The association between proton pump inhibitor use and the risk of mortality in patients with kidney disease: a systematic review and meta-analysis

The association between proton pump inhibitor use and the risk of mortality in patients with kidney disease: a systematic review and meta-analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The association between proton pump inhibitor use and the risk of mortality in patients with kidney disease: a systematic review and meta-analysis Ilsoo Park, Hyun Jin Song, Hyun-Ju Seo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7206711/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Mar, 2026 Read the published version in European Journal of Clinical Pharmacology → Version 1 posted 14 You are reading this latest preprint version Abstract Background: Use of proton pump inhibitor (PPI) has been associated with adverse health outcomes, including increased risk of all-cause mortality. Evidence suggests that individuals with kidney disease who use PPIs may experience higher mortality, though the nature of this association is not well established. Objective: To assess the relationship between PPI use and mortality among individuals with kidney disease through a systematic review and meta-analysis. Methods: A comprehensive search of Ovid-MEDLINE, Ovid-EMBASE, and Cochrane CENTRAL was conducted through April 2025 to identify randomized controlled trials and observational studies examining mortality among PPI users versus non-users with kidney disease. Both unadjusted mortality rates and adjusted hazard ratios (aHRs) were extracted. A random-effects meta-analysis was performed using the Hartung-Knapp-Sidik-Jonkman method, with the Sidik-Jonkman estimator used for between-study variance (τ²). Study heterogeneity was evaluated using the I² statistic and Cochran’s Q test. Subgroup analyses were carried out based on follow-up length, population characteristics, geographic region, and risk of bias level. Results: The review included 24 observational studies encompassing 216,032 individuals with kidney disease. Across 20 cohorts from 17 observational studies, mortality was 23.2% among PPI users and 22.1% among non-users. Pooled adjusted estimates from 18 studies (20 cohorts) indicated a significantly increased risk of death in PPI users (aHR 1.26; 95% CI, 1.11–1.42). Considerable heterogeneity was observed, but subgroup analyses revealed consistent trends. Conclusions: Our meta-analysis showed that PPI use was linked to elevated mortality risk in kidney disease populations. Careful consideration is advised when prescribing PPIs, and further research is needed. proton pump inhibitors mortality elderly systematic review meta-analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Globally, more than 850 million people are affected by chronic kidney disease, acute kidney injury, or are undergoing dialysis or renal transplant [ 1 ]. The prevalence of kidney disease has been increasing, driven by factors such as aging populations, diabetes, and hypertension [ 2 ]. Patients with kidney disease are frequently prescribed proton pump inhibitors (PPIs) to manage gastrointestinal conditions like gastroesophageal reflux disease, peptic ulcers, and to prevent upper gastrointestinal bleeding, especially when on antiplatelet or anticoagulant therapies [ 3 – 5 ]. However, emerging evidence has raised concerns about the long-term safety of PPIs, particularly in individuals with compromised renal function [ 6 , 7 ]. Long-term PPI use has been associated with several adverse effects, including hypomagnesemia, Clostridioides difficile infection, pneumonia, bone fractures, and progression of kidney disease [ 8 – 11 ]. These risks may be amplified in CKD patients due to altered drug metabolism and increased susceptibility to complications. Recent studies have suggested a potential link between PPI use and increased all-cause mortality. An analysis of data from 214,467 individuals found that PPI users had a higher risk of chronic kidney disease-related mortality compared to those using H2 blockers [ 12 ]. A large prospective cohort study in the US also reported significantly higher risks of all-cause mortality and mortality due to renal disease among PPI users [ 13 ]. However, the evidence remains inconclusive. While previous studies have primarily focused on the general population, no systematic review or meta-analysis has specifically evaluated the association between PPI use and mortality in patients with impaired renal function. Given the widespread use of PPIs among patients with kidney disease and the potential for serious adverse outcomes, it is crucial to comprehensively assess the association between PPI use and mortality risk in this population. Therefore, we conducted a systematic review and meta-analysis to evaluate the association between PPI use and the risk of all-cause mortality in patients with kidney disease. Methods Literature Search and Study Selection We conducted a comprehensive literature search of Ovid-MEDLINE, Ovid-EMBASE, and the Cochrane CENTRAL to identify relevant articles published up to April 24, 2025. The search strategy included a combination of MeSH terms and free-text keywords related to the patient population (e.g., “kidney disease,” “renal failure,” “dialysis” ) and the intervention of interest ( proton pump inhibitors ), including both generic and brand names ( benatoprazole, dexlansoprazole, esomeprazole, lansoprazole, omeprazole, pantoprazole, rabeprazole, tenatoprazole ). The full search strategy is provided in Supplement Table 1 . We included studies that met all of the following criteria: 1) evaluated the association between PPI use and the risk of mortality among patients with kidney disease; 2) compared PPIs with a control group (e.g., placebo or active comparator); 3) reported either the number of deaths in both groups or a hazard ratio (HR) for mortality; 4) employed a randomized controlled trial (RCT), non-randomized controlled study, or observational study design; 5) were published in English. We excluded non-original research articles, including case reports and series, editorials, narrative or systematic reviews, and conference abstracts. Additionally, studies were excluded if they did not report either the number of deaths or the hazard ratio comparing PPI and control groups. Two reviewers independently screened titles and abstracts, followed by full-text assessment of potentially eligible studies. Any discrepancies were resolved through discussion or adjudication by a third reviewer. This systematic review was registered in PROSPERO (CRD420251063447), and we adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines throughout the review process [ 14 ]. Quality Assessment Two independent researchers assessed the quality of the included studies. The Risk of Bias In Non-randomized Studies - of Interventions (ROBINS-I) was applied to evaluate observational studies. ROBINS-I evaluates seven items across three domains: pre-intervention, at-intervention, and post-intervention domains [ 15 ]. Pre-intervention domain covers bias due to confounding and bias in selection of participants into the study. The at-intervention domain assesses bias in the classification of intervention. The post-intervention domain addresses bias due to deviations from intended interventions, bias due to missing data, bias in measurement of the outcome, and bias in selection of the reported result. We included an overall risk of bias assessment based on seven items. Each study was rated as having low, moderate, serious risk of bias. Data Extraction From each included study, we extracted information on demographic characteristics, including country, study design, data source, study period, mean age, and the proportion of male participants. We also collected data on exposure, such as the definition and number of PPI users and controls, duration of follow-up, and concomitant medication use. Outcome data included the number of deaths in both the PPI and comparator groups, as well as the reported HRs for mortality. When applicable, confounding variables adjusted for in the regression analyses used to calculate hazard ratios were also documented. The primary outcome was the risk of mortality associated with PPI use comparing nonusers. For the meta-analysis, we prioritized the most fully adjusted effect estimates (i.e., adjusted hazard ratios [HRs]) along with their corresponding 95% confidence intervals (CIs), accounting for confounders reported in each study. Unadjusted estimates were also extracted for the two groups. Statistical Analysis To estimate the pooled relative risks (RRs) or HRs with corresponding 95% CIs, we used a random-effects model based on inverse-variance weighting, applying the Hartung-Knapp-Sidik-Jonkman adjustment for CIs and the Sidik-Jonkman estimator to calculate the between-study variance (τ²). This Sidik-Jonkman estimator is considered more robust in the presence of substantial heterogeneity and varying study sizes, as it provides more conservative estimates and reduces the risk of false positives [ 16 , 17 ]. Statistical heterogeneity was assessed using the I² statistic and Cochran’s Q test. An I² value greater than 50% was interpreted as indicating substantial heterogeneity [ 18 ], and a p-value < 0.05 for the Q test was considered statistically significant. To assess potential publication bias, we visually inspected funnel plots, which may reveal asymmetry due to the preferential publication of studies with positive findings. Among included studies, Kang et al. shared a non-user comparator group for both the > 90 days and ≤ 90 days exposure groups; therefore, we divided the sample size and number of events in the comparator group equally across the relevant comparisons to prevent double-counting and preserve the independence of comparisons within the meta-analysis [ 18 ]. To assess potential publication bias, we visually inspected funnel plots for asymmetry, which may suggest the preferential publication of studies with positive findings. In addition, we conducted Begg’s rank correlation test and Egger’s regression asymmetry test. A p-value of less than 0.10 was considered indicative of potential publication bias for both tests [ 19 , 20 ]. We conducted subgroup analyses of aHRs to explore potential sources of heterogeneity and to assess whether the association between PPI use and mortality varied across different study-level and population characteristics. Subgroups were defined based on follow-up duration (≤ 3 years vs. >3 years), mean or median age of study participants (≤ 65 vs. >65 years), and the proportion of male participants in each study (≤ 60% vs. >60%). To further explore disease-specific mortality risk, we evaluated the association between PPI use and mortality outcomes separately for patient subgroups, including individuals with chronic kidney disease, dialysis, kidney transplant, or renal cancer. To account for differences in healthcare systems and clinical practice patterns, subgroup analyses were also stratified by region (United States/Canada, Europe, and Asia). Additionally, we examined whether study quality influenced the pooled estimates by performing subgroup analyses according to risk of bias, comparing studies classified as having low versus moderate risk; no studies reporting aHRs were categorized as serious risk of bias. All statistical analyses were performed using R version 4.4.1 (R Foundation for Statistical Computing, Vienna, Austria). Results Literature Search An initial search identified 5,308 articles. After removing 608 duplicates, 