The prevalence of pain among patients with chronic kidney disease using systematic review and meta-analysis
Authors: Emilie Lambourg, Lesley Colvin, Greg Guthrie, Kiruthikka Murugan, Michelle Lim, Heather Walker, Georgia Boon, Samira Bell
Journal: Kidney International (2021)

Pain is a common but often undertreated symptom in patients with chronic kidney disease (CKD) with a much higher prevalence than in the general population. The aim of this systematic review was to synthesize all available quantitative evidence, in order to gain a better understanding of pain prevalence and pain types in patients with CKD. Four databases and the grey literature were searched until 15th January 2021. Random-effect meta-analyses were conducted with multiple subgroup analyses and meta-regressions to further explore the between-study heterogeneity. The quality of studies included was assessed using the Newcastle-Ottawa scale and the level of evidence was determined using the GRADE approach. One hundred sixteen studies reported data on 40,678 individuals. Results from meta-analyses yielded an overall prevalence of 60% (95% confidence interval 56-64) for pain, 48% (42-55) for chronic pain and 10% (6-15) for neuropathic pain. The prevalence of pain was lower among kidney transplant recipients 46% (37-56) compared with patients undergoing dialysis 63% (57-68) and those with non-dialysis CKD 63% (55-70). Musculoskeletal pain appeared to be the most common pain symptom among patients with CKD managed conservatively 42% (28-56) or receiving dialysis 45% (36-55) whilst abdominal pain was most prevalent in kidney transplant recipients 41% (7-86). Thus, all subgroups of patients with CKD suffer from a high burden of pain. Hence, greater awareness and recognition of this issue is vital to inform policy and service provision in this area. Pain is a common but often undertreated symptom in patients with chronic kidney disease (CKD) with a much higher prevalence than in the general population. The aim of this systematic review was to synthesize all available quantitative evidence, in order to gain a better understanding of pain prevalence and pain types in patients with CKD. Four databases and the grey literature were searched until 15th January 2021. Random-effect meta-analyses were conducted with multiple subgroup analyses and meta-regressions to further explore the between-study heterogeneity. The quality of studies included was assessed using the Newcastle-Ottawa scale and the level of evidence was determined using the GRADE approach. One hundred sixteen studies reported data on 40,678 individuals. Results from meta-analyses yielded an overall prevalence of 60% (95% confidence interval 56-64) for pain, 48% (42-55) for chronic pain and 10% (6-15) for neuropathic pain. The prevalence of pain was lower among kidney transplant recipients 46% (37-56) compared with patients undergoing dialysis 63% (57-68) and those with non-dialysis CKD 63% (55-70). Musculoskeletal pain appeared to be the most common pain symptom among patients with CKD managed conservatively 42% (28-56) or receiving dialysis 45% (36-55) whilst abdominal pain was most prevalent in kidney transplant recipients 41% (7-86). Thus, all subgroups of patients with CKD suffer from a high burden of pain. Hence, greater awareness and recognition of this issue is vital to inform policy and service provision in this area. There is a growing body of evidence showing that pain is among the most common symptoms experienced by individuals with chronic kidney disease (CKD), but little is known about the specific types of pain in this population.1Barakzoy A.S. Moss A.H. Efficacy of the world health organization analgesic ladder to treat pain in end-stage renal disease.J Am Soc Nephrol. 2006; 17: 3198-3203Crossref PubMed Scopus (135) Google Scholar Moreover, in clinical practice, there is a lack of recognition by health care providers leading to underreporting and undertreatment of pain in this population.2Claxton R.N. Blackhall L. Weisbord S.D. Holley J.L. Undertreatment of symptoms in patients on maintenance hemodialysis.J Pain Symptom Manage. 2010; 39: 211-218Abstract Full Text Full Text PDF PubMed Scopus (95) Google Scholar Chronic pain results in a further reduction in quality of life3Tong A. Wong G. McTaggart S. et al.Quality of life of young adults and adolescents with chronic kidney disease.J Pediatr. 2013; 163: 1179-1185.e1175Abstract Full Text Full Text PDF PubMed Scopus (46) Google Scholar with associated insomnia, depression,4Weisbord S.D. Fried L.F. Arnold R.M. et al.Prevalence, severity, and importance of physical and emotional symptoms in chronic hemodialysis patients.J Am Soc Nephrol. 