GLP-1 Receptor Agonists in Kidney Transplant Recipients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis on Mortality and Major Adverse Kidney Events

GLP-1 Receptor Agonists in Kidney Transplant Recipients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis on Mortality and Major Adverse Kidney Events | 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 GLP-1 Receptor Agonists in Kidney Transplant Recipients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis on Mortality and Major Adverse Kidney Events Turkan Aliyeva, Enyinnaya Calistus Jiakponna, Julia Natche, Feras Ahmad Ahmad, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7859743/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Jan, 2026 Read the published version in Journal of Diabetes & Metabolic Disorders → Version 1 posted You are reading this latest preprint version Abstract Background: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are increasingly used in patients with type 2 diabetes and chronic kidney disease. However, their safety and efficacy in kidney transplant recipients remain uncertain. This study aims to evaluate the impact of GLP-1 RAs on all-cause mortality, major adverse cardiovascular events (MACE), and major adverse kidney events (MAKE) in adult kidney transplant recipients. Methods: We conducted a systematic review and meta-analysis of retrospective cohort studies reporting outcomes in adult kidney transplant recipients treated with GLP-1 RAs. A comprehensive search of PubMed, Embase and Cochrane Library was performed up to July 2025. Studies were included if they reported on at least one of the following outcomes: all-cause mortality, MACE, or MAKE. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using a random-effects model. Results: A total of four retrospective cohort studies involving 27,153 were included. A total of 5,479 (20.2%) patients received GLP-1 RAs. The median follow-up period across studies ranged from 1.38 to 3.1 years. GLP-1 RAs treatment was associated with a significant reduction in all-cause mortality, with an aHR of 0.52 (95% CI: 0.32–0.85, I² = 86%; p = 0.009). Similarly, a significant reduction in MAKEs was observed, with a pooled aHR of 0.62 (95% CI, 0.53-0.73; I² = 15%; p < 0.00001). Conclusions: In kidney transplant recipients, GLP-1 RAs appear to be associated with reduced risks of all-cause mortality and MAKEs. These findings support the potential role of GLP-1 RAs in this population, however prospective studies are needed to confirm long-term safety and efficacy. GLP-1 RAs kidney transplantation mortality MACE MAKE Figures Figure 1 Figure 2 Figure 3 Introduction Kidney transplant recipients are at high risk for both cardiovascular and renal complications, which significantly impact long-term patient and graft survival [1]. Despite improvements in transplantation techniques and immunosuppressive regimens, cardiovascular disease remains the leading cause of death in this population, while chronic allograft dysfunction continues to contribute to morbidity and graft loss [2–4]. Type 2 diabetes mellitus (T2DM), a common comorbidity among kidney transplant recipients, further increases the risk of adverse outcomes, including cardiovascular events and graft loss [5]. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are a class of antidiabetic agents that have demonstrated cardiovascular and renal protective effects in the general population with T2DM [6,7]. Large randomized trials have shown that GLP-1 RAs reduce the risk of major adverse cardiovascular events (MACE), slow the progression of chronic kidney disease, and lower all-cause mortality in patients with diabetes mellitus [8,9]. However, the role of GLP-1 RAs in kidney transplant recipients remains uncertain. This population is often excluded from major clinical trials, and concerns about drug interactions with immunosuppressants and altered pharmacokinetics have limited their widespread use in transplant settings. As a result, the evidence base for GLP-1 RAs use in kidney transplant recipients is primarily limited to retrospective observational studies. The majority of these studies focused on evaluating the effectiveness of this treatment in improving weight loss, glycemic control, kidney function, and in assessing its short-term safety outcomes [10–12]. A meta-analysis conducted by Krisanapan et al., which included observational studies involving 338 kidney transplant recipients, found that GLP-1 RAs were effective in improving blood sugar control, reducing proteinuria, and promoting weight loss, while having no significant impact on tacrolimus blood concentrations [13]. However, there is limited data on the impact of GLP-1 RAs on patient survival and kidney outcomes in kidney transplant recipients. To address this evidence gap, we conducted a systematic review and meta-analysis of retrospective cohort studies to assess the impact of GLP-1 RAs on all-cause mortality, MACE, and MAKE in adult kidney transplant recipients with type 2 DM. Our aim was to synthesize the limited available evidence to inform future research and clinical practice in this population. Methods This meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [14,15]. The study protocol was registered in PROSPERO (CRD420251029674). A systematic search of PubMed, Embase and Cochrane Library was performed from inception to July 2025. The following search strategy was used in PubMed and adapted appropriately for the other databases: ("Glucagon-Like Peptide 1 Receptor Agonists"[Mesh] OR "GLP-1 receptor agonist*" OR "GLP-1" OR "GLP-1 analogue" OR "Liraglutide" OR "Semaglutide" OR "Dulaglutide" OR "Exenatide" OR "Lixisenatide") AND ("Kidney transplant recipient" OR "Renal transplant recipient" OR "Kidney transplantation" OR "Renal