4,700 unique records remained for screening (Fig. 1 ). Of these, 4,630 articles were excluded during the title and abstract screening. An additional 46 articles were excluded after full-text review due to one or more of the following reasons: absence of kidney disease, no exposure to PPI therapy, lack of a comparator group, ineligible study design, no relevant outcomes reported, non-original research, or publication in a non-English language. Ultimately, 27 cohorts from 24 studies were included in the systematic review [ 21 – 44 ], with three studies contributing two cohorts each [ 22 , 26 , 29 ]. For the meta-analysis, 20 cohorts from 17 studies were included for unadjusted RRs of mortality, and 20 cohorts from 18 studies were included for aHRs of mortality. General Characteristics of the Included Studies A total of 22 cohort studies and 2 ad hoc analyses of clinical trials were included in the review (Table 1 ). The intervention group comprised patients receiving PPIs, with comparators being either placebo or histamine-2 receptor antagonists (H2RAs). The studies were conducted in North America (United States and Canada), Europe (Spain, Netherlands, Belgium, United Kingdom, and France), and Asia (Japan, Taiwan, South Korea, Pakistan, and China). Study populations included patients on dialysis (n = 10), with chronic kidney disease (n = 7), kidney transplant recipients (n = 2), and individuals with renal cancer (n = 5). In studies of renal cancer, comedications included tyrosine kinase inhibitors and immune checkpoint inhibitors. Altogether, the included studies enrolled 216,032 participants, with median ages ranging from 53 to 73 years and the proportion of male participants ranging from 36–99%. The duration of follow-up ranged from 4.4 months to 5.6 years. Most studies adjusted for potential confounders in their estimation of HRs, including baseline demographics, clinical characteristics, comorbidities, and concomitant medication use. Quality Assessment All included cohort studies were assessed as having a low risk of bias in the following domains: selection of participants, deviations from intended interventions, missing data, measurement of outcomes, and selection of reported results (Fig. 2 ). The risk of bias for outcome measurement was considered low, as mortality is an objective outcome unlikely to be influenced by measurement methods. However, approximately half of the studies were rated as having a moderate risk of bias in the classification of interventions, primarily due to the potential for over the counter (OTC) use of PPIs, which may not have been fully captured. Four studies were judged to have a serious risk of bias due to confounding, as they did not report adjusted hazard ratios accounting for potential confounders. Overall, 37.5% of studies were rated as having a low risk of bias, 37.5% as moderate, and 25% as serious. Proton Pump Inhibitors and Mortality Among 20 cohorts from 17 studies reporting unadjusted mortality rates, the death rate was 23.2% among PPI users (15,755 of 67,853) and 22.1% among non-users (28,986 of 131,009). PPI use was significantly associated with an increased risk of mortality in unadjusted analyses (RR 1.28, 95% CI: 1.06–1.55), with substantial heterogeneity observed across studies (I² = 95%, p < 0.001) (Fig. 3 A). Funnel plot analysis, Begg test (p = 0.190), and Egger test (p = 0.130) showed no indication of publication bias (Fig. 4 A). For adjusted analyses, 20 cohorts from 18 studies comprising 167,053 individuals with kidney impairment were included. PPI use remained significantly associated with a higher risk of mortality compared to non-use (adjusted HR 1.26, 95% CI: 1.12–1.43) (Fig. 3 B). Considerable heterogeneity was present (I² = 88%, p < 0.001), and no evidence of publication bias was detected in the corresponding funnel plot (Fig. 4 B). Begg’s test did not indicate significant publication bias (p = 0.105), whereas Egger’s test suggested potential publication bias (p = 0.013). Subgroup analyses Subgroup analyses of aHRs were conducted across observational studies. Among individuals with kidney impairment, PPI use was significantly associated with an increased risk of mortality during both shorter (≤ 3 years; aHR 1.23, 95% CI: 1.06–1.43) and longer follow-up periods (> 3 years; aHR 1.32, 95% CI: 1.04–1.69) (Table 2 ). Similar trends were observed across patient subgroups, including those on dialysis, with chronic kidney disease, and individuals with renal cancer, with the associations approaching statistical significance. Table 2 Subgroup analysis of the association between proton pump inhibitors and the adjusted risk of mortality Cohort, n PPI, n Control, n Random effects, aHR [95% CI] Effect, P -value I 2 Heterogeneity, P -value Follow up ≤ 3 years 7 14,333 26,397 1.23 [1.06, 1.43] 0.015 40% 0.128 >3 years 9 37.080 119,654 1.32 [1.04, 1.69] 0.030 94% < 0.001 Patients Dialysis 8 34,072 116,979 1.18 [0.97,1.42] 0.084 65% 0.005 Chronic kidney disease 5 16,432 26,879 1.46 [0.95–2.25] 0.070 97% < 0.001 Kidney transplant 2 727 632 1.56 [0.51, 4.74] 0.123 0% 0.524 Renal cancer a 5 612 3,731 1.10 [0.92–1.32] 0.203 37% 0.175 Countries US/Canada a 7 21,194 40,947 1.05 [0.95, 1.15] 0.282 42% 0.111 Europe 5 3,680 3,651 1.61 [1.20, 2.16] 0.011 54% 0.070 Asia a 8 26,969 103,623 1.29 [1.03, 1.62] 0.034 94% < 0.001 Mean/median age ≤65 years old 11 29,657 116,098 1.27 [1.09, 1.48] 0.006 91% 65 years old 6 21,712 30,917 1.31 [0.93, 1.83] 0.100 88% 60% 9 9,391 11,467 1.50 [1.22, 1.83] 0.002 69% 0.001 ROBINS-I Low a 10 18,777 95,651 1.33 [1.13, 1.57] 0.003 91% < 0.001 Moderate 9 33,066 52,570 1.18 [0.95, 1.46] 0.126 79% < 0.001 aHR: adjusted hazard ratio, CI: confidence interval, PPI: proton pump inhibitor, ROBINS-I: Risk of Bias Assessment tool for Nonrandomized Studies of Interventions, US: United States a Nayan et al., 2018 did not report the number of patients for both PPIs and controls separately. Region-specific analyses revealed a significant association between PPI use and increased mortality in studies conducted in Europe (aHR 1.61, 95% CI: 1.20–2.16) and Asia (aHR 1.29, 95% CI: 1.03–1.62), while studies from North America showed a trend toward statistical significance in the same direction. When stratified by median age, the association between PPI use and mortality was consistent with the overall findings. The increased mortality risk associated with PPI use was evident across studies with a higher proportion of male participants (> 60% male: aHR 1.50, 95% CI: 1.22–1.82; ≤60% male: aHR 1.09, 95% CI: 0.98–1.20). Furthermore, the association appeared stronger in studies assessed as having a low risk of bias (aHR 1.33, 95% CI: 1.13–1.57) compared to those with a moderate risk of bias (aHR 1.18, 95% CI: 0.95–1.46). No studies reporting aHRs were classified as having a high risk of bias. Discussion This systematic review examined the association between PPI use and the risk of mortality in patients with kidney disease. Our meta-analysis revealed that PPI use was associated with a 26% increased risk of death among individuals with impaired kidney function compared to non-users. Particularly, among patients with kidney disease, this association was especially pronounced in studies involving those with chronic kidney disease, older adults, European or Asian populations, and long-term follow-up durations. Our findings are consistent with previous studies that focused on vulnerable populations, such as the elderly and individuals with chronic kidney disease or cardiovascular disease [ 12 , 45 – 48 ]. Previous systematic reviews involving elderly patients have shown that PPI use is associated with a significantly increased risk of all-cause mortality, including among subgroups with kidney and cardiovascular diseases [ 46 ], as well as increased risks of mortality and cardiovascular events specifically in elderly patients with cardiovascular disease [ 47 ]. Similarly, a 10-year longitudinal observational cohort study of individuals over the age of 65 found that PPI users had a significantly higher risk of all-cause mortality, including deaths related to chronic kidney disease and cardiovascular conditions, compared to H2RA users [ 12 ]. Older patients and those with chronic kidney disease often have multiple comorbidities and may be more susceptible to PPI-related adverse events due to polypharmacy and impaired drug clearance [ 48 ]. Several biological mechanisms have been proposed to explain the association between PPI use and increased mortality in patients with kidney disease. PPIs have been linked to the development and progression of chronic kidney disease, acute interstitial nephritis, and acute kidney injury through immune-mediated and ischemic pathways [ 49 , 50 ]. In addition, long-term PPI use may contribute to cardiovascular risk by inducing endothelial dysfunction, reducing nitric oxide availability, and increasing asymmetric dimethylarginine levels [ 51 ]. PPIs can also lead to hypomagnesemia and imbalances in electrolytes, which are associated with arrhythmias and sudden cardiac death, particularly in individuals with compromised renal function [ 52 ]. Furthermore, alterations in the gut microbiome and increased susceptibility to infections such as Clostridioides difficile may contribute to systemic inflammation and adverse outcomes [ 53 ]. These overlapping renal, cardiovascular, and immunological effects may partly explain the increased mortality risk observed in PPI users with kidney disease. Our subgroup analyses further highlight that this association is particularly evident in studies involving European and Asian populations, which accounted for 61% and 29% of the observed increase in mortality, respectively. These findings align with previous meta-analyses and observational studies that have also reported stronger associations in Asian and European cohorts [ 12 , 47 ]. The heightened association observed in these populations may be due to regional differences in prescribing practices, genetic factors, and healthcare systems. In many European and Asian countries, PPIs are more commonly prescribed and often available over the counter, which may contribute to prolonged or inappropriate use [ 53 , 54 ]. Furthermore, genetic polymorphisms such as CYP2C19 variants, more prevalent in Asian populations, can slow PPI metabolism, leading to increased drug exposure and a higher risk of adverse effects [ 55 , 56 ]. Additionally, the increased mortality among patients taking PPIs was 32% in studies with more than three years of follow-up. This stronger association in long-term studies may reflect the cumulative adverse effects of prolonged PPI use, which are less likely to manifest in shorter studies. Chronic PPI use has been associated with a range of long-term complications, including chronic kidney disease, micronutrient deficiencies (e.g., magnesium, vitamin B12), bone fractures, and alterations in gut microbiota that may predispose patients to infections and systemic inflammation [ 48 , 49 , 57 ]. Longer follow-up durations also allow for more robust assessment of mortality outcomes, reducing the risk of underestimating potential harm due to insufficient observation time. This meta-analysis has several notable strengths. To our knowledge, it is the first study to comprehensively evaluate the association between PPI use and mortality specifically in patients with kidney disease, based on a large, pooled sample size. The clinical relevance of our findings is further supported by real-world data from cohort studies with extended follow-up periods. We conducted extensive subgroup