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Prevalence of polypharmacy and associated adverse health outcomes in adult patients with chronic kidney disease: protocol for a systematic review and meta-analysis



Polypharmacy, often defined as the concomitant use of ≥ 5 medications, has been identified as a significant global public health threat. Aging and multimorbidity are key drivers of polypharmacy and have been linked to a broad range of adverse health outcomes and mortality. Patients with chronic kidney disease (CKD) are particularly at high risk of polypharmacy and use of potentially inappropriate medications given the numerous risk factors and complications associated with CKD. The aim of this systematic review will be to assess the prevalence of polypharmacy among adult patients with CKD, and the potential association between polypharmacy and adverse health outcomes within this population.


We will search empirical databases such as MEDLINE, Embase, Cochrane Library, CINAHL, Web of Science, and PsycINFO and grey literature from inception onwards (with no language restrictions) for observational studies (e.g., cross-sectional or cohort studies) reporting the prevalence of polypharmacy in adult patients with CKD (all stages including dialysis). Two reviewers will independently screen all citations, full-text articles, and extract data. Potential conflicts will be resolved through discussion. The study methodological quality will be appraised using an appropriate tool. The primary outcome will be the prevalence of polypharmacy. Secondary outcomes will include any adverse health outcomes (e.g., worsening kidney function) in association with polypharmacy. If appropriate, we will conduct random effects meta-analysis of observational data to summarize the pooled prevalence of polypharmacy and the associations between polypharmacy and adverse outcomes. Statistical heterogeneity will be estimated using Cochran’s Q and I2 index. Additional analyses will be conducted to explore the potential sources of heterogeneity (e.g., sex, kidney replacement therapy, multimorbidity).


Given that polypharmacy is a major and a growing public health issue, our findings will highlight the prevalence of polypharmacy, hazards associated with it, and medication thresholds associated with adverse outcomes in patients with CKD. Our study will also draw attention to the prognostic importance of improving medication practices as a key priority area to help minimize the use of inappropriate medications in patients with CKD.

Systematic review registration

PROSPERO registration number: [CRD42020206514].

Peer Review reports


Polypharmacy, the concurrent use of multiple medications by an individual, is a significant and growing public health threat worldwide [1,2,3]. In 2017, the World Health Organization (WHO) highlighted polypharmacy as a key action to address unsafe medication practices and medication errors which are often associated with significant patient injury and preventable harm [1]. Globally, the prevalence of polypharmacy continues to increase, with estimates of 10–20% in the general population and 40–60% in the elderly [4,5,6]. There is no standard definition of polypharmacy; various definitions and related terms have been used (reviewed in detail by Masnoon et al.) [7]. Variability in the numerical threshold used in characterizing polypharmacy, as well as the reported inconsistencies regarding duration of therapy, healthcare setting, and inclusion of over-the-counter (OTC), and traditional and complementary medicines often creates challenges when defining polypharmacy [7]. Most studies, however, define polypharmacy as the concomitant use of ≥ 5 medications which is supported by evidence on medication-related adverse effects associated with polypharmacy [8].

Aging and multimorbidity are the key driving factors of polypharmacy [2, 3]. It is estimated that about half of individuals over the age of 65 years have at least three coexisting chronic conditions, and about 20% have five or more [ 9]. Given a rising burden of multimorbidity among the elderly, there is a corresponding increase in the amount of medication use in this group, thus increasing the prevalence of polypharmacy [2, 3]. In the USA, more than 4 in 10 older adults take 5 or more prescription medications daily—a marked rise of 300% from 1994 to 2014 [10]. This proportion increases to 7 in 10 older adults if OTC medications and supplements are counted [11] and nearly 20% of older adults take ≥ 10 drugs [10]. Similarly, the Canadian Institute for Health Information (CIHI) have reported that almost two-thirds of individuals aged 65 years and over used ≥ 5 drug classes, while 27% ≥ 10 and 8.6% used ≥ 15 [12]. Table 1 summarizes other driving forces of polypharmacy.