transplantation" OR "Post-transplant patients" OR "Kidney allograft" OR "Renal allograft" OR "Graft function" OR "Transplant patients"). No language restrictions were applied. Reference lists of relevant studies and reviews were also screened manually for additional eligible studies. Eligibility Criteria Studies were included if they met the following criteria: (1) adult (≥ 18 years) kidney transplant recipients; (2) being diagnosed with type 2 diabetes mellitus (type 2 DM) either before or after transplantation; (3) treatment with any glucagon-like peptide-1 receptor agonist (GLP-1 RA); (4) reported data on at least one of the following clinical outcomes (all-cause mortality, major adverse cardiovascular events (MACE), major adverse kidney events (MAKE); and (5) were randomized controlled trials (RCTs) or observational studies (prospective or retrospective cohort studies). Exclusion criteria: (1) studies without a comparator group; (2) case reports, case series, editorials, letters, conference abstracts, or reviews; (3) studies not reporting at least one of the primary outcomes or lacking sufficient data to extract effect estimates. Data Extraction and Quality Assessment Two authors (T. A. and J.N.) independently screened the search results to identify eligible studies, following predefined criteria for study selection, data extraction, and quality assessment. Discrepancies were resolved by consensus between the two reviewers. Data extracted included: first author, publication year, study design, sample size, patient demographics and baseline characteristics (age, gender, HbA1c, BMI, eGFR, UACR), type of GLP-1 RA, duration of follow-up. The quality of non-randomized studies was assessed using the Risk of Bias in Non-Randomized Studies of Interventions (ROBINS-I) tool [16]. Publication bias was evaluated using funnel plots to explore the relationship between study effect sizes and their precision. Outcomes The primary outcome was all-cause mortality. Secondary outcomes included major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, myocardial infarction, stroke, or hospitalization for heart failure; and major adverse kidney events (MAKE), defined as a composite of graft loss, re-initiation of dialysis, or death. For mortality outcomes, recipients were followed from the time of transplantation until the earliest occurrence of death or the end of the study. However, the definitions of MAKE were not consistent across the included studies. Specifically, Orandi et al. reported death-censored graft loss [17], Lin et al. defined MAKE as dialysis dependence, eGFR < 15 mL/min/1.73 m², or death [18], and Cohen et al. reported a broader composite outcome including graft rejection, dialysis, re-transplantation, or all-cause mortality [19]. In our analysis, we used the most comparable definition available in each study to ensure consistency as much as possible. Statistical Analysis Pooled effect estimates were calculated using a random-effects model with restricted maximum likelihood (REML) to account for between-study heterogeneity. Hazard ratios (HRs) were used as the principal summary measure. Heterogeneity was assessed using the I² statistic, with values > 50% indicating substantial heterogeneity. Heterogeneity among the included studies was evaluated using Cochrane’s Q test and the I² statistic. A p-value below 0.10 was considered indicative of significant heterogeneity. I² values were interpreted as follows: 0–40% (low), 30–60% (moderate), 50–90% (substantial), and 75–100% (considerable) heterogeneity [20]. Sensitivity analyses were conducted by sequentially omitting individual studies to evaluate the robustness of the findings. All analyses were performed using Review Manager (RevMan Web), The Cochrane Collaboration, Copenhagen, Denmark. Results The initial database search yielded 636 records. After removing duplicates and screening titles and abstracts, 54 studies were selected for full-text review. Following full-text assessment, 4 studies met the inclusion criteria and were included in the final analysis. All included studies were retrospective cohort studies. The study population included a total of 27,153 individuals, of whom 5,479 (20.2%) received GLP-1 RAs. The median follow-up duration ranged from 1.38 to 3.1 years. Baseline characteristics of the included studies are summarized in Table 1 . All-Cause Mortality Three studies reported adjusted HR for all-cause mortality in kidney transplant recipients treated with GLP-1 RAs. The pooled analysis demonstrated a statistically significant reduction in mortality risk associated with GLP-1 RAs use, with a combined aHR of 0.52 (95% CI: 0.32–0.85, p = 0.009), indicating a 48% relative risk reduction compared to controls (Fig. 2 A). However, substantial heterogeneity was observed across studies (I² = 86%), suggesting variability in study populations, adjustments, or methodologies. A leave-one-out sensitivity analysis was performed to assess the robustness of the results. Excluding Lin et al., the study with the largest weight and effect size, the pooled aHR for all-cause mortality became 0.65 (95% CI: 0.39–1.10, p = 0.11, I² = 44%), indicating a non-significant association. Similarly, when Sahi et al. was excluded, the HR was 0.55 (95% CI: 0.28–1.05, p = 0.07, I² = 94%), showing a non-significant result. In contrast, excluding Orandi et al. yielded an HR of 0.39 (95% CI not reported), with I² = 0 and p < 0.0001, suggesting a strong effect with no heterogeneity. These findings are presented in Supplementary Fig. 1. These results indicate that the observed mortality benefit is largely driven by specific studies, highlighting the need for cautious interpretation. The unadjusted analysis, based on two studies, also showed a significant