2005; 16: 2487-2494Crossref PubMed Scopus (342) Google Scholar decrease in daily activities and social interactions, isolation, reduced survival, and higher use of other medical resources leading to major health care costs and risk of dialysis withdrawal. Overall, prevalence of pain in patients undergoing kidney replacement therapy is thought to range between 40% and 60%.5Pham P.C. Khaing K. Sievers T.M. et al.2017 update on pain management in patients with chronic kidney disease.Clin Kidney J. 2017; 10: 688-697Crossref PubMed Scopus (67) Google Scholar However, there are currently no reliable overall prevalence estimates of the different types of pain in the various CKD subgroups as quantitative syntheses of chronic pain are scarce, especially among kidney transplant recipients (KTRs) and patients managed conservatively. Moreover, the recent increasing number of publications in this field report highly variable pain prevalence measures.6Brkovic T. Burilovic E. Puljak L. Prevalence and severity of pain in adult end-stage renal disease patients on chronic intermittent hemodialysis: a systematic review.Patient Prefer Adherence. 2016; 10: 1131-1150PubMed Google Scholar Almutary et al.7Almutary H. Bonner A. Douglas C. Which patients with chronic kidney disease have the greatest symptom burden? A comparative study of advanced CKD stage and dialysis modality.J Ren Care. 2016; 42: 73-82Crossref PubMed Scopus (58) Google Scholar reviewed the burden of symptoms experienced by patients with CKD grades 4 and 5, including dialysis and conservative management. They identified pain as one of the most common symptoms along with fatigue, pruritus, dry skin, and drowsiness, with prevalence measures ranging from 38% to 90% and a weighted mean of 65%. Brkovic et al.6Brkovic T. Burilovic E. Puljak L. Prevalence and severity of pain in adult end-stage renal disease patients on chronic intermittent hemodialysis: a systematic review.Patient Prefer Adherence. 2016; 10: 1131-1150PubMed Google Scholar examined prevalence and severity of pain in a systematic review of patients undergoing hemodialysis, with measurements ranging between 33% and 82% for chronic pain and 21% and 92% for acute pain. However neither meta-analysis nor meta-regression were conducted.6Brkovic T. Burilovic E. Puljak L. Prevalence and severity of pain in adult end-stage renal disease patients on chronic intermittent hemodialysis: a systematic review.Patient Prefer Adherence. 2016; 10: 1131-1150PubMed Google Scholar They acknowledged important heterogeneity in their results, recommending further exploration of the factors underlying this diversity. These inconclusive findings are likely to be explained by the large variation in pain types and sites studied, the lack of standardization in pain definitions and assessment scales, and heterogeneity of the CKD population with regard to their treatment options (conservative management with or without palliative care, dialysis, kidney transplantation). The aims of this systematic review are to obtain up-to-date population-based estimates of the prevalence of various pain types in the different subgroups constituting the population of patients with CKD (CKD nondialysis, dialysis, KTRs, palliative care) and to better understand the heterogeneity reported in previous systematic reviews, via stratified meta-analyses and meta-regressions. This study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The protocol was registered and published on PROSPERO (CRD42019156491).8Lambourg E. Colvin L. Bell S. Boon G. Guthrie G. The prevalence of pain, analgesics use and their adverse events in patients with chronic kidney disease: protocol for a systematic review. PROSPERO Web site. 2019.https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=156491Google Scholar This article reports the first outcome out of the 3 stated in the protocol. Electronic searches (from inception to January 15, 2021) of MEDLINE/PubMed, Embase, Cochrane Register for Controlled Trials (CENTRAL), and Cumulative Index of Nursing and Allied Health (CINAHL) were conducted. The search strategies combined free text words and medical subject heading (MeSH) terms (Supplementary Table S1). Only articles available in French or English languages were considered. Reference lists of systematic reviews and short-listed studies were manually searched to identify additional citations that could have been missed. The gray literature also supplemented the results in order to cover the topic as extensively as possible. Contact was made with the authors when additional details were required to ensure the suitability of the study or to gather supplementary data. All records were screened on the basis of their title and abstract by 2 different reviewers (EL and GB) who were blinded to each other, using the online platform Rayyan.9Ouzzani M. Hammady H. Fedorowicz Z. Elmagarmid A. Rayyan-a web and mobile app for systematic reviews.Syst Rev. 2016; 5: 210Crossref PubMed Scopus (2809) Google Scholar Conflict was resolved by a third author (SB). Reviewers then proceeded to full-text assessment of potentially relevant articles against the following predefined inclusion/exclusion criteria. Studies