Table 1 Drivers of Polypharmacy and Various Associated Negative Consequences

Polypharmacy is associated with a broad range of adverse health outcomes, resulting in significant costs to both the patient and the healthcare system [13,14,15], with the risk and severity of harm increasing with an increasing number of medications [16]. Polypharmacy has also been strongly associated with adverse drug events (ADEs), adverse drug reactions (ADRs), drug-drug interactions, and drug-disease interactions [13,14,15]. In the USA, ADRs are estimated to claim between 100,000 and 218,000 lives annually and cost the healthcare system up to $137–177 billion [24]. The true incidence of ADRs are estimated to be much higher since underreporting is shown to be as high as 94% [25]. Studies have also shown that the risk of ADEs increases by up to 7–10% for each additional medication taken, and that outpatients using 5 or more medications have an 88% increased chance of experiencing an ADE compared to those taking less medications [26].

Polypharmacy has also been directly associated with mortality. In a systematic review that investigated the association between polypharmacy and mortality, a significant association between polypharmacy and death was observed when polypharmacy was defined as a discrete variable (pooled-adjusted odds ratio [aOR] 1.08 [95% CI 1.04–1.12]) [27]. When polypharmacy was defined categorically, a dose-response relationship was also observed across increasing thresholds of medications use, i.e., 1–4 medications [aOR 1.24]; 5 medications [aOR 1.31] and 6–9 medications [aOR 1.59]. Excessive polypharmacy (i.e., use of ≥ 10 medications) was also significantly associated with death [aOR 1.96] [27]. Other negative consequences associated with polypharmacy are also summarized in Table 1 [13,14,15,16,17,18,19,20,21,22,23].

An increasingly aging and multimorbid population has contributed to the rising prevalence of chronic kidney disease (CKD) [28, 29]. Individuals with CKD are highly vulnerable to polypharmacy given that CKD risk factors (e.g., diabetes mellitus and hypertension) and other cardiovascular diseases and risk factors are more prevalent in this population [30, 31]. Furthermore, patients with CKD require additional medications to limit the progression of CKD and manage disease-related complications (e.g., anemia, metabolic disorders, hyperlipidemia, mineral, and bone disorders) as kidney function deteriorates [32]. In CKD, all mechanisms of kidney excretion are impaired, including glomerular filtration, tubular secretion, and reabsorption. Since most drugs are largely eliminated through the kidneys, reduced kidney function causes a wide-ranging changes to the pharmacokinetic (drug absorption, distribution, metabolism, and excretion) and pharmacodynamic (drug-receptor interactions) properties of drugs thereby increasing the likelihood of potentially life-threatening toxicities, drug-drug interactions, and ADRs [33, 34]. The substantial burden of medications in individuals with CKD is well-documented, with studies showing that between 70.4–81% of patients with CKD take ≥ 5 medications [35, 36]. In a German study of 5217 patients with CKD, the prevalence of polypharmacy at baseline and follow-up was almost 80%, the median number of different medications per day was 8 (range 0–27), and factors associated with polypharmacy were increasing CKD stage, age, body mass index (BMI), diabetes mellitus, cardiovascular disease, and a history of smoking [35]. Another study found that 35.5% of older individuals with CKD took ≥ 10 medications, vitamins, and supplements [36].

Polypharmacy is also the main reason for potentially inappropriate medications (PIMs) use, with the number of PIMs increasing with the number of prescribed medications [37]. In individuals with CKD, numerous studies have revealed that PIM use as well as renally inappropriate medications use (RIMs) is common [36,37,38,39] and often overlooked [38, 39]. The prevalence of PIMs is estimated to be as much as 62–67% of patients in the inpatient and ambulatory care setting [40]. The recently published CKD-REIN study revealed that a large proportion of medications prescribed to patients with CKD were contraindicated, suggesting a lack of regular and/or thorough assessment of patients’ medication lists as kidney function declined [41].