reduction in all-cause mortality associated with GLP-1 RAs use (HR = 0.68, 95% CI: 0.57–0.82, p < 0.0001), with no heterogeneity (I² = 0%), as shown in Fig. 2 B. Major Adverse Cardiovascular Events (MACE) A meta-analysis for MACE could not be conducted due to the limited availability of data. Only one study, Lin et al. 2025, reported an aHR of 0.66 (95% 0.56–0.79) for MACE. This result suggests a significant 34% reduction in the risk of MACE associated with the GLP-1 RA in kidney transplant recipients with type 2 DM. Major Adverse Kidney Events (MAKE) The meta-analysis demonstrated a statistically significant association between the use of GLP-1 RA and a reduced risk of MAKEs in kidney transplant recipients with type 2 DM. The pooled aHR was 0.62 (95% CI 0.53–0.73, I² = 15%, p < 0.00001), indicating a 38% relative reduction in the risk of MAKEs among individuals receiving GLP1-RA therapy compared to those in the control group (Fig. 3 A). Notably, the definitions of MAKE varied across studies: Orandi et al. reported death-censored graft loss; Lin et al. defined MAKE as dialysis, eGFR < 15 mL/min/1.73 m², or death; and Cohen et al. used a composite of graft rejection, dialysis, re-transplantation, or all-cause mortality. To assess the robustness of the overall effect, a leave-one-out sensitivity analysis was conducted. Excluding any individual study did not significantly alter the pooled HR, supporting the stability and reliability of the overall findings. Although our findings appear robust, they should still be interpreted with caution due to differences in MAKE definitions across studies and the limited number of included studies (Supplementary Fig. 2). Furthermore, the unadjusted analyses demonstrated GLP-1 RAs use was associated with a significantly lower risk of kidney outcome, with a pooled HR of 0.59 (95% CI: 0.46–0.76, I² = 0%, p < 0.0001), Fig. 3 B. Table 1 Characteristics of the studies included in the systematic review and meta-analysis. Study Design Sample size Age † Male (%) BMI, kg/m2 † HbA1c † eGFR, ml/min/ 1.73m2 † UACR, mg/gr § Follow- up § Type of GLP1-RA (%) Cohen et al. 2025 [19] RC GLP1-RA: 136 Control: 136 57.9 (10.6) 58.7 (11.4) 69 69 31.1 (4.0) 27.2 (4.5) 7.8 (1.4) 7.0 (1.4) 67 (25) 62 (26) 38 (14–104) 21 (5-189) 3.1 years (1.2–5.7) liraglutide (29) dulaglutide (52) semaglutide (19) Orandi et al. 2025 [17] RC GLP1-RA: 1969 Control: 16047 57 (49–64) § 60 (51–66) § 60.1 64.8 31.2 (4.8) 29.6 (5.1) N/A N/A N/A 1.38 years (0.62–2.48) N/A Lin et al. 2025 [18] RC PSM GLP1-RA: 3297 Control: 3297 57.2 (11.0) 57.3 (11.7) 55.3 55 31.7 (5.9) 31.3 (6.2) 7.3 (1.7) 7.2. (1.7) 52.4 (21.8) 51.4 (23.1) 353 (1036.0) † 292 (730) † 2.5 years (1.4–3.6) N/A Sahi et al. 2025 [21] RC GLP1-RA: 77 Control: 2094 57.9 (9.5) 60.8 (9.5) 61 66 32.1 (4.3) 30.1 (5.1) 7.2 (55.2) 7.1 (54.1) 52.8 (14.4) 50.3 (17.5) 29.0 (3-665) 41.7(2.4–1444) 1.5 years (0.99–2.4) liraglutide (23) dulaglutide(47) semaglutide(30) † , mean, (SD); § , median, range; RC, retrospective Cohort; RC PSM, Retrospective Cohort with Propensity Score Matching; BMI, body mass index; eGFR, estimated glomerular filtration rate; GLP-1 RA, glucagon-like peptide-1 receptor agonist; HbA1c, hemoglobin A1c; uACR, urine albumin/creatinine ratio. Quality Assessment Funnel plots for mortality and MAKEs appeared symmetric, indicating a low risk of publication bias. Risk of bias was assessed using the ROBINS-I tool. Sahi et al. (2025) was judged to have a serious risk of bias, primarily due to a large imbalance between the treatment and control groups, which raises concerns about confounding and comparability [21]. The remaining studies were assessed as having a moderate risk of bias. Discussion In this meta-analysis of four retrospective cohort studies including 27,153 adult kidney transplant recipients with type 2 DM, the use of GLP-1 RAs was associated with favorable clinical outcomes: (1) a significant reduction in all-cause mortality, with a pooled aHR of 0.52 (95% CI: 0.32–0.85; I² = 86%; p = 0.009), indicating a 38% lower risk of death compared to nonusers; and (2) a significant reduction in the risk of MAKEs, with a pooled aHR of 0.62 (95% CI: 0.53–0.73; I² = 15%; p < 0.00001). Although a pooled analysis could not be performed as only one study reported MACE outcomes, Lin et al. found a significant 34% reduction in risk with GLP-1 RA use (aHR 0.66; 95% CI: 0.56–0.79; p < 0.001) in kidney transplant recipients with type 2 diabetes. GLP-1 RAs have demonstrated substantial benefits beyond glycemic control, particularly in reducing kidney and cardiovascular risks in patients with type 2 diabetes. Evidence from several large randomized controlled trials, such as LEADER, SUSTAIN-6, REWIND, and the more recent SELECT trial consistently supports these effects [7, 23–25]. A comprehensive meta-analysis of over 85,000 participants reported that GLP-1 RAs reduced the risk of composite kidney outcomes by 18%, kidney failure by 16%, major adverse cardiovascular events (MACE) by 13%, and all-cause mortality by 12%, with no significant increase in serious adverse events [25]. These findings highlight the therapeutic potential of GLP-1 RAs in improving kidney and cardiovascular outcomes in high-risk populations. This meta-analysis showed a significant reduction in all-cause mortality with GLP-1 RA use, with a pooled aHR of 0.52 (95% CI: 0.32–0.85, I² = 15%, p < 0.00001). However, sensitivity analyses indicate that this observed benefit is not fully robust. Leave-one-out analyses revealed that excluding influential studies such as Lin et al. or Sahi et al. resulted in non-significant associations, suggesting that the overall effect is largely driven by a few studies with substantial weight or strong effect sizes. These findings underscore the need for