in French or English language that reported (or allowed for calculation of) a prevalence of general or site-specific pain in participants with CKD aged 18 years or older were included. Patients with CKD were defined as individuals with an estimated glomerular filtration rate (eGFR) < 60 ml/min per 1.73 m2 (or eGFR categories G3 to G5 in the CGA staging [i.e., identify cause of CKD {C}, assign GFR category {G}, assign albuminuria category {A}]) for over 3 months or more, irrespective of cause, in accordance with the National Kidney Foundation Kidney Disease Outcomes Quality Initiative (NKF K/DOQI) definition.10Levey A.S. Eckardt K.U. Tsukamoto Y. et al.Definition and classification of chronic kidney disease: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO).Kidney Int. 2005; 67: 2089-2100Abstract Full Text Full Text PDF PubMed Scopus (2272) Google Scholar,11Levey A.S. Eckardt K.U. Dorman N.M. et al.Nomenclature for kidney function and disease: report of a Kidney Disease: Improving Global Outcomes (KDIGO) Consensus Conference.Kidney Int. 2020; 97: 1117-1129Abstract Full Text Full Text PDF PubMed Scopus (153) Google Scholar Studies investigating pain among KTRs, irrespective of their eGFR measurement, and patients undergoing dialysis (hemodialysis or peritoneal dialysis) were also included. Observational studies were included without any restriction on their design (cross-sectional, case-control, or cohort studies). Clinical trials were also included if a baseline prevalence of pain in the sample before the implementation of any intervention could be retrieved. Data from the gray literature such as conference abstracts and posters were also included to limit the risk of publication bias. Studies were excluded if they met any of the following criteria: studies investigating acute pain related to specific procedures, such as postoperative or intradialytic pain; studies reporting on individuals <18 years old; and those including patients with an eGFR > 60 ml/min per 1.73 m2. Case reports, case-series, book chapters, reviews, and personal opinions were also systematically excluded. Studies reporting a prevalence of pain without any specification (not qualified as chronic, neuropathic, or site-specific) were included in the "pain" category, independently of the recall period assessed (e.g., current pain, pain over the past 3 days, past week, past month). Studies labeling their outcome "chronic pain" or investigating pain lasting >3 months were categorized as "chronic pain," in accordance with the new International Classification of Diseases–11th Revision classification.12Treede R.D. Rief W. Barke A. et al.Chronic pain as a symptom or a disease: the IASP classification of chronic pain for the International Classification of Diseases (ICD-11).Pain. 2019; 160: 19-27Crossref PubMed Scopus (483) Google Scholar Studies labeling their outcome "neuropathic pain," "neuralgia," "neuropathic cause of pain," or "painful peripheral neuropathy" were classified in the neuropathic pain category. Studies on peripheral neuropathy such as diabetic neuropathy were excluded if it was not clearly specified as painful. The musculoskeletal pain category included studies reporting pain affecting the bones, joints, muscles, or related soft tissues. The headache category included pain in the head but also in the back of the upper neck. Abdominal pain and chest pain were differentiated and reported in 2 different categories. Abdominal pain included upper and lower abdominal pain, uncomfortable bloating, stomach pain, pain or burning sensations related to gastroesophageal reflux disease, and discomfort related to constipation or diarrhea. Chest pain included pain related to pulmonary or cardiovascular conditions such as angina but also benign musculoskeletal pain localized specifically in the chest wall area. Data were extracted on a standardized Microsoft Excel spreadsheet specifically designed for the study and piloted beforehand on a small sample of the selected studies. The spreadsheet contained key characteristics of studies, selected according to the Population Intervention Comparison Outcome Study type (PICOS) principle.13Schardt C. Adams M.B. Owens T. et al.Utilization of the PICO framework to improve searching PubMed for clinical questions.BMC Med Inform Decis Mak. 2007; 7: 16Crossref PubMed Scopus (921) Google Scholar14Muhammad S. Bushra A. Modifying "Pico" question into "Picos" model for more robust and reproducible presentation of the methodology employed in a scientific study..World J Plast Surg. 2017; 6: 390-392PubMed Google Scholar The detailed list of relevant items collected in the data extraction spreadsheet is available in Supplementary Material S1. Data were fully extracted by 1 author (EL). However, for outcome data an independent duplicate extraction was performed by another reviewer (KM), as recommended in the Cochrane handbook.15Higgins JPT, Thomas J, Chandler J, et al. Cochrane