analyses based on follow-up duration, underlying conditions, geographic location, demographic characteristics, and risk of bias, providing detailed and comprehensive insights into potential variations in the association. The robustness of our findings is supported by stronger associations observed in high-quality studies with a low risk of bias. Notably, we found that PPI use showed a pronounced association with increased mortality among patients with chronic kidney disease, older adults, and those residing in Europe. Several limitations should be considered when interpreting our findings. First, the pooled mortality estimates showed substantial heterogeneity, which may be attributed to variations in study populations, differences in covariate adjustment, clinical practices, healthcare systems, and other unmeasured factors. To explore potential sources of this heterogeneity, we conducted multiple subgroup analyses. Despite the diversity among the studies included, the results remained consistent across subgroups. Second, due to the availability of OTC PPIs without prescriptions in some countries, approximately 50% of the included studies exhibited a moderate risk of bias in classifying the intervention. Although the association between PPI use and mortality was more pronounced in studies with a low risk of bias, a similar trend was still observed in those with moderate risk. Additionally, the reported effect estimates may be conservative, as individuals who self-administer OTC PPIs could be misclassified as either users or non-users. Third, due to limited data, we could not evaluate how the duration or dosage of PPI influences mortality risk. However, the current evidence supports an association between PPI use and increased mortality among patients with impaired renal function. Conclusions Our meta-analysis found that PPI use was associated with a higher risk of mortality in patients with kidney disease, and this association remained consistent across various subgroups, including those with chronic kidney disease, older adults, individuals in European populations, and in studies with longer follow-up durations. These findings highlight the need to raise awareness about the potential mortality risk associated with PPI use and suggest that PPIs should be prescribed with caution in patients with impaired renal function when there is no clear and justified clinical benefit. Declarations Registration The PROSPERO registration number is CRD420251063447. Author contribution IP was involved in literature search, data extraction, data analysis, data interpretation, and manuscript writing. HJ Song was involved in study concept design, literature search, data extraction, data interpretation, and manuscript writing. HJ Seo was involved in data interpretation and manuscript writing. All authors reviewed and approved the final version. Funding None Data availability The datasets generated during the current study are available from the corresponding author on reasonable request. Conflicts of interest The authors declare that they have no competing interests. Ethics approval Not applicable Consent to participate Not applicable Consent for publication Not applicable References Jager KJ, Kovesdy C, Langham R, Rosenberg M, Jha V, Zoccali C (2019) A single number for advocacy and communication—worldwide more than 850 million individuals have kidney diseases. Nephrol Dial Transplant 34(11):1803–1805. Kovesdy CP (2022) Epidemiology of chronic kidney disease: an update 2022. Kidney Int Suppl (2011) 12(1):7–11. Gries JJ, Triadafilopoulos G, Virk HUH, Khalid U, Jneid H, Birnbaum Y, Lavie CJ, Sibbing D, Levine GN, Krittanawong C (2025) Pharmaceutical and clinical implications of proton pump inhibitors with dual antiplatelet therapies: a systematic review. NPJ Gut Liver 2:2. Jiang Z, Yang Y, Zhang M, et al. (2013) Proton-pump inhibitors can decrease gastrointestinal bleeding after percutaneous coronary intervention. Clin Res Hepatol Gastroenterol 37:636–641. Huang KW, Chen CL, Lin CH, et al. (2013) Risk factors for upper gastrointestinal bleeding in coronary artery disease patients receiving both aspirin and clopidogrel. J Chin Med Assoc 76:9–14. Czikk D, Parpia Y, Roberts K, Jain G, Vu DC, Zimmerman D (2022) De-prescribing proton pump inhibitors in patients with end stage kidney disease: a quality improvement project. Can J Kidney Health Dis 9:20543581221106244. Klatte CF, Gasparini A, Xu H, de Deco P, Trevisan M, Johansson ALV, Wettermark B, Ärnlöv J, Janmaat CJ, Lindholm B, Dekker FW, Coresh J, Grams ME, Carrero JJ (2017) Association between proton pump inhibitor use and risk of progression of chronic kidney disease. Gastroenterology 153(3):702–710. Cheungpasitporn W, Thongprayoon C, Kittanamongkolchai W, et al. (2015) Proton pump inhibitors and hypomagnesemia: a meta-analysis of observational studies. Medicine (Baltimore) 94(44):e1916. Tleyjeh IM, Abdulhak AB, Riaz M, et al. (2024) Association between proton pump inhibitor therapy and Clostridioides difficile infection: a systematic review and meta-analysis. J Neurogastroenterol Motil 30(4):567–578. Nehra AK, Alexander JA, Loftus CG, Nehra V (2018) Proton pump inhibitors: review of emerging concerns. Mayo Clin Proc 93(2):240–246. Xie Y, Bowe B, Li T, Xian H, Yan Y, Al-Aly Z (2016) Proton pump inhibitors and risk of incident CKD and progression to ESRD. J Am Soc Nephrol 27(10):3153–3163. Xie Y, Bowe B, Yan Y, Xian H, Li T, Al-Aly Z (2019) Estimates of all cause mortality and cause specific mortality associated with proton pump inhibitors among US veterans: cohort study. BMJ 365:l1580. Lo CH, Lochhead P, Wu K, Chan AT, Ogino S, Giovannucci EL (2022) Proton pump inhibitors and the risk of all-cause and cause-specific mortality: a prospective cohort study. Gut 71(12):2541–2549. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP et al (2009) The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med 151(4):W65–W94. Sterne JA, Hernan MA, Reeves BC, Savović J, Berkman ND, Viswanathan M et al (2016) ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ 355:i4919. Veroniki AA, Jackson D, Viechtbauer W, et al. (2016) Methods to estimate the between-study variance and its uncertainty in meta-analysis. Res Synth Methods 7(1):55–79. Röver C, Knapp G, Friede T. (2021) Hartung–Knapp–Sidik–Jonkman approach and its modifications for random-effects meta-analysis with few studies. BMC Med Res Methodol 21(1):1–12. Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page M, Welch V (2024) Cochrane handbook for systematic reviews of interventions: the Cochrane Collaboration, Version 6.5. Available from: https://www.cochrane.org/authors/handbooks-and-manuals/handbook. Assessed 23 Jul 2025 Begg CB, Mazumdar M. (1994) Operating characteristics of a rank correlation test for publication bias. Biometrics 50(4):1088–1101. Egger M, Davey Smith G, Schneider M, et al. (1997) Bias in meta-analysis detected by a simple, graphical test. BMJ 315(7109):629–634. Ago R, Shindo T, Banshodani M, et al. (2016) Hypomagnesemia as a predictor of mortality in hemodialysis patients and the role of proton pump inhibitors: a cross-sectional, 1-year, retrospective cohort study. Hemodial Int 20(4):580–588. Assimon MM, Pun PH, Al-Khatib SM, et al. (2022) Proton pump inhibitors may enhance the risk of citalopram- and escitalopram-associated sudden cardiac death among patients receiving hemodialysis. Pharmacoepidemiol Drug Saf 31(6):670–679. Chen YC, Chen YC, Chiou WY, Yu BH. (2022) Impact of acid suppression therapy on renal and survival outcomes in patients with chronic kidney disease: a Taiwanese nationwide cohort study. J Clin Med 11(19):5612. Cholin L, Ashour T, Mehdi A, et al. (2021) Proton-pump inhibitor vs. H2-receptor blocker use and overall risk of CKD progression. BMC Nephrol 22:264. de Francisco ALM, Varas J, Ramos R, et al. (2018) Proton pump inhibitor usage and the risk of mortality in hemodialysis patients. Kidney Int Rep 3(2):374–384. Douwes RM, Gomes-Neto AW, Eisenga MF, et al. (2020) The association between use of proton-pump inhibitors and excess mortality after kidney transplantation: a cohort study. PLoS Med 17(6):e1003140. Giusti S, Lin Y, Sogbetun F, et al. (2021) The effect of proton pump inhibitor use on the course of kidney function in patients with chronic kidney disease stages G3a to G4. Am J Med Sci 362(5):453–461. Grant CH, Gillis KA, Lees JS, et al. (2019) Proton pump inhibitor use and progression to major adverse renal events: a competing risk analysis. QJM 112(11):835–840. Kang SH, Kim GO, Kim BY, et al. (2023) Effects of proton pump inhibitors on patient survival in patients undergoing maintenance hemodialysis. J Clin Med 12(14):4749. Kim SG, Cho JM, Han K, et al. (2024) Non-indicated initiation of proton pump inhibitor and risk of adverse outcomes in patients with underlying chronic kidney disease: a nationwide, retrospective, cohort study. BMJ Open 14:e078032. Kitajima A, Horie T, Onishi Y, et al. (2023) Proton pump inhibitor use is associated with adverse renal outcomes in patients with chronic kidney disease: A prospective cohort study. PLoS One 18(3):e0282291. Knorr JP, Yeung L, MacLennan G, et al. (2014) Proton pump inhibitors and risk of acute kidney injury: a systematic review and meta-analysis. BMC Nephrol 15:112. Kosedo R, Prabahar MR. (2020) Proton pump inhibitor use and its association with mortality in chronic kidney disease: a retrospective observational study. Saudi J Kidney Dis Transpl 31(4):845–851. Lalani T, Kausz AT, Li S, et al. (2017) Proton pump inhibitors and the risk of chronic kidney disease progression and mortality in dialysis patients. Kidney Int 91(2):643–653. Liabeuf S, Moranne O, Vautier V, et al. (2021) Proton pump inhibitors and short-term mortality in patients with CKD: A prospective observational study. J Am Soc Nephrol 32(4):e205. McAlister FA, Youngson E, Kaul P, et al. (2018) Postdischarge proton pump inhibitor use in patients with acute kidney injury: A population-based cohort study. CMAJ 190(44):E1293–E1299. Nayan M, Finelli A, Jewett MAS, et al. (2018) Medication use and kidney cancer survival: A population-based cohort study. Cancer Causes Control 29(3):273–281. Rassy E, Dalban C, Colomba E, et al. (2022) Efficacy and safety of concomitant proton pump inhibitor and nivolumab in renal cell carcinoma: Results of the GETUG-AFU 26 NIVOREN study. Clin Genitourin Cancer 20(5):488–494. Saeed AA, Khalid P, Muzammil M, Abbas G. (2022) Comparison of frequency of upper gastrointestinal bleeding with and without the use of proton pump inhibitors in patients of chronic kidney disease undergoing hemodialysis. Med Forum 33(3):57–60. Sharma A, Lee M, Park K, et al. (2019) The concomitant use of tyrosine kinase inhibitors and proton pump inhibitors in metastatic renal cell carcinoma. Clin Genitourin Cancer 17(3):201–208. Weng SC, Shu KH, Tarng DC, et al. (2013) In-Hospital Mortality Risk Estimation in Patients with Acute Nonvariceal Upper Gastrointestinal Bleeding Undergoing Hemodialysis: A Retrospective Cohort Study. Ren Fail 35(2):243–248. Zeng Y, Liu L, Zhu L, et al. (2022) Proton pump inhibitor usage is associated with higher all-cause mortality and CV events in peritoneal dialysis patients. Ren Fail 44(1):398–405. Shi Y, Wang Y, Su W, et al. (2020) Proton pump inhibitor use increases mortality and major adverse cardiac events in patients with chronic kidney disease: a meta-analysis. Clin Exp Pharmacol Physiol 47(4):564–571. Tsai CF, Chou CY, Chung CH, et al. (2020) Association between proton pump inhibitors use and risk of mortality in renal transplant recipients. Sci Rep 