cautious interpretation, as the evidence is somewhat inconsistent across the included studies. Nonetheless, the results provide preliminary support for a potential mortality benefit, which warrants further confirmation in larger, high-quality studies. The kidney-protective mechanisms of GLP-1 receptor agonists (GLP-1 RAs) are not yet fully elucidated but are believed to involve both direct renal and systemic effects. Proposed mechanisms include natriuresis via inhibition of sodium-hydrogen exchanger 3 (NHE3) in the proximal tubules, suppression of the intrarenal renin-angiotensin system, and improved kidney oxygenation by reducing ischemia and hypoxia [27,28]. These effects are supported by human studies demonstrating GLP-1 receptor expression in key renal structures, including proximal tubules, juxtaglomerular cells, and preglomerular vessels [28]. Furthermore, GLP-1 RAs may exert anti-inflammatory effects by inhibiting angiotensin II signaling, reducing oxidative stress, and promoting M2 macrophage polarization, as shown in experimental models of Kidney disease in patients with diabetes mellitus [30,31]. The cardioprotective effects of GLP-1 RAs are believed to result from their pleiotropic actions. Preclinical studies suggest that these agents may reduce atherosclerosis by decreasing vascular inflammation, minimizing oxidative stress, and inhibiting the proliferation and activation of vascular smooth muscle cells [32,33]. Studies investigating the use of GLP-1 receptor agonists (GLP-1 RAs) in kidney transplant patients are currently limited and primarily consist of small and retrospective cohort analyses. GLP-1 RAs have demonstrated promising effects on weight and glycemic control in kidney transplant recipients. Mahmoud et al. reported a reduction in BMI of 0.34 kg/m² among GLP-1 RA users, while the control group showed a minimal increase of 0.015 kg/m² [33]. Furthermore, after one year, recipients treated with GLP-1 RAs experienced a 0.4% reduction in HbA1c, while no change was observed in the control group (P = .009). Similarly, a study by Mahzari et al., involving patients with pre-existing type 2 DM or post-transplant diabetes mellitus, found that semaglutide significantly lowered HbA1c levels and body weight [10]. Singh et al. showed that, in a cohort of 63 solid organ transplant recipients, there was a sustained and statistically significant reduction in the primary endpoints, such as weight, body mass index (BMI), and insulin requirements at 6, 12, and 24 months, respectively [34]. In a retrospective cohort of Japanese kidney transplant recipients, GLP-1 RA use was linked to a significantly lower risk of sustained eGFR reduction ≥ 40% at 4 months post-transplant (OR 0.105; 95% CI: 0.012–0.961; p = 0.046) after propensity score matching [12]. Similarly, Singh et al. reported a 15% increase in eGFR with dulaglutide treatment, compared to an 8% decrease with liraglutide in kidney transplant patients [34]. Krisanapan et al. conducted a meta-analysis including 338 kidney transplant recipients from nine cohort studies. Their findings showed that GLP-1 RA treatment did not lead to significant changes in eGFR (SMD − 0.07 mL/min/1.73m²; 95% CI: −0.64 to 0.50) or serum creatinine levels (SMD − 0.08 mg/dL; 95% CI: −0.44 to 0.28). However, GLP-1 RA therapy was associated with significant reductions in HbA1c levels (SMD − 0.85%; 95% CI: −1.41 to − 0.28) and urine protein-to-creatinine ratio (SMD − 0.47; 95% CI: −0.77 to − 0.18) [13]. In the study by Liou et al., renal graft function showed a significant improvement, with the estimated glomerular filtration rate (eGFR) increasing from 67.7 ± 18.7 to a peak of 76.5 ± 18.7 mL/min/1.73 m² (P = .024). However, no significant change was observed in the urinary protein-to-creatinine ratio [35]. Our meta-analysis demonstrated that GLP-1 receptor agonist use in kidney transplant recipients with type 2 diabetes was associated with a significantly lower risk of MAKEs, with a pooled adjusted hazard ratio of 0.65 (95% CI 0.57–0.74). However, we acknowledge that the definitions of MAKE varied across the included studies. These differences may have introduced heterogeneity and limit the direct comparability of the findings, although sensitivity analyses supported the robustness of the overall effect. A study by Dotan et al. reported data on MACE, the findings were notable. In this study, which included 318 diabetic transplant recipients (kidney, lungs, liver, heart) with a median follow-up of 3.1 years, GLP-1 RA use was associated with a substantial reduction in MACE risk (HR 0.46; 95% CI: 0.27–0.78) [36]. This suggests a potential cardioprotective effect of GLP-1 RAs in this high-risk population, although further data are needed to confirm this observation. GLP-1RAs can delay gastric emptying, potentially affecting the absorption of oral drugs like immunosuppressants. While dose adjustments are usually unnecessary and interactions are few, starting with low doses and slow titration is recommended due to GI side effects. Dose changes may depend on treatment goals, kidney function, and medication type, but data on dosing in kidney transplant patients are limited. Careful dose management is important to avoid hypoglycemia when GLP-1RAs are combined with other glucose-lowering drugs [37]. Strength and Limitations While previous meta-analyses have primarily focused on the effects of GLP-1 RAs on kidney function, weight loss, glycemic control, or short-term safety outcomes in kidney transplant recipients, to our knowledge, this is the first meta-analysis to assess their impact on overall mortality and major adverse kidney events (MAKEs). This study has several limitations. First, all included studies were retrospective cohorts, which are inherently subject