The number of older persons is expected to have doubled by 2050 (reaching nearly 2.1 billion) [42], and this is likely to further increase the burden of multimorbidity and prevalence of individuals with CKD on polypharmacy [28]. Given the relationship between multimorbidity and CKD, and that such patients are at high risk of polypharmacy, PIMs, and adverse health effects associated with polypharmacy, this study will provide adequate information characterizing the burden of these conditions among patients with CKD. This will likely improve caution when prescribing medications for patients with CKD and reduce the frequency of adverse health effects related to polypharmacy in this population.

The aim of this systematic review will be to assess the prevalence of polypharmacy among adult patients with CKD, and the potential association between polypharmacy and adverse health outcomes within this population.


The present protocol has been registered within the PROSPERO database (registration number CRD42020206514) and is being reported in accordance with the guidance provided in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) statement [43] (see checklist in Additional file 1). The planned review will be reported according to the Preferred Reporting Items for Reporting Systematic Reviews and Meta-Analyses (PRISMA) 2020 Statement [44], and the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) reporting guideline [45].

Information sources and search strategies

The following databases will be searched from inception onwards with no language restriction: MEDLINE, Embase, Cochrane Library, CINAHL, Web of Science, and PsycINFO. The search strategy will be developed in consultation with a research librarian, the study investigators, and with guidance from the Cochrane handbook. We will also use a combination of controlled vocabulary search terms (i.e., Medical Subject Headings), and we will adapt the MEDLINE search strategy for the other databases. The draft search strategy for MEDLINE is provided in Additional file 2.

Reference lists of all relevant and selected publications will be searched manually to identify further studies. Conference abstracts and grey literature studies will also be considered from recommended resources in consultation with our medical librarian. As such, we will search ProQuest Dissertations & Theses Global, and Conference Proceedings Citation Index (Clarivate Analytics).

Criteria for considering studies for the review

Types of studies

Eligible studies will be observational studies (cohort, cross-sectional, or health surveys) reporting prevalence data of polypharmacy. Cross-sectional studies will be the most appropriate study design to determine the prevalence of polypharmacy. Cross-sectional health surveys are typically used to estimate the point prevalence of common conditions of long duration.

Types of participants

We will include studies with participants over 18 years of age, regardless of sex and ethnicity, across the spectrum of CKD (including those receiving kidney replacement therapy), and studies performed in in-patient and outpatient settings. We will exclude studies where the prevalence of polypharmacy cannot be computed as well as review articles, case reports, case studies, images, and other studies from which relevant data cannot be obtained even after attempting to contact the authors.

Exposure of interest

We will include studies that explored polypharmacy in patients with CKD and reported the prevalence of polypharmacy in their study setting with or without reporting the duration of therapy and/or healthcare setting (e.g., ambulatory care, hospitalization). We will define polypharmacy as the use of ≥ 5 medications (i.e., prescriptions, not pills, or dispensations) and excessive polypharmacy (hyperpolypharmacy) as use of ≥ 10 medications.

Types of outcome

The primary outcome will be the prevalence of polypharmacy (as described above). Secondary outcomes will include any adverse health outcomes in association with polypharmacy. Specifically, we will include studies that reported an association between polypharmacy and the following adverse health outcomes: kidney-related outcomes (such as episodes of acute kidney injury, worsening of estimated glomerular filtration rate [eGFR], initiation of dialysis, episodes of hyperkalemia), cardiovascular-related outcomes (such as fatal and non-fatal cardiovascular events), all-cause mortality, hospitalizations, drug-related outcomes (ADRs, ADEs, etc.), health-related quality of life (HRQoL), and other cognitive and physical decline outcomes.

Data collection and analysis

Study selection

A flow diagram showing details of studies included and excluded at each stage of the study selection process will be provided in the final review. We will adopt a 2-stage collaborative review process for screening and inclusion of studies. First, 2 investigators (MT and SM) will independently review the titles and abstracts of retrieved studies using the established study inclusion and exclusion criteria. Subsequently, full texts of the selected studies will be obtained and will be independently assessed by these reviewers for eligibility. If necessary, any discrepancies will be resolved by a third reviewer (IGO). For any excluded study, one of the predefined exclusion criteria will be recorded.