10(1):12688. Ben-Eltriki M, Green CJ, Maclure M, Musini V, Bassett KL, Wright JM (2020) Do proton pump inhibitors increase mortality? A systematic review and in-depth analysis of the evidence. Pharmacol Res Perspect 8(5):e00651. Song HJ, Seo HJ, Jiang X, Jeon N, Lee YJ, Ha IH (2024) Proton pump inhibitors associated with an increased risk of mortality in elderly: a systematic review and meta-analysis. Eur J Clin Pharmacol 80:367–382. Shiraev TP, Bullen A (2018) Proton pump inhibitors and cardiovascular events: a systematic review. Heart Lung Circ 27(4):443–450. Freedberg DE, Kim LS, Yang YX (2017) The risks and benefits of long-term use of proton pump inhibitors: expert review and best practice advice from the American Gastroenterological Association. Gastroenterology 152(4):706–715. Lazarus B, Chen Y, Wilson FP, Sang Y, Chang AR, Coresh J, Grams ME (2016) Proton pump inhibitor use and the risk of chronic kidney disease. JAMA Intern Med 176(2):238–246. Blank ML, Parkin L, Paul C, Herbison P (2014) A nationwide nested case-control study indicates an increased risk of acute interstitial nephritis with proton pump inhibitor use. Kidney Int 86(4):837–844. Ghebremariam YT, Cooke JP, Gerhart W, Griego C, Brower JB, Doyle-Eisele M, et al. (2013) Proton pump inhibitors and vascular function: a potential mechanism for increased cardiovascular risk. Vasc Med 18(5):247–253. Koulouridis I, Ku E, McCulloch CE, Tattersall J, Lin F, Chertow GM (2013) Proton pump inhibitors and risk of hypomagnesemia in chronic kidney disease. Pharmacoepidemiol Drug Saf 22(10):1128–1133. Imhann F, Bonder MJ, Vich Vila A, Fu J, Mujagic Z, Vork L, et al. (2016) Proton pump inhibitors affect the gut microbiome. Gut 65(5):740–748. Forgacs I, Loganayagam A (2008) Overprescribing proton pump inhibitors. BMJ 336(7634):2–3 Li H, Qiu X, Zhang H, et al. (2014) CYP2C19 polymorphisms affect the pharmacokinetics of omeprazole in healthy Chinese volunteers. Eur J Clin Pharmacol 70(9):1041–1046. Sugano K, Choi MG, Lin JT, et al. (2010) Systematic review of management of gastroesophageal reflux disease in Asian countries. J Gastroenterol Hepatol 25(3):319–328. Vaezi MF, Yang YX, Howden CW (2017) Complications of proton pump inhibitor therapy. Gastroenterology 153(1):35–48. Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files supplement.docx Table1.docx Cite Share Download PDF Status: Published Journal Publication published 07 Mar, 2026 Read the published version in European Journal of Clinical Pharmacology → Version 1 posted Editorial decision: Revision requested 14 Oct, 2025 Reviews received at journal 13 Oct, 2025 Reviews received at journal 10 Oct, 2025 Reviews received at journal 08 Oct, 2025 Reviewers agreed at journal 30 Sep, 2025 Reviewers agreed at journal 29 Sep, 2025 Reviewers agreed at journal 27 Sep, 2025 Reviews received at journal 26 Aug, 2025 Reviewers agreed at journal 13 Aug, 2025 Reviewers agreed at journal 11 Aug, 2025 Reviewers invited by journal 11 Aug, 2025 Editor assigned by journal 30 Jul, 2025 Submission checks completed at journal 30 Jul, 2025 First submitted to journal 24 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7206711","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":501326974,"identity":"a504849e-c3b5-4532-b65d-c551e7bee326","order_by":0,"name":"Ilsoo Park","email":"","orcid":"","institution":"Eastern University","correspondingAuthor":false,"prefix":"","firstName":"Ilsoo","middleName":"","lastName":"Park","suffix":""},{"id":501326975,"identity":"8d00fc80-776c-40f6-a575-2e18188f96d3","order_by":1,"name":"Hyun Jin Song","email":"","orcid":"","institution":"University of Florida","correspondingAuthor":false,"prefix":"","firstName":"Hyun","middleName":"Jin","lastName":"Song","suffix":""},{"id":501326976,"identity":"07be45a1-c480-44aa-89ef-32dfc80d8804","order_by":2,"name":"Hyun-Ju Seo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYBACA4YDQLJCQg4hQJyWMzbGpGgBAsa2tMQGorWYMx5/+OAD2+H0/tk9Bgw/ahiMzRsIaLFsOGNsOIPncO6MO2cMGHuOMZjJHCDksANn2KR5JA7nbpDIMWDgbWCwkSDkMIMDx5//5jE4nG4A1ML4lzgtB8yYeRLSEkBamIG2mBGh5Yyx5IwDNoYzbqQVHJY5JmFMWMuN4w8/fPwnIc8/I3njwzc1QL2EtDBIHECwgUyCdgABfwMRikbBKBgFo2BkAwDphz8/TmWdyQAAAABJRU5ErkJggg==","orcid":"","institution":"Chungnam National University","correspondingAuthor":true,"prefix":"","firstName":"Hyun-Ju","middleName":"","lastName":"Seo","suffix":""}],"badges":[],"createdAt":"2025-07-24 14:38:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7206711/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7206711/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00228-026-04022-w","type":"published","date":"2026-03-07T15:59:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89380545,"identity":"92122c60-2659-4048-aed5-2205d44cf109","added_by":"auto","created_at":"2025-08-19 11:49:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":432406,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA flow diagram of study selections\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7206711/v1/f4742087951e766e1b441e5a.png"},{"id":89378725,"identity":"82b64bf1-b1e4-4b8c-95ad-b5e1e4167f99","added_by":"auto","created_at":"2025-08-19 11:33:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3101456,"visible":true,"origin":"","legend":"\u003cp\u003eThe Risk of Bias In Non-randomized Studies - of Interventions (ROBINS-I). (A) graph, (B) summary\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7206711/v1/3ccf2b7216d41bc5c9d25416.png"},{"id":89380113,"identity":"8b0e4b57-262d-40ef-9f6e-2a6b52c07075","added_by":"auto","created_at":"2025-08-19 11:41:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2283597,"visible":true,"origin":"","legend":"\u003cp\u003eTheassociation between proton pump inhibitors and mortality. (A) unadjusted risk ratio in randomized controlled trials, (B) unadjusted risk ratio in observational studies, (C) adjusted risk ratio in randomized controlled trials, (D) adjusted risk ratio in observational studies\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7206711/v1/424127be7f57243e3dbee6f6.png"},{"id":89378722,"identity":"f9c941c3-cbe1-4356-9a6b-fbe93bdc96fd","added_by":"auto","created_at":"2025-08-19 11:33:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":255316,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plot of observational studies. (A) unadjusted risk ratio, (B) adjusted risk ratio\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7206711/v1/c56f7a64311fb37b5880e842.png"},{"id":104251399,"identity":"5e681609-378e-459f-9cf2-2ddccfb67c87","added_by":"auto","created_at":"2026-03-09 16:13:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7700823,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7206711/v1/889ddd9a-3f86-429c-8bdf-d92b21f5ad79.pdf"},{"id":89378719,"identity":"73731537-d293-4c92-b0d5-69e1045f9780","added_by":"auto","created_at":"2025-08-19 11:33:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":48982,"visible":true,"origin":"","legend":"","description":"","filename":"supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-7206711/v1/2c7b392d2fc461953e762faa.docx"},{"id":89380112,"identity":"22d1b0d0-006b-49c7-894a-379c314d05c1","added_by":"auto","created_at":"2025-08-19 11:41:48","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":61292,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7206711/v1/62f4666d3ef09673b45ec895.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The association between proton pump inhibitor use and the risk of mortality in patients with kidney disease: a systematic review and meta-analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlobally, more than 850\u0026nbsp;million people are affected by chronic kidney disease, acute kidney injury, or are undergoing dialysis or renal transplant [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The prevalence of kidney disease has been increasing, driven by factors such as aging populations, diabetes, and hypertension [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePatients with kidney disease are frequently prescribed proton pump inhibitors (PPIs) to manage gastrointestinal conditions like gastroesophageal reflux disease, peptic ulcers, and to prevent upper gastrointestinal bleeding, especially when on antiplatelet or anticoagulant therapies [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e–\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, emerging evidence has raised concerns about the long-term safety of PPIs, particularly in individuals with compromised renal function [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Long-term PPI use has been associated with several adverse effects, including hypomagnesemia, Clostridioides difficile infection, pneumonia, bone fractures, and progression of kidney disease [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e–\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These risks may be amplified in CKD patients due to altered drug metabolism and increased susceptibility to complications.\u003c/p\u003e\u003cp\u003eRecent studies have suggested a potential link between PPI use and increased all-cause mortality. An analysis of data from 214,467 individuals found that PPI users had a higher risk of chronic kidney disease-related mortality compared to those using H2 blockers [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. A large prospective cohort study in the US also reported significantly higher risks of all-cause mortality and mortality due to renal disease among PPI users [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, the evidence remains inconclusive. While previous studies have primarily focused on the general population, no systematic review or meta-analysis has specifically evaluated the association between PPI use and mortality in patients with impaired renal function.\u003c/p\u003e\u003cp\u003eGiven the widespread use of PPIs among patients with kidney disease and the potential for serious adverse outcomes, it is crucial to comprehensively assess the association between PPI use and mortality risk in this population. Therefore, we conducted a systematic review and meta-analysis to evaluate the association between PPI use and the risk of all-cause mortality in patients with kidney disease.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eLiterature Search and Study Selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a comprehensive literature search of Ovid-MEDLINE, Ovid-EMBASE, and the Cochrane CENTRAL to identify relevant articles published up to April 24, 2025. The search strategy included a combination of MeSH terms and free-text keywords related to the patient population (e.g., \u003cem\u003e\u0026ldquo;kidney disease,\u0026rdquo; \u0026ldquo;renal failure,\u0026rdquo; \u0026ldquo;dialysis\u0026rdquo;\u003c/em\u003e) and the intervention of interest (\u003cem\u003eproton pump inhibitors\u003c/em\u003e), including both generic and brand names (\u003cem\u003ebenatoprazole, dexlansoprazole, esomeprazole, lansoprazole, omeprazole, pantoprazole, rabeprazole, tenatoprazole\u003c/em\u003e). The full search strategy is provided in Supplement Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eWe included studies that met all of the following criteria: 1) evaluated the association between PPI use and the risk of mortality among patients with kidney disease; 2) compared PPIs with a control group (e.g., placebo or active comparator); 3) reported either the number of deaths in both groups or a hazard ratio (HR) for mortality; 4) employed a randomized controlled trial (RCT), non-randomized controlled study, or observational study design; 5) were published in English. We excluded non-original research articles, including case reports and series, editorials, narrative or systematic reviews, and conference abstracts. Additionally, studies were excluded if they did not report either the number of deaths or the hazard ratio comparing PPI and control groups.