to confounding and selection bias. Although adjustments were made for baseline characteristics, residual confounding cannot be ruled out. Second, the number of studies and sample sizes were relatively small, particularly for outcomes such as MAKE, MACE, and mortality, which limits the statistical power and generalizability of the findings. Third, there was heterogeneity in the definitions of MAKE among the included studies. Although all outcomes reflected clinically meaningful adverse kidney events, the lack of a standardized definition may have affected the comparability of results and should be considered when interpreting our findings. Fourth, the number of studies and events for MACE was limited, precluding a robust meta-analysis of cardiovascular outcomes. Fifth, variability in study populations, GLP-1 RA agents used, dosages, and follow-up durations may have contributed to heterogeneity. Finally, important clinical details such as baseline kidney function, immunosuppressive regimens, and comorbidities were not uniformly reported across studies, restricting the ability to perform more detailed subgroup analyses. Conclusion This meta-analysis suggests that GLP-1 RAs may be associated with reduced risks of all-cause mortality and major adverse kidney events in kidney transplant recipients; however, the observed benefit appears to be influenced by a few large, high-weight studies, highlighting variability across the evidence and the need for cautious interpretation. Further well-designed, large-scale studies are warranted to confirm the potential mortality benefit and to better understand which patient populations are most likely to derive clinically meaningful effects. Declarations Ethics Approval and Consent to Participate This study is a meta-analysis and did not involve direct human or animal subjects; therefore, ethics approval and consent to participate were not required. Consent for Publication Not applicable. Availability of Data and Materials The data that support the findings of this study are available from the corresponding author upon reasonable request. Competing Interests The authors declare no competing interests. Funding No financial support was received for this study. References S. M. Arend, M. J. Mallat, R. J. Westendorp, F. J. van der Woude, ve L. A. van Es, “Patient survival after renal transplantation; more than 25 years follow-up.”, Nephrol. Dial. Transplant. Off. Publ. Eur. Dial. Transpl. Assoc. - Eur. Ren. Assoc. , c. 12, sy 8, ss. 1672-1679, Ağu. 1997, doi: 10.1093/ndt/12.8.1672. J. S. Gill, “Cardiovascular disease in transplant recipients: current and future treatment strategies.”, Clin. J. Am. Soc. Nephrol. 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14:53:14","extension":"xml","order_by":40,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":74015,"visible":true,"origin":"","legend":"","description":"","filename":"c56b43525a754137afad032959a6b08b1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7859743/v1/1c01809d1558d6ecfa64d9f2.xml"},{"id":94681810,"identity":"c35c7b67-fc63-46b8-8849-47f8516e8637","added_by":"auto","created_at":"2025-10-29 14:53:13","extension":"html","order_by":41,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":87507,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7859743/v1/628f764cb5c041b91b61b137.html"},{"id":94681760,"identity":"72634077-f098-4b31-a2e4-89203de161f2","added_by":"auto","created_at":"2025-10-29 14:53:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":218298,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA flowchart for the literature searching strategy and procedure for study selection.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7859743/v1/db1db0c7c98d95e3dd613592.png"},{"id":94728953,"identity":"b77e056c-ca16-43b4-b27a-822157816b3d","added_by":"auto","created_at":"2025-10-30 07:04:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":752706,"visible":true,"origin":"","legend":"\u003cp\u003ePooled Hazard Ratios for All-Cause Mortality: (A) Adjusted and (B) Unadjusted Analyses\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7859743/v1/7537b533816b2466d7a9cfd1.png"},{"id":94728188,"identity":"33a6cdc6-83f1-465b-aa45-7992da0fb183","added_by":"auto","created_at":"2025-10-30 07:03:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":751589,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled Hazard Ratios for MAKEs: (A) Adjusted and (B) Unadjusted Analyses.\u003c/strong\u003e\u003cbr\u003e\nMAKE definitions in the included studies: Orandi et al.: death-censored graft loss; Lin et al.: dialysis, eGFR \u0026lt;15 mL/min/1.73 m², or death; Cohen et al.: composite of graft rejection, dialysis, re-transplantation, or all-cause mortality.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7859743/v1/9f0ba81ae97839b1c61302e1.png"},{"id":100069091,"identity":"85ee51e3-d46f-4460-a9e2-b28391a378c7","added_by":"auto","created_at":"2026-01-12 16:08:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2825332,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7859743/v1/2d6868af-800d-4bd2-abcb-4ccb80668d33.pdf"},{"id":94728185,"identity":"b2dc097a-119f-4548-b185-c4ba951e9982","added_by":"auto","created_at":"2025-10-30 07:03:17","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":440246,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-7859743/v1/0ffad526855a9b7378e3cbf3.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"GLP-1 Receptor Agonists in Kidney Transplant Recipients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis on Mortality and Major Adverse Kidney Events","fulltext":[{"header":"Introduction","content":"\u003cp\u003eKidney transplant recipients are at high risk for both cardiovascular and renal complications, which significantly impact long-term patient and graft survival [1]. Despite improvements in transplantation techniques and immunosuppressive regimens, cardiovascular disease remains the leading cause of death in this population, while chronic allograft dysfunction continues to contribute to morbidity and graft loss [2\u0026ndash;4].