Data extraction and management

Two investigators will independently extract data from selected studies. The extracted data will be entered into a standardized form and will be reviewed for accuracy and completeness. Data elements from the selected studies will include first author, country, year of publication, study design, sample size, age, sex, CKD stages, and/or kidney function (i.e., serum creatinine and/or estimated glomerular filtration rate), number of comorbidities, duration of therapy, healthcare setting, mean/median number of medications, the article’s definition of polypharmacy, prevalence of polypharmacy, and adverse health outcomes reported. Reported adverse health outcomes will be grouped into ADRs, ADEs, or others and recorded as reported from the studies. Authors of the studies will be contacted for missing or additional data. If possible, we will calculate missing data using available information (e.g., imputation). All missing data will be reported in the data extraction form and risk of bias table.

Assessment of risk of bias

Methodological quality of the studies will be evaluated using the checklist developed by Hoy et al. [46] to assess the risk of bias from studies. This quality assessment tool incorporates assessments of risk of bias across core domains including sampling, the sampling technique and size, outcome measurement, response rate, and statistical reporting. The overall risk of bias for each study will be displayed in a risk of bias summary table.

Data synthesis

Study characteristics will be summarized in Tables and described in texts in the study manuscript.. The decision to perform a meta-analysis on the primary outcome (prevalence of polypharmacy) will depend on the assessment of statistical heterogeneity. If heterogeneity between studies is high (I2 > 50% and deemed to represent considerable heterogeneity), then data will be reported descriptively and we will provide a narrative synthesis of included studies using the Synthesis Without Meta-analysis (SWiM) reporting guideline as a framework [47]. If heterogeneity is acceptable, we will pool the study-specific estimates using a random-effects meta-analysis model (DerSimonian and Laird) to obtain an overall summary estimate of the prevalence of polypharmacy and rates of the secondary outcomes [48] [49].Heterogeneity among studies will be evaluated in relation to participant characteristics (e.g., comorbidities), number of medications, and types of adverse health outcomes (kidney-related/others). We will evaluate heterogeneity across studies by applying the χ2 test (p < 0.1 will indicate heterogeneity) and quantified using the I2 statistic (values of < 25%, 25–75%, and > 75% representing low, medium, and high heterogeneity, respectively) [50]. We will assess the presence of publication bias using funnel plots and Egger’s test [51].

Additional analyses

Subgroup analysis will be performed to investigate variations in prevalence data and potential sources of heterogeneity [49]. The following subgroups will be considered for further analyses: sex (males versus females), age groups: elderly and very elderly, study setting (in-patient versus outpatient settings), quality of study (low versus moderate versus high), patients on kidney replacement therapy (KRT) versus not receiving KRT, and multimorbidity (≤ 3 versus > 3). Significant results will be defined as p < 0.05.

Confidence in cumulative evidence

The quality of evidence for the primary outcome, i.e., prevalence of polypharmacy, will be assessed as “very low” to “high” in accordance to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Workgroup [52]. We will identify limitations of included studies and suggest improvement where possible.

Patient and public involvement

Given that this study is a systematic review, there will be no direct involvement of patients and public.

Ethics and dissemination

Ethical approval will not be required for this study as data used will be extracted from published studies. Results of this review will be published using traditional approaches including open-access peer-reviewed publications(s), presentations at relevant scientific conferences, reports, and lay summaries.


To the best of our knowledge, this review is the first to comprehensively assess the prevalence of polypharmacy in patients with CKD as well as reporting the incidence of adverse health outcomes associated with polypharmacy in such patients. As polypharmacy is a major and growing public health issue, our findings will highlight the hazards associated with polypharmacy as well as medication thresholds associated with adverse outcomes. Our study will also draw attention to the prognostic importance of improving medication practices as a key priority area to help minimize the use of inappropriate medications in patients with CKD. A potential limitation of this study could be non-uniform reporting of adverse outcomes and their associations with polypharmacy. This could make it difficult to identify adverse outcomes associated with use of medications in the CKD population. Another limitation could be that identified studies are mostly of low quality which could impact on the final reporting of our outcomes. Despite these, we expect that the results of this study will inform medication education, physician practice guidelines, and various quality improvement initiatives to address polypharmacy. Any amendments we make to this protocol when conducting the review will be outlined in PROSPERO and reported in the final manuscript.