\u003c/p\u003e\n\u003cp\u003eTwo reviewers independently screened titles and abstracts, followed by full-text assessment of potentially eligible studies. Any discrepancies were resolved through discussion or adjudication by a third reviewer. This systematic review was registered in PROSPERO (CRD420251063447), and we adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines throughout the review process [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuality Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo independent researchers assessed the quality of the included studies. The Risk of Bias In Non-randomized Studies - of Interventions (ROBINS-I) was applied to evaluate observational studies. ROBINS-I evaluates seven items across three domains: pre-intervention, at-intervention, and post-intervention domains [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. Pre-intervention domain covers bias due to confounding and bias in selection of participants into the study. The at-intervention domain assesses bias in the classification of intervention. The post-intervention domain addresses bias due to deviations from intended interventions, bias due to missing data, bias in measurement of the outcome, and bias in selection of the reported result. We included an overall risk of bias assessment based on seven items. Each study was rated as having low, moderate, serious risk of bias.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom each included study, we extracted information on demographic characteristics, including country, study design, data source, study period, mean age, and the proportion of male participants. We also collected data on exposure, such as the definition and number of PPI users and controls, duration of follow-up, and concomitant medication use. Outcome data included the number of deaths in both the PPI and comparator groups, as well as the reported HRs for mortality. When applicable, confounding variables adjusted for in the regression analyses used to calculate hazard ratios were also documented.\u003c/p\u003e\n\u003cp\u003eThe primary outcome was the risk of mortality associated with PPI use comparing nonusers. For the meta-analysis, we prioritized the most fully adjusted effect estimates (i.e., adjusted hazard ratios [HRs]) along with their corresponding 95% confidence intervals (CIs), accounting for confounders reported in each study. Unadjusted estimates were also extracted for the two groups.\u003c/p\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eTo estimate the pooled relative risks (RRs) or HRs with corresponding 95% CIs, we used a random-effects model based on inverse-variance weighting, applying the Hartung-Knapp-Sidik-Jonkman adjustment for CIs and the Sidik-Jonkman estimator to calculate the between-study variance (\u0026tau;\u0026sup2;). This Sidik-Jonkman estimator is considered more robust in the presence of substantial heterogeneity and varying study sizes, as it provides more conservative estimates and reduces the risk of false positives [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eStatistical heterogeneity was assessed using the I\u0026sup2; statistic and Cochran\u0026rsquo;s Q test. An I\u0026sup2; value greater than 50% was interpreted as indicating substantial heterogeneity [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e], and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for the Q test was considered statistically significant. To assess potential publication bias, we visually inspected funnel plots, which may reveal asymmetry due to the preferential publication of studies with positive findings.\u003c/p\u003e\n\u003cp\u003eAmong included studies, Kang et al. shared a non-user comparator group for both the \u0026gt;\u0026thinsp;90 days and \u0026le;\u0026thinsp;90 days exposure groups; therefore, we divided the sample size and number of events in the comparator group equally across the relevant comparisons to prevent double-counting and preserve the independence of comparisons within the meta-analysis [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e]. To assess potential publication bias, we visually inspected funnel plots for asymmetry, which may suggest the preferential publication of studies with positive findings. In addition, we conducted Begg\u0026rsquo;s rank correlation test and Egger\u0026rsquo;s regression asymmetry test. A p-value of less than 0.10 was considered indicative of potential publication bias for both tests [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eWe conducted subgroup analyses of aHRs to explore potential sources of heterogeneity and to assess whether the association between PPI use and mortality varied across different study-level and population characteristics. Subgroups were defined based on follow-up duration (\u0026le;\u0026thinsp;3 years vs. \u0026gt;3 years), mean or median age of study participants (\u0026le;\u0026thinsp;65 vs. \u0026gt;65 years), and the proportion of male participants in each study (\u0026le;\u0026thinsp;60% vs. \u0026gt;60%). To further explore disease-specific mortality risk, we evaluated the association between PPI use and mortality outcomes separately for patient subgroups, including individuals with chronic kidney disease, dialysis, kidney transplant, or renal cancer. To account for differences in healthcare systems and clinical practice patterns, subgroup analyses were also stratified by region (United States/Canada, Europe, and Asia). Additionally, we examined whether study quality influenced the pooled estimates by performing subgroup analyses according to risk of bias, comparing studies classified as having low versus moderate risk; no studies reporting aHRs were categorized as serious risk of bias.\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using R version 4.4.1 (R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eLiterature Search\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAn initial search identified 5,308 articles. After removing 608 duplicates, 4,700 unique records remained for screening (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Of these, 4,630 articles were excluded during the title and abstract screening. An additional 46 articles were excluded after full-text review due to one or more of the following reasons: absence of kidney disease, no exposure to PPI therapy, lack of a comparator group, ineligible study design, no relevant outcomes reported, non-original research, or publication in a non-English language. Ultimately, 27 cohorts from 24 studies were included in the systematic review [\u003cspan additionalcitationids=\"CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33 CR34 CR35 CR36 CR37 CR38 CR39 CR40 CR41 CR42 CR43\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], with three studies contributing two cohorts each [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. For the meta-analysis, 20 cohorts from 17 studies were included for unadjusted RRs of mortality, and 20 cohorts from 18 studies were included for aHRs of mortality.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eGeneral Characteristics of the Included Studies\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 22 cohort studies and 2 ad hoc analyses of clinical trials were included in the review (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The intervention group comprised patients receiving PPIs, with comparators being either placebo or histamine-2 receptor antagonists (H2RAs). The studies were conducted in North America (United States and Canada), Europe (Spain, Netherlands, Belgium, United Kingdom, and France), and Asia (Japan, Taiwan, South Korea, Pakistan, and China). Study populations included patients on dialysis (n\u0026thinsp;=\u0026thinsp;10), with chronic kidney disease (n\u0026thinsp;=\u0026thinsp;7), kidney transplant recipients (n\u0026thinsp;=\u0026thinsp;2), and individuals with renal cancer (n\u0026thinsp;=\u0026thinsp;5). In studies of renal cancer, comedications included tyrosine kinase inhibitors and immune checkpoint inhibitors. Altogether, the included studies enrolled 216,032 participants, with median ages ranging from 53 to 73 years and the proportion of male participants ranging from 36\u0026ndash;99%. The duration of follow-up ranged from 4.4 months to 5.6 years. Most studies adjusted for potential confounders in their estimation of HRs, including baseline demographics, clinical characteristics, comorbidities, and concomitant medication use.\u003c/p\u003e\u003cp\u003e\u003cb\u003eQuality Assessment\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll included cohort studies were assessed as having a low risk of bias in the following domains: selection of participants, deviations from intended interventions, missing data, measurement of outcomes, and selection of reported results (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The risk of bias for outcome measurement was considered low, as mortality is an objective outcome unlikely to be influenced by measurement methods. However, approximately half of the studies were rated as having a moderate risk of bias in the classification of interventions, primarily due to the potential for over the counter (OTC) use of PPIs, which may not have been fully captured. Four studies were judged to have a serious risk of bias due to confounding, as they did not report adjusted hazard ratios accounting for potential confounders. Overall, 37.5% of studies were rated as having a low risk of bias, 37.5% as moderate, and 25% as serious.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eProton Pump Inhibitors and Mortality\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmong 20 cohorts from 17 studies reporting unadjusted mortality rates, the death rate was 23.2% among PPI users (15,755 of 67,853) and 22.1% among non-users (28,986 of 131,009). PPI use was significantly associated with an increased risk of mortality in unadjusted analyses (RR 1.28, 95% CI: 1.06\u0026ndash;1.55), with substantial heterogeneity observed across studies (I\u0026sup2; = 95%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Funnel plot analysis, Begg test (p\u0026thinsp;=\u0026thinsp;0.190), and Egger test (p\u0026thinsp;=\u0026thinsp;0.130) showed no indication of publication bias (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor adjusted analyses, 20 cohorts from 18 studies comprising 167,053 individuals with kidney impairment were included. PPI use remained significantly associated with a higher risk of mortality compared to non-use (adjusted HR 1.26, 95% CI: 1.12\u0026ndash;1.43) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Considerable heterogeneity was present (I\u0026sup2; = 88%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and no evidence of publication bias was detected in the corresponding funnel plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Begg\u0026rsquo;s test did not indicate significant publication bias (p\u0026thinsp;=\u0026thinsp;0.105), whereas Egger\u0026rsquo;s test suggested potential publication bias (p\u0026thinsp;=\u0026thinsp;0.013).