Handbook for Systematic Reviews of Interventions version 6.1. Available at: www.training.cochrane.org/handbook. Published 2020. Updated September 2020. Accessed May 12, 2021.Google Scholar Disagreement was resolved by discussion and consensus with a third reviewer (SB). Two reviewers (EL and KM) working independently evaluated the risk of bias at study-level using the Newcastle-Ottawa scale,16Wells G. Shea B. O'Connell D. et al.The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses.http://www.ohri.ca/programs/clinical_epidemiology/oxford.aspGoogle Scholar a tool specifically designed to assess the quality of nonrandomized studies. Its "star system" enables us to assign an overall study quality (low, moderate, or high) after evaluating risk of bias across 3 domains: selection bias, confounding, and outcome measurement bias. Prior to performing quality appraisal, the scale was customized to specifically assess studies measuring a prevalence of pain in the CKD population. This adaptation was based on the team's knowledge in the fields of pain and nephrology, as well as on published guidelines for prevalence studies evaluation.17Boyle M.H. Guidelines for evaluating prevalence studies.Evid Based Ment Health. 1998; 1: 37-39Crossref Scopus (215) Google Scholar Details of the scale are provided in Supplementary Material S2. Exclusion of low-quality studies only took place when performing sensitivity analyses in an objective to explore the result's heterogeneity. Otherwise, following Glass's approach,18Glass G.V. Meta-analysis at 25.http://glass.ed.asu.edu/gene/papers/meta25.htmlGoogle Scholar all studies were retained, independently of their quality. Funnel plots specifically adapted to proportion data were built to detect "small-study effect." They represent the logit-transformed prevalence, for its better statistical properties, against a measure of precision chosen here as the standard error. Their asymmetry was tested using Egger's (linear regression method) and Begg's (rank correlation method) tests. However, it should be kept in mind that traditional publication bias assessment tools are designed for comparative studies reporting effect size results along with a significance level and not for observational studies reporting single proportions.19Wang N. How to conduct a meta-analysis of proportions in R: a comprehensive tutorial. 2018.https://www.researchgate.net/publication/325486099Google Scholar Multiple meta-analyses were conducted according to pain types with 3 different outcomes for general pain—pain, chronic pain, neuropathic pain—and 5 supplementary outcomes for pain affecting specific body sites—headache, chest pain, musculoskeletal pain, abdominal pain, and fibromyalgia. Meta-regressions investigating the role of patients' baseline characteristics and meta-analyses stratified by CKD management strategies, risk of bias, and geographic location were planned a priori. Meta-analyses stratified by pain assessment scales, dialysis modality, and CKD stages were data-driven. When a single study simultaneously reported a prevalence of pain in groups of patients characterized by different CKD management strategies, they were included in a same stratified meta-analysis as separate estimates. Between-study heterogeneity was assessed by Higgin and Thompson I2. I2 can compare the heterogeneity between subgroups and between meta-analyses of different sizes, suiting the stratified design of our analyses. It is considered that an I2 value above the 75% threshold describes a high level of heterogeneity.20Higgins J.P. Thompson S.G. Deeks J.J. Altman D.G. Measuring inconsistency in meta-analyses.BMJ. 2003; 327: 557-560Crossref PubMed Scopus (35163) Google Scholar To explore the heterogeneity, uni- and multivariate meta-regressions were conducted with various patients' baseline characteristics as predictors. Specifically, the influence of sex, age, ethnicity, body mass index (BMI), diabetes and hypertension were investigated on prevalence estimates. Several sensitivity analyses were also performed to further investigate the observed heterogeneity in results. Specifically, we explored the influence of geographic area and pain assessment scales. The methods and results of those analyses are described in Supplementary Material S3. All statistical analyses were conducted using R software version 3.5.2 (R Foundation). Meta-analyses pooling prevalence data were performed using the metaprop function from R package "meta"21Balduzzi S. Rucker G. Schwarzer G. How to perform a meta-analysis with R: a practical tutorial.Evid Based Ment Health. 