Availability of data and materials

The datasets used and/or analyzed will be available from the corresponding author on reasonable request.



Adverse drug events


Adverse drug reactions


Body mass index


Canadian Institute for Health Information


Chronic kidney disease


Health-related quality of life


Over the counter


Potentially inappropriate medications

PRISMA-P 2015:

Preferred reporting items for systematic reviews and meta-analyses for protocols 2015


Renally inappropriate medications use


World Health Organization


  1. Donaldson LJ, Kelley ET, Dhingra-Kumar N, Kieny MP, Sheikh A. Medication without harm: who's third global patient safety challenge. Lancet. 2017;389(10080):1680–1.

    Article  PubMed  Google Scholar 

  2. Duerden M, Payne R, Avery T. Polypharmacy and medicines optimisation. King's Fund Report, November 2013; 2013.

    Google Scholar 

  3. Mair A, Wilson M, Dreischulte T. Addressing the challenge of polypharmacy. Annu Rev Pharmacol Toxicol. 2020;60(1):661–81.

    Article  CAS  PubMed  Google Scholar 

  4. Jokanovic N, Tan EC, Dooley MJ, Kirkpatrick CM, Bell JS. Prevalence and factors associated with polypharmacy in long-term care facilities: a systematic review. J Am Med Dir Assoc. 2015;16(6):535 e531–12.

    Article  Google Scholar 

  5. Kantor ED, Rehm CD, Haas JS, Chan AT, Giovannucci EL. Trends in prescription drug use among adults in the United States from 1999-2012. JAMA. 2015;314(17):1818–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Sarkar S. Geriatric poly-pharmacy: a growing epidemic. How to prevent it? Br J Med Med Res. 2017;21:1–11.

    Article  CAS  Google Scholar 

  7. Masnoon N, Shakib S, Kalisch-Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC geriatrics. 2017;17(1):230.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Gnjidic D, Hilmer SN, Blyth FM, Naganathan V, Waite L, Seibel MJ, et al. Polypharmacy cutoff and outcomes: five or more medicines were used to identify community-dwelling older men at risk of different adverse outcomes. J Clin Epidemiol. 2012;65(9):989–95.

    Article  PubMed  Google Scholar 

  9. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012;380(9836):37–43.

    Article  PubMed  Google Scholar 

  10. National Center for Health Statistics (US). Health, United States, 2016: With Chartbook on Long-term Trends in Health. Hyattsville: National Center for Health Statistics (US); 2017. Report No.: 2017-1232.

  11. Qato DM, Wilder J, Schumm LP, Gillet V, Alexander GC. Changes in prescription and over-the-counter medication and dietary supplement use among older adults in the United States, 2005 vs 2011. JAMA Intern Med. 2016;176(4):473–82.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Proulx J, Hunt J. Drug use among seniors on public drug programs in Canada, 2012. Healthcare Quarterly (Toronto). 2015;18(1):11–3.

    Article  Google Scholar 

  13. Wastesson JW, Morin L, Tan ECK, Johnell K. An update on the clinical consequences of polypharmacy in older adults: a narrative review. Expert Opin Drug Saf. 2018;17(12):1185–96.

    Article  PubMed  Google Scholar 

  14. Davies LE, Spiers G, Kingston A, Todd A, Adamson J, Hanratty B. Adverse outcomes of polypharmacy in older people: systematic review of reviews. J Am Med Dir Assoc. 2020;21(2):181–7.

    Article  PubMed  Google Scholar 

  15. Khezrian M, McNeil CJ, Murray AD, Myint PK. An overview of prevalence, determinants and health outcomes of polypharmacy. Ther Adv Drug Saf. 2020;11:2042098620933741.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Maher RL, Hanlon J, Hajjar ER. Clinical consequences of polypharmacy in elderly. Expert Opin Drug Saf. 2014;13(1):57–65.