\u003c/p\u003e\u003cp\u003e\u003cb\u003eSubgroup analyses\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSubgroup analyses of aHRs were conducted across observational studies. Among individuals with kidney impairment, PPI use was significantly associated with an increased risk of mortality during both shorter (\u0026le;\u0026thinsp;3 years; aHR 1.23, 95% CI: 1.06\u0026ndash;1.43) and longer follow-up periods (\u0026gt;\u0026thinsp;3 years; aHR 1.32, 95% CI: 1.04\u0026ndash;1.69) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Similar trends were observed across patient subgroups, including those on dialysis, with chronic kidney disease, and individuals with renal cancer, with the associations approaching statistical significance.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSubgroup analysis of the association between proton pump inhibitors and the adjusted risk of mortality\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCohort,\u003c/p\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePPI,\u003c/p\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eControl,\u003c/p\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRandom effects,\u003c/p\u003e\u003cp\u003eaHR [95% CI]\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEffect,\u003c/p\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eI\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHeterogeneity, \u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFollow up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;3 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14,333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26,397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.23 [1.06, 1.43]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e40%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.128\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;3 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37.080\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e119,654\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.32 [1.04, 1.69]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e94%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePatients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDialysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34,072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e116,979\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.18 [0.97,1.42]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e65%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic kidney disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16,432\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26,879\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.46 [0.95\u0026ndash;2.25]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e97%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKidney transplant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e727\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e632\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.56 [0.51, 4.74]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.524\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRenal cancer\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e612\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3,731\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.10 [0.92\u0026ndash;1.32]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.203\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e37%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.175\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCountries\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUS/Canada\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21,194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40,947\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.05 [0.95, 1.15]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e42%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.111\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEurope\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3,680\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3,651\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.61 [1.20, 2.16]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e54%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.070\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsia \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26,969\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e103,623\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.29 [1.03, 1.62]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e94%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean/median age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;65 years old\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29,657\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e116,098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.27 [1.09, 1.48]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e91%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;65 years old\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21,712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30,917\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.31 [0.93, 1.83]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e88%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePercentage of male\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;60% \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41,978\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e135,548\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.09 [0.98, 1.20]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e69%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;60%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9,391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11,467\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.50 [1.22, 1.83]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e69%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eROBINS-I\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18,777\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e95,651\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.33 [1.13, 1.57]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e91%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33,066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e52,570\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.18 [0.95, 1.46]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e79%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eaHR: adjusted hazard ratio, CI: confidence interval, PPI: proton pump inhibitor, ROBINS-I: Risk of Bias Assessment tool for Nonrandomized Studies of Interventions, US: United States\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003ea\u003c/sup\u003eNayan et al., 2018 did not report the number of patients for both PPIs and controls separately.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eRegion-specific analyses revealed a significant association between PPI use and increased mortality in studies conducted in Europe (aHR 1.61, 95% CI: 1.20\u0026ndash;2.16) and Asia (aHR 1.29, 95% CI: 1.03\u0026ndash;1.62), while studies from North America showed a trend toward statistical significance in the same direction. When stratified by median age, the association between PPI use and mortality was consistent with the overall findings.\u003c/p\u003e\u003cp\u003eThe increased mortality risk associated with PPI use was evident across studies with a higher proportion of male participants (\u0026gt;\u0026thinsp;60% male: aHR 1.50, 95% CI: 1.22\u0026ndash;1.82; \u0026le;60% male: aHR 1.09, 95% CI: 0.98\u0026ndash;1.20). Furthermore, the association appeared stronger in studies assessed as having a low risk of bias (aHR 1.33, 95% CI: 1.13\u0026ndash;1.57) compared to those with a moderate risk of bias (aHR 1.18, 95% CI: 0.95\u0026ndash;1.46). No studies reporting aHRs were classified as having a high risk of bias.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis systematic review examined the association between PPI use and the risk of mortality in patients with kidney disease. Our meta-analysis revealed that PPI use was associated with a 26% increased risk of death among individuals with impaired kidney function compared to non-users. Particularly, among patients with kidney disease, this association was especially pronounced in studies involving those with chronic kidney disease, older adults, European or Asian populations, and long-term follow-up durations.\u003c/p\u003e\u003cp\u003eOur findings are consistent with previous studies that focused on vulnerable populations, such as the elderly and individuals with chronic kidney disease or cardiovascular disease [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR46 CR47\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Previous systematic reviews involving elderly patients have shown that PPI use is associated with a significantly increased risk of all-cause mortality, including among subgroups with kidney and cardiovascular diseases [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], as well as increased risks of mortality and cardiovascular events specifically in elderly patients with cardiovascular disease [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Similarly, a 10-year longitudinal observational cohort study of individuals over the age of 65 found that PPI users had a significantly higher risk of all-cause mortality, including deaths related to chronic kidney disease and cardiovascular conditions, compared to H2RA users [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Older patients and those with chronic kidney disease often have multiple comorbidities and may be more susceptible to PPI-related adverse events due to polypharmacy and impaired drug clearance [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSeveral biological mechanisms have been proposed to explain the association between PPI use and increased mortality in patients with kidney disease. PPIs have been linked to the development and progression of chronic kidney disease, acute interstitial nephritis, and acute kidney injury through immune-mediated and ischemic pathways [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. In addition, long-term PPI use may contribute to cardiovascular risk by inducing endothelial dysfunction, reducing nitric oxide availability, and increasing asymmetric dimethylarginine levels [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. PPIs can also lead to hypomagnesemia and imbalances in electrolytes, which are associated with arrhythmias and sudden cardiac death, particularly in individuals with compromised renal function [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Furthermore, alterations in the gut microbiome and increased susceptibility to infections such as Clostridioides difficile may contribute to systemic inflammation and adverse outcomes [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. These overlapping renal, cardiovascular, and immunological effects may partly explain the increased mortality risk observed in PPI users with kidney disease.