\u003c/p\u003e\u003cp\u003eType 2 diabetes mellitus (T2DM), a common comorbidity among kidney transplant recipients, further increases the risk of adverse outcomes, including cardiovascular events and graft loss [5]. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are a class of antidiabetic agents that have demonstrated cardiovascular and renal protective effects in the general population with T2DM [6,7]. Large randomized trials have shown that GLP-1 RAs reduce the risk of major adverse cardiovascular events (MACE), slow the progression of chronic kidney disease, and lower all-cause mortality in patients with diabetes mellitus [8,9].\u003c/p\u003e\u003cp\u003eHowever, the role of GLP-1 RAs in kidney transplant recipients remains uncertain. This population is often excluded from major clinical trials, and concerns about drug interactions with immunosuppressants and altered pharmacokinetics have limited their widespread use in transplant settings. As a result, the evidence base for GLP-1 RAs use in kidney transplant recipients is primarily limited to retrospective observational studies. The majority of these studies focused on evaluating the effectiveness of this treatment in improving weight loss, glycemic control, kidney function, and in assessing its short-term safety outcomes [10\u0026ndash;12]. A meta-analysis conducted by Krisanapan et al., which included observational studies involving 338 kidney transplant recipients, found that GLP-1 RAs were effective in improving blood sugar control, reducing proteinuria, and promoting weight loss, while having no significant impact on tacrolimus blood concentrations [13].\u003c/p\u003e\u003cp\u003eHowever, there is limited data on the impact of GLP-1 RAs on patient survival and kidney outcomes in kidney transplant recipients. To address this evidence gap, we conducted a systematic review and meta-analysis of retrospective cohort studies to assess the impact of GLP-1 RAs on all-cause mortality, MACE, and MAKE in adult kidney transplant recipients with type 2 DM. Our aim was to synthesize the limited available evidence to inform future research and clinical practice in this population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e This meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [14,15]. The study protocol was registered in PROSPERO (CRD420251029674).\u003c/p\u003e\u003cp\u003eA systematic search of PubMed, Embase and Cochrane Library was performed from inception to July 2025. The following search strategy was used in PubMed and adapted appropriately for the other databases: (\"Glucagon-Like Peptide 1 Receptor Agonists\"[Mesh] OR \"GLP-1 receptor agonist*\" OR \"GLP-1\" OR \"GLP-1 analogue\" OR \"Liraglutide\" OR \"Semaglutide\" OR \"Dulaglutide\" OR \"Exenatide\" OR \"Lixisenatide\") AND (\"Kidney transplant recipient\" OR \"Renal transplant recipient\" OR \"Kidney transplantation\" OR \"Renal transplantation\" OR \"Post-transplant patients\" OR \"Kidney allograft\" OR \"Renal allograft\" OR \"Graft function\" OR \"Transplant patients\"). No language restrictions were applied. Reference lists of relevant studies and reviews were also screened manually for additional eligible studies.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eEligibility Criteria\u003c/h2\u003e\u003cp\u003eStudies were included if they met the following criteria: (1) adult (\u0026ge;\u0026thinsp;18 years) kidney transplant recipients; (2) being diagnosed with type 2 diabetes mellitus (type 2 DM) either before or after transplantation; (3) treatment with any glucagon-like peptide-1 receptor agonist (GLP-1 RA); (4) reported data on at least one of the following clinical outcomes (all-cause mortality, major adverse cardiovascular events (MACE), major adverse kidney events (MAKE); and (5) were randomized controlled trials (RCTs) or observational studies (prospective or retrospective cohort studies).\u003c/p\u003e\u003cp\u003eExclusion criteria: (1) studies without a comparator group; (2) case reports, case series, editorials, letters, conference abstracts, or reviews; (3) studies not reporting at least one of the primary outcomes or lacking sufficient data to extract effect estimates.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData Extraction and Quality Assessment\u003c/h3\u003e\n\u003cp\u003eTwo authors (T. A. and J.N.) independently screened the search results to identify eligible studies, following predefined criteria for study selection, data extraction, and quality assessment. Discrepancies were resolved by consensus between the two reviewers. Data extracted included: first author, publication year, study design, sample size, patient demographics and baseline characteristics (age, gender, HbA1c, BMI, eGFR, UACR), type of GLP-1 RA, duration of follow-up. The quality of non-randomized studies was assessed using the Risk of Bias in Non-Randomized Studies of Interventions (ROBINS-I) tool [16]. Publication bias was evaluated using funnel plots to explore the relationship between study effect sizes and their precision.