    Article  PubMed  Google Scholar 

  17. Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: implications for pay for performance. JAMA. 2005;294(6):716–24.

    Article  CAS  PubMed  Google Scholar 

  18. Mangin D, Bahat G, Golomb BA, Mallery LH, Moorhouse P, Onder G, et al. International group for reducing inappropriate medication use & polypharmacy (IGRIMUP): position statement and 10 recommendations for action. Drugs Aging. 2018;35(7):575–87.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Garber J, Brownlee S. Medication overload: America's Other Drug Problem. In. Brookline: The Lown Institute; 2019.

    Book  Google Scholar 

  20. Garfinkel D, Ilhan B, Bahat G. Routine deprescribing of chronic medications to combat polypharmacy. Ther Adv Drug Saf. 2015;6(6):212–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Moffat K, Mercer SW. Challenges of managing people with multimorbidity in today’s healthcare systems. BMC Fam Pract. 2015;16(1):1–3.

    Article  Google Scholar 

  22. Ahn R, Woodbridge A, Abraham A, Saba S, Korenstein D, Madden E, Boscardin WJ, Keyhani S. Financial ties of principal investigators and randomized controlled trial outcomes: cross sectional study. BMJ. 2017;356:i6770.

  23. Norris SL, Holmer HK, Ogden LA, Burda BU. Conflict of interest in clinical practice guideline development: a systematic review. Plos One. 2011;6(10):e25153.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Phillips KA, Veenstra D, Van Bebber S, Sakowski J. An introduction to cost-effectiveness and cost-benefit analysis of pharmacogenomics. Pharmacogenomics. 2003;4(3):231–9.

    Article  PubMed  Google Scholar 

  25. SA HLS: Under-reporting of adverse drug reactions: a systematic review. Drug Saf 2006, 29(5):385-396, doi:

  26. Bourgeois FT, Shannon MW, Valim C, Mandl KD. Adverse drug events in the outpatient setting: an 11-year national analysis. Pharmacoepidemiol Drug Saf. 2010;19(9):901–10.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Leelakanok N, Holcombe AL, Lund BC, Gu X, Schweizer ML. Association between polypharmacy and death: A systematic review and meta-analysis. J Am Pharm Assoc (2003). 2017;57(6):729–738.e710.

    Article  Google Scholar 

  28. Tonelli M, Riella M. Chronic kidney disease and the aging population. Brazilian J Nephrol. 2014;36(1):1–5.

    Article  Google Scholar 

  29. Nitta K, Okada K, Yanai M, Takahashi S. Aging and chronic kidney disease. Kidney Blood Pressure Res. 2013;38(1):109–20.

    Article  Google Scholar 

  30. Titze S, Schmid M, Köttgen A, Busch M, Floege J, Wanner C, et al. Disease burden and risk profile in referred patients with moderate chronic kidney disease: composition of the German Chronic Kidney Disease (GCKD) cohort. Nephrol Dial Transplan. 2015;30(3):441–51.

    Article  Google Scholar 

  31. USRDS. United States Renal Data System. 2018 USRDS annual data report: Epidemiology of kidney disease in the United States. Bethesda: National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases; 2018.

    Google Scholar 

  32. Mason NA. Polypharmacy and medication-related complications in the chronic kidney disease patient. Curr Opin Nephrol Hypertens. 2011;20(5):492–7.

    Article  PubMed  Google Scholar 

  33. Lea-Henry TN, Carland JE, Stocker SL, Sevastos J, Roberts DM. Clinical Pharmacokinetics in Kidney Disease: Fundamental Principles. Clin J Am Soc Nephrol. 2018;13(7):1085–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Verbeeck RK, Musuamba FT. Pharmacokinetics and dosage adjustment in patients with renal dysfunction. Eur J Clin Pharmacol. 2009;65(8):757–73.