2019; 22: 153-160Crossref PubMed Scopus (631) Google Scholar and the results obtained were displayed in forest plots. All meta-analyses were undertaken using random-effect models, as assumption was made that pain prevalence would vary between sample populations arising from different countries, health care centers, and socioeconomic areas. A generalized linear mixed model approach was adopted. This method, considered as a promising alternative to the Freeman-Tukey double arcsine transformation, has recently been recommended for meta-analyses of single proportions.22Schwarzer G. Chemaitelly H. Abu-Raddad L.J. Rucker G. Seriously misleading results using inverse of Freeman-Tukey double arcsine transformation in meta-analysis of single proportions.Res Synth Methods. 2019; 10: 476-483Crossref PubMed Scopus (136) Google Scholar The model was built with a maximum likelihood estimator and the Q-profile to estimate tau and its confidence interval (CI), as recommended by Veroniki. The Hartung-Knapp method was systematically implemented to adjust the confidence interval of the overall estimate.23van Aert R.C.M. Jackson D. A new justification of the Hartung-Knapp method for random-effects meta-analysis based on weighted least squares regression.Res Synth Methods. 2019; 10: 515-527Crossref PubMed Scopus (21) Google Scholar As recommended by Cochrane, the certainty of available evidence was evaluated according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria. Using the online software GradePro,24GRADEpro GDT: GRADEpro Guideline Development Tool [Software]. McMaster University, 2020 (developed by Evidence Prime, Inc.). Available at: gradepro.org. Accessed May 12, 2021.Google Scholar the assessment was based on study design, consistency, directness, risk of bias, precision, and publication bias. For each outcome, the level of evidence was characterized as high, moderate, low, or very low. Our electronic search of MEDLINE, Embase, CENTRAL, and CINAHL yielded 7754 articles, complemented by 34 records from the gray literature. A total of 116 studies met our inclusion criteria, including a total of 40,678 participants in 38 different countries across the 5 continents. The United States and the United Kingdom were the highest data providers with 30 articles arising from those 2 countries (United States: n = 18; United Kingdom: n = 12). Overall, there were 30% (n = 35) investigating pain on <100 patients and only 9% (n = 10) assessing pain on >1000 patients. A flow diagram details the selection process (Figure 1) while the precise number of studies and participants by outcome is available in Supplementary Table S2. Baseline characteristics of the 71 studies investigating pain, chronic pain, or neuropathic pain are presented in Supplementary Tables S3, S4, and S5, respectively. Supplementary Tables S6–S10 present the main characteristics of the 45 additional studies focusing on pain in specific body sites. Figure 2 displays the forest-plot pooling 57 studies reporting a prevalence of pain among a total of nearly 20,000 participants, stratified by CKD management strategy. Fifty-eight studies were eligible, but 1 was excluded from meta-analyses25Jhamb M. Abdel-Kader K. Yabes J. et al.Comparison of fatigue, pain, and depression in patients with advanced kidney disease and cancer-symptom burden and clusters.J Pain Symptom Manage. 2019; 57: 566-575.e563Abstract Full Text Full Text PDF PubMed Scopus (23) Google Scholar due to the high threshold chosen by the authors to determine a clinically significant pain (score ≤50 on the 36-Item Short Form Survey), excluding all patients experiencing mild pain and a large part of those with moderate pain. Prevalence estimates ranged from 29% in a sample of KTRs in the United Kingdom to 90% among patients with CKD G5 treated conservatively in a palliative care unit. The mean prevalence of pain was 60% (95% CI: 56%–64%), I2 = 96%. The dialysis group was the most widely investigated and displayed the highest prevalence of pain, estimated at 63% (95% CI: 57%–68%). Although the burden of pain remained substantial among KTRs, we observed a significantly lower prevalence (46%; 95% CI: 37%–56%) compared with patients with CKD nondialysis (63%; 95% CI: 55%–70%) and those undergoing dialysis (63%; 95% CI: 57%–68%), χ2 test for subgroup differences P < 0.01. Prevalence of pain was further stratified by dialysis modality (hemodialysis or peritoneal dialysis) in the dialysis subgroup and by CKD stage (3, 4, or 5) in the CKD nondialysis subgroup. Our random-effect pooled estimates showed similar prevalence of pain (χ2 test for subgroup difference: P = 0.42) among patients undergoing hemodialysis (65%; 95% CI: 58%–72%) or peritoneal dialysis (58%; 95% CI: 30%–81%) (Figure 3). Among patients with CKD managed conservatively, the forest plot stratified by CKD stages considerably decreased the between-study heterogeneity with an I2 down to 0% in the CKD stage 3 and CKD stage 4 subgroups, and to 17% in the CKD stages 4–5 subgroup. Surprisingly, a lower prevalence of pain was associated with later CKD stages (Figure 4a). However, we hypothesized that this could be related to the fact that the CKD stage 5 subgroup was mainly constituted of studies conducted in palliative care settings where pain is the main focus and its symptoms are more likely to be treated. Confirming our hypotheses, after removing palliative care studies of the CKD stage 5 subgroup, the pain prevalence increased from 58% to 70% with no more difference across the various CKD stages (Figure 4b). However, this suggests that patients with CKD stage 3 or 4 are just as likely to suffer from pain as those with kidney failure managed conservatively.Figure 4Forest plot of pain prevalence stratified by chronic kidney disease (CKD) stage, before (a) and after (b) exclusion of studies conducted in palliative care settings. CI, confidence interval; df, degrees of freedom; GLMM, generalized linear mixed model; NA, not available; ND, nondialysis.