\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eThe primary outcome was all-cause mortality. Secondary outcomes included major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, myocardial infarction, stroke, or hospitalization for heart failure; and major adverse kidney events (MAKE), defined as a composite of graft loss, re-initiation of dialysis, or death. For mortality outcomes, recipients were followed from the time of transplantation until the earliest occurrence of death or the end of the study. However, the definitions of MAKE were not consistent across the included studies. Specifically, Orandi et al. reported death-censored graft loss [17], Lin et al. defined MAKE as dialysis dependence, eGFR\u0026thinsp;\u0026lt;\u0026thinsp;15 mL/min/1.73 m\u0026sup2;, or death [18], and Cohen et al. reported a broader composite outcome including graft rejection, dialysis, re-transplantation, or all-cause mortality [19]. In our analysis, we used the most comparable definition available in each study to ensure consistency as much as possible.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003ePooled effect estimates were calculated using a random-effects model with restricted maximum likelihood (REML) to account for between-study heterogeneity. Hazard ratios (HRs) were used as the principal summary measure. Heterogeneity was assessed using the I\u0026sup2; statistic, with values\u0026thinsp;\u0026gt;\u0026thinsp;50% indicating substantial heterogeneity. Heterogeneity among the included studies was evaluated using Cochrane\u0026rsquo;s Q test and the I\u0026sup2; statistic. A p-value below 0.10 was considered indicative of significant heterogeneity. I\u0026sup2; values were interpreted as follows: 0\u0026ndash;40% (low), 30\u0026ndash;60% (moderate), 50\u0026ndash;90% (substantial), and 75\u0026ndash;100% (considerable) heterogeneity [20]. Sensitivity analyses were conducted by sequentially omitting individual studies to evaluate the robustness of the findings. All analyses were performed using Review Manager (RevMan Web), The Cochrane Collaboration, Copenhagen, Denmark.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe initial database search yielded 636 records. After removing duplicates and screening titles and abstracts, 54 studies were selected for full-text review. Following full-text assessment, 4 studies met the inclusion criteria and were included in the final analysis.\u003c/p\u003e\u003cp\u003eAll included studies were retrospective cohort studies. The study population included a total of 27,153 individuals, of whom 5,479 (20.2%) received GLP-1 RAs. The median follow-up duration ranged from 1.38 to 3.1 years. Baseline characteristics of the included studies are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eAll-Cause Mortality\u003c/h2\u003e\u003cp\u003eThree studies reported adjusted HR for all-cause mortality in kidney transplant recipients treated with GLP-1 RAs. The pooled analysis demonstrated a statistically significant reduction in mortality risk associated with GLP-1 RAs use, with a combined aHR of 0.52 (95% CI: 0.32\u0026ndash;0.85, p\u0026thinsp;=\u0026thinsp;0.009), indicating a 48% relative risk reduction compared to controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). However, substantial heterogeneity was observed across studies (I\u0026sup2; = 86%), suggesting variability in study populations, adjustments, or methodologies. A leave-one-out sensitivity analysis was performed to assess the robustness of the results. Excluding Lin et al., the study with the largest weight and effect size, the pooled aHR for all-cause mortality became 0.65 (95% CI: 0.39\u0026ndash;1.10, p\u0026thinsp;=\u0026thinsp;0.11, I\u0026sup2; = 44%), indicating a non-significant association. Similarly, when Sahi et al. was excluded, the HR was 0.55 (95% CI: 0.28\u0026ndash;1.05, p\u0026thinsp;=\u0026thinsp;0.07, I\u0026sup2; = 94%), showing a non-significant result. In contrast, excluding Orandi et al. yielded an HR of 0.39 (95% CI not reported), with I\u0026sup2; = 0 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, suggesting a strong effect with no heterogeneity. These findings are presented in Supplementary Fig.\u0026nbsp;1. These results indicate that the observed mortality benefit is largely driven by specific studies, highlighting the need for cautious interpretation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe unadjusted analysis, based on two studies, also showed a significant reduction in all-cause mortality associated with GLP-1 RAs use (HR\u0026thinsp;=\u0026thinsp;0.68, 95% CI: 0.57\u0026ndash;0.82, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with no heterogeneity (I\u0026sup2; = 0%), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMajor Adverse Cardiovascular Events (MACE)\u003c/h3\u003e\n\u003cp\u003eA meta-analysis for MACE could not be conducted due to the limited availability of data. Only one study, Lin et al. 2025, reported an aHR of 0.66 (95% 0.56\u0026ndash;0.79) for MACE. This result suggests a significant 34% reduction in the risk of MACE associated with the GLP-1 RA in kidney transplant recipients with type 2 DM.\u003c/p\u003e\n\u003ch3\u003eMajor Adverse Kidney Events (MAKE)\u003c/h3\u003e\n\u003cp\u003eThe meta-analysis demonstrated a statistically significant association between the use of GLP-1 RA and a reduced risk of MAKEs in kidney transplant recipients with type 2 DM. The pooled aHR was 0.62 (95% CI 0.53\u0026ndash;0.73, I\u0026sup2; = 15%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001), indicating a 38% relative reduction in the risk of MAKEs among individuals receiving GLP1-RA therapy compared to those in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Notably, the definitions of MAKE varied across studies: Orandi et al. reported death-censored graft loss; Lin et al. defined MAKE as dialysis, eGFR\u0026thinsp;\u0026lt;\u0026thinsp;15 mL/min/1.73 m\u0026sup2;, or death; and Cohen et al. used a composite of graft rejection, dialysis, re-transplantation, or all-cause mortality. To assess the robustness of the overall effect, a leave-one-out sensitivity analysis was conducted. Excluding any individual study did not significantly alter the pooled HR, supporting the stability and reliability of the overall findings. Although our findings appear robust, they should still be interpreted with caution due to differences in MAKE definitions across studies and the limited number of included studies (Supplementary Fig.