\u003c/p\u003e\u003cp\u003eOur subgroup analyses further highlight that this association is particularly evident in studies involving European and Asian populations, which accounted for 61% and 29% of the observed increase in mortality, respectively. These findings align with previous meta-analyses and observational studies that have also reported stronger associations in Asian and European cohorts [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The heightened association observed in these populations may be due to regional differences in prescribing practices, genetic factors, and healthcare systems. In many European and Asian countries, PPIs are more commonly prescribed and often available over the counter, which may contribute to prolonged or inappropriate use [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Furthermore, genetic polymorphisms such as CYP2C19 variants, more prevalent in Asian populations, can slow PPI metabolism, leading to increased drug exposure and a higher risk of adverse effects [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAdditionally, the increased mortality among patients taking PPIs was 32% in studies with more than three years of follow-up. This stronger association in long-term studies may reflect the cumulative adverse effects of prolonged PPI use, which are less likely to manifest in shorter studies. Chronic PPI use has been associated with a range of long-term complications, including chronic kidney disease, micronutrient deficiencies (e.g., magnesium, vitamin B12), bone fractures, and alterations in gut microbiota that may predispose patients to infections and systemic inflammation [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Longer follow-up durations also allow for more robust assessment of mortality outcomes, reducing the risk of underestimating potential harm due to insufficient observation time.\u003c/p\u003e\u003cp\u003eThis meta-analysis has several notable strengths. To our knowledge, it is the first study to comprehensively evaluate the association between PPI use and mortality specifically in patients with kidney disease, based on a large, pooled sample size. The clinical relevance of our findings is further supported by real-world data from cohort studies with extended follow-up periods. We conducted extensive subgroup analyses based on follow-up duration, underlying conditions, geographic location, demographic characteristics, and risk of bias, providing detailed and comprehensive insights into potential variations in the association. The robustness of our findings is supported by stronger associations observed in high-quality studies with a low risk of bias. Notably, we found that PPI use showed a pronounced association with increased mortality among patients with chronic kidney disease, older adults, and those residing in Europe.\u003c/p\u003e\u003cp\u003eSeveral limitations should be considered when interpreting our findings. First, the pooled mortality estimates showed substantial heterogeneity, which may be attributed to variations in study populations, differences in covariate adjustment, clinical practices, healthcare systems, and other unmeasured factors. To explore potential sources of this heterogeneity, we conducted multiple subgroup analyses. Despite the diversity among the studies included, the results remained consistent across subgroups. Second, due to the availability of OTC PPIs without prescriptions in some countries, approximately 50% of the included studies exhibited a moderate risk of bias in classifying the intervention. Although the association between PPI use and mortality was more pronounced in studies with a low risk of bias, a similar trend was still observed in those with moderate risk. Additionally, the reported effect estimates may be conservative, as individuals who self-administer OTC PPIs could be misclassified as either users or non-users. Third, due to limited data, we could not evaluate how the duration or dosage of PPI influences mortality risk. However, the current evidence supports an association between PPI use and increased mortality among patients with impaired renal function.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur meta-analysis found that PPI use was associated with a higher risk of mortality in patients with kidney disease, and this association remained consistent across various subgroups, including those with chronic kidney disease, older adults, individuals in European populations, and in studies with longer follow-up durations. These findings highlight the need to raise awareness about the potential mortality risk associated with PPI use and suggest that PPIs should be prescribed with caution in patients with impaired renal function when there is no clear and justified clinical benefit.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eRegistration\u0026nbsp;\u003c/strong\u003eThe PROSPERO registration number is CRD420251063447.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAuthor contribution\u0026nbsp;\u003c/strong\u003eIP was involved in literature search, data extraction, data analysis, data interpretation, and manuscript writing. HJ Song was involved in study concept design, literature search, data extraction, data interpretation, and manuscript writing. HJ Seo was involved in data interpretation and manuscript writing. All authors reviewed and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e The authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e Not applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJager KJ, Kovesdy C, Langham R, Rosenberg M, Jha V, Zoccali C (2019) A single number for advocacy and communication\u0026mdash;worldwide more than 850 million individuals have kidney diseases. Nephrol Dial Transplant 34(11):1803\u0026ndash;1805.\u003c/li\u003e\n\u003cli\u003eKovesdy CP (2022) Epidemiology of chronic kidney disease: an update 2022. Kidney Int Suppl (2011) 12(1):7\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eGries JJ, Triadafilopoulos G, Virk HUH, Khalid U, Jneid H, Birnbaum Y, Lavie CJ, Sibbing D, Levine GN, Krittanawong C (2025) Pharmaceutical and clinical implications of proton pump inhibitors with dual antiplatelet therapies: a systematic review. NPJ Gut Liver 2:2.\u003c/li\u003e\n\u003cli\u003eJiang Z, Yang Y, Zhang M, et al. (2013) Proton-pump inhibitors can decrease gastrointestinal bleeding after percutaneous coronary intervention. Clin Res Hepatol Gastroenterol 37:636\u0026ndash;641.\u003c/li\u003e\n\u003cli\u003eHuang KW, Chen CL, Lin CH, et al. (2013) Risk factors for upper gastrointestinal bleeding in coronary artery disease patients receiving both aspirin and clopidogrel. J Chin Med Assoc 76:9\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eCzikk D, Parpia Y, Roberts K, Jain G, Vu DC, Zimmerman D (2022) De-prescribing proton pump inhibitors in patients with end stage kidney disease: a quality improvement project. Can J Kidney Health Dis 9:20543581221106244.\u003c/li\u003e\n\u003cli\u003eKlatte CF, Gasparini A, Xu H, de Deco P, Trevisan M, Johansson ALV, Wettermark B, \u0026Auml;rnl\u0026ouml;v J, Janmaat CJ, Lindholm B, Dekker FW, Coresh J, Grams ME, Carrero JJ (2017) Association between proton pump inhibitor use and risk of progression of chronic kidney disease. Gastroenterology 153(3):702\u0026ndash;710.\u003c/li\u003e\n\u003cli\u003eCheungpasitporn W, Thongprayoon C, Kittanamongkolchai W, et al. (2015) Proton pump inhibitors and hypomagnesemia: a meta-analysis of observational studies. Medicine (Baltimore) 94(44):e1916.\u003c/li\u003e\n\u003cli\u003eTleyjeh IM, Abdulhak AB, Riaz M, et al. (2024) Association between proton pump inhibitor therapy and Clostridioides difficile infection: a systematic review and meta-analysis. J Neurogastroenterol Motil 30(4):567\u0026ndash;578.\u003c/li\u003e\n\u003cli\u003eNehra AK, Alexander JA, Loftus CG, Nehra V (2018) Proton pump inhibitors: review of emerging concerns. Mayo Clin Proc 93(2):240\u0026ndash;246.\u003c/li\u003e\n\u003cli\u003eXie Y, Bowe B, Li T, Xian H, Yan Y, Al-Aly Z (2016) Proton pump inhibitors and risk of incident CKD and progression to ESRD. J Am Soc Nephrol 27(10):3153\u0026ndash;3163.\u003c/li\u003e\n\u003cli\u003eXie Y, Bowe B, Yan Y, Xian H, Li T, Al-Aly Z (2019) Estimates of all cause mortality and cause specific mortality associated with proton pump inhibitors among US veterans: cohort study. BMJ 365:l1580.\u003c/li\u003e\n\u003cli\u003eLo CH, Lochhead P, Wu K, Chan AT, Ogino S, Giovannucci EL (2022) Proton pump inhibitors and the risk of all-cause and cause-specific mortality: a prospective cohort study. \u003cem\u003eGut\u003c/em\u003e 71(12):2541\u0026ndash;2549.\u003c/li\u003e\n\u003cli\u003eLiberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP et al (2009) The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med 151(4):W65\u0026ndash;W94.\u003c/li\u003e\n\u003cli\u003eSterne JA, Hernan MA, Reeves BC, Savović J, Berkman ND, Viswanathan M et al (2016) ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ 355:i4919.\u003c/li\u003e\n\u003cli\u003eVeroniki AA, Jackson D, Viechtbauer W, et al. (2016) Methods to estimate the between-study variance and its uncertainty in meta-analysis. Res Synth Methods 7(1):55\u0026ndash;79.\u003c/li\u003e\n\u003cli\u003eR\u0026ouml;ver C, Knapp G, Friede T. (2021) Hartung\u0026ndash;Knapp\u0026ndash;Sidik\u0026ndash;Jonkman approach and its modifications for random-effects meta-analysis with few studies. BMC Med Res Methodol 21(1):1\u0026ndash;12.\u003c/li\u003e\n\u003cli\u003eHiggins J, Thomas J, Chandler J, Cumpston M, Li T, Page M, Welch V (2024) Cochrane handbook for systematic reviews of interventions: the Cochrane Collaboration, Version 6.5. Available from: https://www.cochrane.org/authors/handbooks-and-manuals/handbook. Assessed 23 Jul 2025\u003c/li\u003e\n\u003cli\u003eBegg CB, Mazumdar M. (1994) Operating characteristics of a rank correlation test for publication bias. \u003cem\u003eBiometrics\u003c/em\u003e 50(4):1088\u0026ndash;1101. \u003c/li\u003e\n\u003cli\u003eEgger M, Davey Smith G, Schneider M, et al. (1997) Bias in meta-analysis detected by a simple, graphical test. \u003cem\u003eBMJ \u003c/em\u003e315(7109):629\u0026ndash;634. \u003c/li\u003e\n\u003cli\u003eAgo R, Shindo T, Banshodani M, et al. (2016) Hypomagnesemia as a predictor of mortality in hemodialysis patients and the role of proton pump inhibitors: a cross-sectional, 1-year, retrospective cohort study. Hemodial Int 20(4):580\u0026ndash;588.\u003c/li\u003e\n\u003cli\u003eAssimon MM, Pun PH, Al-Khatib SM, et al. (2022) Proton pump inhibitors may enhance the risk of citalopram- and escitalopram-associated sudden cardiac death among patients receiving hemodialysis. Pharmacoepidemiol Drug Saf 31(6):670\u0026ndash;679.\u003c/li\u003e\n\u003cli\u003eChen YC, Chen YC, Chiou WY, Yu BH. (2022) Impact of acid suppression therapy on renal and survival outcomes in patients with chronic kidney disease: a Taiwanese nationwide cohort study. J Clin Med 11(19):5612.\u003c/li\u003e\n\u003cli\u003eCholin L, Ashour T, Mehdi A, et al. (2021) Proton-pump inhibitor vs. H2-receptor blocker use and overall risk of CKD progression. BMC Nephrol 22:264.\u003c/li\u003e\n\u003cli\u003ede Francisco ALM, Varas J, Ramos R, et al. (2018) Proton pump inhibitor usage and the risk of mortality in hemodialysis patients. Kidney Int Rep 3(2):374\u0026ndash;384.\u003c/li\u003e\n\u003cli\u003eDouwes RM, Gomes-Neto AW, Eisenga MF, et al. (2020) The association between use of proton-pump inhibitors and excess mortality after kidney transplantation: a cohort study. PLoS Med 17(6):e1003140.\u003c/li\u003e\n\u003cli\u003eGiusti S, Lin Y, Sogbetun F, et al. (2021) The effect of proton pump inhibitor use on the course of kidney function in patients with chronic kidney disease stages G3a to G4. Am J Med Sci 362(5):453\u0026ndash;461.\u003c/li\u003e\n\u003cli\u003eGrant CH, Gillis KA, Lees JS, et al. (2019) Proton pump inhibitor use and progression to major adverse renal events: a competing risk analysis. QJM 112(11):835\u0026ndash;840.\u003c/li\u003e\n\u003cli\u003eKang SH, Kim GO, Kim BY, et al. (2023) Effects of proton pump inhibitors on patient survival in patients undergoing maintenance hemodialysis. J Clin Med 12(14):4749.