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Figure 4Forest plot of pain prevalence stratified by chronic kidney disease (CKD) stage, before (a) and after (b) exclusion of studies conducted in palliative care settings. CI, confidence interval; df, degrees of freedom; GLMM, generalized linear mixed model; NA, not available; ND, nondialysis.View Large Image Figure ViewerDownload Hi-res image Download (PPT) Meta-regression models were fitted to further explore the heterogeneity. None of the tested covariates showed significance in the univariate analysis. However, age became significant (P = 0.018; I2 = 89%) in the multivariate model accounting for sex, ethnicity, and the geographical area the study was from (Supplementary Table S11). Nineteen studies including 3859 participants were pooled (Figure 5), resulting in an overall random-effect prevalence of 48% (95% CI: 42%–55%). Once again, the largest number of studies (n = 14) was in the dialysis subgroup, while the CKD nondialysis and palliative care subgroups only composed a single study. Four studies assessed pain prevalence among KTRs, with estimates showing a relatively good consistency (I2 = 53%). Two outlying studies were identified: a particularly low prevalence of chronic pain (21%) was reported in the only study conducted in palliative care settings.26Chan K.Y. Yap D.Y.H. Yip T. et al.Palliative care consultation in advanced chronic kidney disease with pain.J Palliat Med. 2018; 21: 809-814Crossref PubMed Scopus (5) Google Scholar However, this is unsurprising as palliative care teams are likely to focus more on pain issues and their management. The other outlying prevalence measurement driving part of the heterogeneity was found in the dialysis subgroup.27Frazao C.M. de Sa J.D. Medeiros A.B. et al.The adaptation problems of patients undergoing hemodialysis: socio-economic and clinical aspects.Rev Lat Am Enfermagem. 2014; 22: 966-972Crossref PubMed Scopus (11) Google Scholar This study, conducted in a single clinic in Brazil, reported a very low prevalence of chronic pain (16%) among a sample of relatively young patients (mean age: 46.6 ± 12.3 years). As age was found to be significantly associated with pain in our multivariate model (see previous section), the exclusion of patients >65 years old could explain the lower prevalence of pain obtained by the authors. The I2 value was down to 77% in the dialysis subgroup and to 89% overall, after exclusion of this study (Supplementary Figure S1). Meta-regression analyses did not uncover any significant association with the covariates tested (Supplementary Table S11). Twelve studies including a total of 3384 individuals were grouped to obtain a global prevalence of neuropathic pain of 10% (95% CI: 6%–15%) (Figure 6) with no significant difference between subgroups defined by CKD management strategies (P = 0.51). Heterogeneity was globally high (I2 = 95%) except in the KTRs subgroup that contained 2 studies with very consistent estimates (I2 = 0%). Meta-regression showed that a higher percentage of participants affected by hypertension in the sample and a higher mean BMI were both associated with a higher prevalence of neuropathic pain (Supplementary Figure S2A and B; P = 0.002 and P < 0.0001, respectively). Univariate models with hypertension and BMI as predictors only left 14% and 0% of unaccounted heterogeneity, respectively, suggesting strong relationships (Supplementary Table S11). Those associations remained in the multivariate models controlling for age, sex, and geographic area. The multivariate model also uncovered another significant covariate: the percentage of patients with diabetes in the sample became positively correlated with the prevalence of neuropathic pain after controlling for age, sex, and geographic area (Supplementary Table S11; P = 0.03; I2 = 61%). Finally, univariate meta-regression demonstrated that the proportion of female subjects in the study sample was negatively associated with the prevalence of neuropathic pain (Supplementary Table S11 and Supplementary Figure S2C). Supplementary Table S12 summarizes the pooled prevalence obtained for several body sites and fibromyalgia, overall and stratified by CKD management strategy. Musculoskeletal pa