.scienztech.org/index.php/irjpas/article/view/561.

  33. Savitha RS, Ramesh M, Shetty MS, Kiran KK. Drug-related problems and pharmacist interventions in inpatients with chronic Kidney Disease. Int J Res Pharm Sci. 2020;11(1):960–6.

    Article  CAS  Google Scholar 

  34. Kim H, Jeong IS, Cho MK. Effect of Treatment Adherence Improvement Program in Hemodialysis patients: a systematic review and Meta-analysis. Int J Environ Res Public Health. 2022;19(18).

  35. Belaiche S, Romanet T, Allenet B, Calop J, Zaoui P. Identification of drug-related problems in ambulatory chronic kidney disease patients: a 6-month prospective study. J Nephrol [Internet]. 2012 Sep [cited 2022 Feb 4];25(5):782–8. Available from: https://pubmed.ncbi.nlm.nih.gov/22322820/.

  36. Greeshma M, Lincy S, Maheswari E, Tharanath S, Viswam S. Identification of drug related problems by clinical pharmacist in prescriptions with polypharmacy: a prospective interventional study. J Young Pharm. 2018;10(4):460–5.

    Article  Google Scholar 

  37. Mathias SD, Blum SI, Sikirica V, Johansen KL, Colwell HH, Okoro T. Symptoms and impacts in anemia of chronic Kidney Disease. J Patient-Reported Outcomes. 2020;4(1).

  38. Castelino RL, Sathvik BS, Parthasarathi G, Gurudev KC, Shetty MS, Narahari MG. Prevalence of medication-related problems among patients with renal compromise in an Indian hospital. J Clin Pharm Ther [Internet]. 2011 Aug 1 [cited 2023 Mar 18];36(4):481–7. Available from: https://onlinelibrary.wiley.com/doi/full/https://doi.org/10.1111/j.1365-2710.2011.01266.x.

  39. Yadesa TM, Kitutu FE, Tamukong R, Alele PE. Predictors of hospital-acquired adverse drug reactions: a cohort of Ugandan older adults. BMC Geriatr [Internet]. 2022 Dec 1 [cited 2023 Mar 18];22(1):1–11. Available from: https://bmcgeriatr.biomedcentral.com/articles/https://doi.org/10.1186/s12877-022-03003-9.

  40. Shegena EA, Nigussie KA, Tamukong R, Lumori BAE, Yadesa TM. Prevalence and factors associated with adverse drug reactions among heart failure patients hospitalized at Mbarara Regional Referral Hospital, Uganda. BMC Cardiovasc Disord [Internet]. 2022 Dec 1 [cited 2023 Mar 18];22(1). Available from: https://pubmed.ncbi.nlm.nih.gov/36368954/.

  41. Belfrage B, Koldestam A, Sjöberg C, Wallerstedt SM. Prevalence of suboptimal drug treatment in patients with and without multidose drug dispensing - a cross-sectional study. Eur J Clin Pharmacol. 2014;70(7):867–72.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Prajapati A, Ganguly B. Appropriateness of drug dose and frequency in patients with renal dysfunction in a tertiary care hospital: A cross-sectional study. J Pharm Bioallied Sci [Internet]. 2013 [cited 2021 Dec 16];5(2):136–40. Available from: https://pubmed.ncbi.nlm.nih.gov/23833519/.

  43. Saleem A, Masood I, Khan TM. Clinical relevancy and determinants of potential drug&ndash;drug interactions in chronic kidney disease patients: results from a retrospective analysis. Integr Pharm Res Pract [Internet]. 2017 Feb [cited 2021 Dec 16];6:71–7. Available from: https://www.pmc/articles/PMC5774325/

  44. Hohl CM, Kuramoto L, Yu E, Rogula B, Stausberg J, Sobolev B. Evaluating adverse drug event reporting in administrative data from emergency departments: A validation study. BMC Health Serv Res [Internet]. 2013 Nov 12 [cited 2023 Mar 21];13(1):1–11. Available from: https://bmchealthservres.biomedcentral.com/articles/https://doi.org/10.1186/1472-6963-13-473.

Download references

Acknowledgements

Not applicable.

Funding

Not applicable.

Author information

Authors and Affiliations

  1. Department of Pharmacy, Faculty of Medicine, Mbarara University of Science and Technology, P. O. Box 1410, Mbarara, Uganda

    Julius Kyomya, Fredrick Atwiine, Efrata Ashuro Shegena & Tadele Mekuriya Yadesa

  2. Department of Internal Medicine, Faculty of Medicine, Mbarara University of Science and Technology, P. O. Box 1410, Mbarara, Uganda

    Rose Muhindo

  3. Department of Clinical Pharmacy and Pharmacy Practice, School of Pharmacy, Kampala International University, Ishaka, Uganda

    Tadele Mekuriya Yadesa

Authors
  1. Julius Kyomya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fredrick Atwiine
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Efrata Ashuro Shegena
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rose Muhindo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tadele Mekuriya Yadesa
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All the authors named in this manuscript have contributed greatly to this work and meet the criteria for authorship. J.K, R.M, and T.M.Y participated in research conceptualization, data collection, data analysis and interpretation, and manuscript writing/revision. F.A and E.A.S contributed towards data interpretation and manuscript writing/revision. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Julius Kyomya.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Research Ethics Committee of Mbarara University of Science and Technology with IRB number: MUST-2022-500. The hospital director of MRRH provided administrative clearance to conduct the study. Informed consent was sought from eligible participants before obtaining data from them. The informed consent tool was also translated into the local language Runyankole for participants who lacked literacy skills. This translated document was then read aloud to the study participants, who expressed their consent by using their thumbprints. In order to further ensure the accuracy of the consent process, literate family members/caregivers were actively involved as witnesses, confirming that the content of the consent form read aloud to the illiterate patient was correct. This procedure was approved by the Research and Ethics Committee of Mbarara University of Science and Technology.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kyomya, J., Atwiine, F., Shegena, E.A. et al. Drug-related problems and associated factors among patients with kidney dysfunction at a tertiary hospital in southwestern Uganda: a prospective observational study. BMC Nephrol 24, 375 (2023). https://doi.org/10.1186/s12882-023-03437-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12882-023-03437-2

Keywords

BMC Nephrology

ISSN: 1471-2369

Contact us