\u003c/li\u003e\n\u003cli\u003eKim SG, Cho JM, Han K, et al. (2024) Non-indicated initiation of proton pump inhibitor and risk of adverse outcomes in patients with underlying chronic kidney disease: a nationwide, retrospective, cohort study. BMJ Open 14:e078032.\u003c/li\u003e\n\u003cli\u003eKitajima A, Horie T, Onishi Y, et al. (2023) Proton pump inhibitor use is associated with adverse renal outcomes in patients with chronic kidney disease: A prospective cohort study. PLoS One 18(3):e0282291.\u003c/li\u003e\n\u003cli\u003eKnorr JP, Yeung L, MacLennan G, et al. (2014) Proton pump inhibitors and risk of acute kidney injury: a systematic review and meta-analysis. BMC Nephrol 15:112.\u003c/li\u003e\n\u003cli\u003eKosedo R, Prabahar MR. (2020) Proton pump inhibitor use and its association with mortality in chronic kidney disease: a retrospective observational study. Saudi J Kidney Dis Transpl 31(4):845\u0026ndash;851.\u003c/li\u003e\n\u003cli\u003eLalani T, Kausz AT, Li S, et al. (2017) Proton pump inhibitors and the risk of chronic kidney disease progression and mortality in dialysis patients. Kidney Int 91(2):643\u0026ndash;653.\u003c/li\u003e\n\u003cli\u003eLiabeuf S, Moranne O, Vautier V, et al. (2021) Proton pump inhibitors and short-term mortality in patients with CKD: A prospective observational study. J Am Soc Nephrol 32(4):e205.\u003c/li\u003e\n\u003cli\u003eMcAlister FA, Youngson E, Kaul P, et al. (2018) Postdischarge proton pump inhibitor use in patients with acute kidney injury: A population-based cohort study. CMAJ 190(44):E1293\u0026ndash;E1299.\u003c/li\u003e\n\u003cli\u003eNayan M, Finelli A, Jewett MAS, et al. (2018) Medication use and kidney cancer survival: A population-based cohort study. Cancer Causes Control 29(3):273\u0026ndash;281.\u003c/li\u003e\n\u003cli\u003eRassy E, Dalban C, Colomba E, et al. (2022) Efficacy and safety of concomitant proton pump inhibitor and nivolumab in renal cell carcinoma: Results of the GETUG-AFU 26 NIVOREN study. Clin Genitourin Cancer 20(5):488\u0026ndash;494.\u003c/li\u003e\n\u003cli\u003eSaeed AA, Khalid P, Muzammil M, Abbas G. (2022) Comparison of frequency of upper gastrointestinal bleeding with and without the use of proton pump inhibitors in patients of chronic kidney disease undergoing hemodialysis. Med Forum 33(3):57\u0026ndash;60.\u003c/li\u003e\n\u003cli\u003eSharma A, Lee M, Park K, et al. (2019) The concomitant use of tyrosine kinase inhibitors and proton pump inhibitors in metastatic renal cell carcinoma. Clin Genitourin Cancer 17(3):201\u0026ndash;208.\u003c/li\u003e\n\u003cli\u003eWeng SC, Shu KH, Tarng DC, et al. (2013) In-Hospital Mortality Risk Estimation in Patients with Acute Nonvariceal Upper Gastrointestinal Bleeding Undergoing Hemodialysis: A Retrospective Cohort Study. Ren Fail 35(2):243\u0026ndash;248.\u003c/li\u003e\n\u003cli\u003eZeng Y, Liu L, Zhu L, et al. (2022) Proton pump inhibitor usage is associated with higher all-cause mortality and CV events in peritoneal dialysis patients. Ren Fail 44(1):398\u0026ndash;405.\u003c/li\u003e\n\u003cli\u003eShi Y, Wang Y, Su W, et al. (2020) Proton pump inhibitor use increases mortality and major adverse cardiac events in patients with chronic kidney disease: a meta-analysis. Clin Exp Pharmacol Physiol 47(4):564\u0026ndash;571.\u003c/li\u003e\n\u003cli\u003eTsai CF, Chou CY, Chung CH, et al. (2020) Association between proton pump inhibitors use and risk of mortality in renal transplant recipients. Sci Rep 10(1):12688.\u003c/li\u003e\n\u003cli\u003eBen-Eltriki M, Green CJ, Maclure M, Musini V, Bassett KL, Wright JM (2020) Do proton pump inhibitors increase mortality? A systematic review and in-depth analysis of the evidence. Pharmacol Res Perspect 8(5):e00651.\u003c/li\u003e\n\u003cli\u003eSong HJ, Seo HJ, Jiang X, Jeon N, Lee YJ, Ha IH (2024) Proton pump inhibitors associated with an increased risk of mortality in elderly: a systematic review and meta-analysis. Eur J Clin Pharmacol 80:367\u0026ndash;382.\u003c/li\u003e\n\u003cli\u003eShiraev TP, Bullen A (2018) Proton pump inhibitors and cardiovascular events: a systematic review. Heart Lung Circ 27(4):443\u0026ndash;450.\u003c/li\u003e\n\u003cli\u003eFreedberg DE, Kim LS, Yang YX (2017) The risks and benefits of long-term use of proton pump inhibitors: expert review and best practice advice from the American Gastroenterological Association. Gastroenterology 152(4):706\u0026ndash;715.\u003c/li\u003e\n\u003cli\u003eLazarus B, Chen Y, Wilson FP, Sang Y, Chang AR, Coresh J, Grams ME (2016) Proton pump inhibitor use and the risk of chronic kidney disease. JAMA Intern Med 176(2):238\u0026ndash;246.\u003c/li\u003e\n\u003cli\u003eBlank ML, Parkin L, Paul C, Herbison P (2014) A nationwide nested case-control study indicates an increased risk of acute interstitial nephritis with proton pump inhibitor use. Kidney Int 86(4):837\u0026ndash;844.\u003c/li\u003e\n\u003cli\u003eGhebremariam YT, Cooke JP, Gerhart W, Griego C, Brower JB, Doyle-Eisele M, et al. (2013) Proton pump inhibitors and vascular function: a potential mechanism for increased cardiovascular risk. Vasc Med 18(5):247\u0026ndash;253.\u003c/li\u003e\n\u003cli\u003eKoulouridis I, Ku E, McCulloch CE, Tattersall J, Lin F, Chertow GM (2013) Proton pump inhibitors and risk of hypomagnesemia in chronic kidney disease. Pharmacoepidemiol Drug Saf 22(10):1128\u0026ndash;1133.\u003c/li\u003e\n\u003cli\u003eImhann F, Bonder MJ, Vich Vila A, Fu J, Mujagic Z, Vork L, et al. (2016) Proton pump inhibitors affect the gut microbiome. Gut 65(5):740\u0026ndash;748.\u003c/li\u003e\n\u003cli\u003eForgacs I, Loganayagam A (2008) Overprescribing proton pump inhibitors. BMJ 336(7634):2\u0026ndash;3\u003c/li\u003e\n\u003cli\u003eLi H, Qiu X, Zhang H, et al. (2014) CYP2C19 polymorphisms affect the pharmacokinetics of omeprazole in healthy Chinese volunteers. Eur J Clin Pharmacol 70(9):1041\u0026ndash;1046.\u003c/li\u003e\n\u003cli\u003eSugano K, Choi MG, Lin JT, et al. (2010) Systematic review of management of gastroesophageal reflux disease in Asian countries. J Gastroenterol Hepatol 25(3):319\u0026ndash;328.\u003c/li\u003e\n\u003cli\u003eVaezi MF, Yang YX, Howden CW (2017) Complications of proton pump inhibitor therapy. Gastroenterology 153(1):35\u0026ndash;48.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-clinical-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejcl","sideBox":"Learn more about [European Journal of Clinical Pharmacology](http://link.springer.com/journal/228)","snPcode":"228","submissionUrl":"https://submission.nature.com/new-submission/228/3","title":"European Journal of Clinical Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"proton pump inhibitors, mortality, elderly, systematic review, meta-analysis","lastPublishedDoi":"10.21203/rs.3.rs-7206711/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7206711/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Use of proton pump inhibitor (PPI) has been associated with adverse health outcomes, including increased risk of all-cause mortality. Evidence suggests that individuals with kidney disease who use PPIs may experience higher mortality, though the nature of this association is not well established.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To assess the relationship between PPI use and mortality among individuals with kidney disease through a systematic review and meta-analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A comprehensive search of Ovid-MEDLINE, Ovid-EMBASE, and Cochrane CENTRAL was conducted through April 2025 to identify randomized controlled trials and observational studies examining mortality among PPI users versus non-users with kidney disease. Both unadjusted mortality rates and adjusted hazard ratios (aHRs) were extracted. A random-effects meta-analysis was performed using the Hartung-Knapp-Sidik-Jonkman method, with the Sidik-Jonkman estimator used for between-study variance (τ²). Study heterogeneity was evaluated using the I² statistic and Cochran’s Q test. Subgroup analyses were carried out based on follow-up length, population characteristics, geographic region, and risk of bias level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The review included 24 observational studies encompassing 216,032 individuals with kidney disease. Across 20 cohorts from 17 observational studies, mortality was 23.2% among PPI users and 22.1% among non-users. Pooled adjusted estimates from 18 studies (20 cohorts) indicated a significantly increased risk of death in PPI users (aHR 1.26; 95% CI, 1.11–1.42). Considerable heterogeneity was observed, but subgroup analyses revealed consistent trends.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Our meta-analysis showed that PPI use was linked to elevated mortality risk in kidney disease populations. Careful consideration is advised when prescribing PPIs, and further research is needed.\u003c/p\u003e","manuscriptTitle":"The association between proton pump inhibitor use and the risk of mortality in patients with kidney disease: a systematic review and meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 11:33:44","doi":"10.21203/rs.3.rs-7206711/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-14T06:06:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-13T06:52:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-10T08:49:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-08T15:37:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"294364664994588967908810602866936477803","date":"2025-09-30T05:36:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"212587773402666520724634376644405209497","date":"2025-09-29T13:36:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80489681803654315782619601749738066180","date":"2025-09-27T17:46:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-26T15:10:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"297729907841637837746601206734402984060","date":"2025-08-13T12:58:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"49271784783158089366362860561797390942","date":"2025-08-11T11:22:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-11T06:12:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-30T04:56:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-30T04:55:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Clinical Pharmacology","date":"2025-07-24T14:27:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-clinical-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejcl","sideBox":"Learn more about [European Journal of Clinical Pharmacology](http://link.springer.com/journal/228)","snPcode":"228","submissionUrl":"https://submission.nature.com/new-submission/228/3","title":"European Journal of Clinical Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b9c34a5a-17d5-44cf-a4e0-ccb68fa89063","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T16:09:37+00:00","versionOfRecord":{"articleIdentity":"rs-7206711","link":"https://doi.org/10.1007/s00228-026-04022-w","journal":{"identity":"european-journal-of-clinical-pharmacology","isVorOnly":false,"title":"European Journal of Clinical Pharmacology"},"publishedOn":"2026-03-07 15:59:58","publishedOnDateReadable":"March 7th, 2026"},"versionCreatedAt":"2025-08-19 11:33:44","video":"","vorDoi":"10.1007/s00228-026-04022-w","vorDoiUrl":"https://doi.org/10.1007/s00228-026-04022-w","workflowStages":[]},"version":"v1","identity":"rs-7206711","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7206711","identity":"rs-7206711","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}