    Article  CAS  PubMed  Google Scholar 

  35. Schmidt IM, Hübner S, Nadal J, Titze S, Schmid M, Bärthlein B, et al. Patterns of medication use and the burden of polypharmacy in patients with chronic kidney disease: the German Chronic Kidney Disease study. Clin Kidney J. 2019;12(5):663–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Secora A, Alexander GC, Ballew SH, Coresh J, Grams ME. Kidney function, polypharmacy, and potentially inappropriate medication use in a community-based cohort of older adults. Drugs Aging. 2018;35(8):735–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Morin L, Laroche M-L, Texier G, Johnell K. Prevalence of Potentially Inappropriate Medication Use in Older Adults Living in Nursing Homes: A Systematic Review. J Am Med Direct Assoc. 2016;17(9):862.e861–9.

    Article  Google Scholar 

  38. Papaioannou A, Clarke JA, Campbell G, Bédard M. Assessment of adherence to renal dosing guidelines in long-term care facilities. J Am Geriatr Soc. 2000;48(11):1470–3.

    Article  CAS  PubMed  Google Scholar 

  39. Chang F, O'Hare AM, Miao Y, Steinman MA. Use of Renally Inappropriate Medications in Older Veterans: A National Study. J Am Geriatr Soc. 2015;63(11):2290–7.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Blix HS, Viktil KK, Moger TA, Reikvam A. Use of renal risk drugs in hospitalized patients with impaired renal function--an underestimated problem? Nephrol Dial Transplant. 2006;21(11):3164–71.

    Article  PubMed  Google Scholar 

  41. Laville SM, Metzger M, Stengel B, Jacquelinet C, Combe C, Fouque D, et al. Evaluation of the adequacy of drug prescriptions in patients with chronic kidney disease: results from the CKD-REIN cohort. Br J Clin Pharmacol. 2018;84(12):2811–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. United Nations. World Population Prospects (The 2008 Revision). Accessed 2 July 2021.

  43. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4(1):1.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Page MJ, McKenzie J, Bossuyt P, Boutron I, Hoffmann T, Mulrow C, et al. Updating guidance for reporting systematic reviews: development of the PRISMA 2020 statement; 2020.

    Google Scholar 

  45. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283(15):2008–12.

    Article  CAS  PubMed  Google Scholar 

  46. Hoy D, Brooks P, Woolf A, Blyth F, March L, Bain C, et al. Assessing risk of bias in prevalence studies: modification of an existing tool and evidence of interrater agreement. J Clin Epidemiol. 2012;65(9):934–9.

    Article  PubMed  Google Scholar 

  47. Campbell M, McKenzie JE, Sowden A, Katikireddi SV, Brennan SE, Ellis S, et al. Synthesis without meta-analysis (SWiM) in systematic reviews: reporting guideline. BMJ. 2020;368:l6890.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–60.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Thompson SG, Higgins JP. How should meta-regression analyses be undertaken and interpreted? Stat Med. 2002;21(11):1559–73.

    Article  PubMed  Google Scholar 

  50. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21(11):1539–58.

    Article  PubMed  Google Scholar 

  51. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336(7650):924–6.

    Article  PubMed  PubMed Central  Google Scholar 

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Funding for this project was received from the Canadian Institute of Health Research (CIHR) 2019.

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Authors and Affiliations



IGO and MMT drafted the protocol manuscript. IGO and AKB provided clinical area, systematic review expertise. FY provided methodology expertise. AKB is the guarantor. All authors read, contributed to, and approved the final version of the manuscript.

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Correspondence to Aminu K. Bello.

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Supplementary Information

Additional file 1:.

PRISMA-P checklist.

Additional file 2:.

Ovid MEDLINE search terms and strategy <1946 to September 18, 2020>.

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Okpechi, I.G., Tinwala, M.M., Muneer, S. et al. Prevalence of polypharmacy and associated adverse health outcomes in adult patients with chronic kidney disease: protocol for a systematic review and meta-analysis. Syst Rev 10, 198 (2021).

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