\u0026nbsp;2). Furthermore, the unadjusted analyses demonstrated GLP-1 RAs use was associated with a significantly lower risk of kidney outcome, with a pooled HR of 0.59 (95% CI: 0.46\u0026ndash;0.76, I\u0026sup2; = 0%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of the studies included in the systematic review and meta-analysis.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDesign\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSample size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAge\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003cp\u003e(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBMI,\u003c/p\u003e\u003cp\u003ekg/m2\u0026nbsp;\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHbA1c\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eeGFR, ml/min/\u003c/p\u003e\u003cp\u003e1.73m2\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eUACR,\u003c/p\u003e\u003cp\u003emg/gr\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eFollow-\u003c/p\u003e\u003cp\u003eup\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eType of\u003c/p\u003e\u003cp\u003eGLP1-RA (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCohen et al. 2025 [19]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGLP1-RA: 136\u003c/p\u003e\u003cp\u003eControl: 136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57.9 (10.6)\u003c/p\u003e\u003cp\u003e58.7 (11.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e69\u003c/p\u003e\u003cp\u003e69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e31.1 (4.0)\u003c/p\u003e\u003cp\u003e27.2 (4.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.8 (1.4)\u003c/p\u003e\u003cp\u003e7.0 (1.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e67 (25)\u003c/p\u003e\u003cp\u003e62 (26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e38 (14\u0026ndash;104)\u003c/p\u003e\u003cp\u003e21 (5-189)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.1 years (1.2\u0026ndash;5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eliraglutide (29) dulaglutide (52) semaglutide (19)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrandi et al. 2025 [17]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGLP1-RA: 1969\u003c/p\u003e\u003cp\u003eControl: 16047\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57 (49\u0026ndash;64) \u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e60 (51\u0026ndash;66) \u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60.1\u003c/p\u003e\u003cp\u003e64.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e31.2 (4.8)\u003c/p\u003e\u003cp\u003e29.6 (5.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.38 years\u003c/p\u003e\u003cp\u003e(0.62\u0026ndash;2.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLin et al. 2025 [18]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRC\u003c/p\u003e\u003cp\u003ePSM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGLP1-RA: 3297\u003c/p\u003e\u003cp\u003eControl: 3297\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57.2 (11.0)\u003c/p\u003e\u003cp\u003e57.3 (11.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e55.3\u003c/p\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e31.7 (5.9)\u003c/p\u003e\u003cp\u003e31.3 (6.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.3 (1.7)\u003c/p\u003e\u003cp\u003e7.2. (1.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e52.4 (21.8)\u003c/p\u003e\u003cp\u003e51.4 (23.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e353 (1036.0) \u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e292 (730) \u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e2.5 years\u003c/p\u003e\u003cp\u003e(1.4\u0026ndash;3.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSahi et al. 2025 [21]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGLP1-RA: 77\u003c/p\u003e\u003cp\u003eControl: 2094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57.9 (9.5)\u003c/p\u003e\u003cp\u003e60.8 (9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61\u003c/p\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32.1 (4.3)\u003c/p\u003e\u003cp\u003e30.1 (5.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.2 (55.2)\u003c/p\u003e\u003cp\u003e7.1 (54.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e52.8 (14.4)\u003c/p\u003e\u003cp\u003e50.3 (17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e29.0 (3-665)\u003c/p\u003e\u003cp\u003e41.7(2.4\u0026ndash;1444)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.5 years\u003c/p\u003e\u003cp\u003e(0.99\u0026ndash;2.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eliraglutide (23)\u003c/p\u003e\u003cp\u003edulaglutide(47) semaglutide(30)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e, mean, (SD); \u003csup\u003e\u0026sect;\u003c/sup\u003e, median, range; RC, retrospective Cohort; RC PSM, Retrospective Cohort with Propensity Score Matching; BMI, body mass index; eGFR, estimated glomerular filtration rate; GLP-1 RA, glucagon-like peptide-1 receptor agonist; HbA1c, hemoglobin A1c; uACR, urine albumin/creatinine ratio.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eQuality Assessment\u003c/h2\u003e\u003cp\u003eFunnel plots for mortality and MAKEs appeared symmetric, indicating a low risk of publication bias. Risk of bias was assessed using the ROBINS-I tool. Sahi et al. (2025) was judged to have a serious risk of bias, primarily due to a large imbalance between the treatment and control groups, which raises concerns about confounding and comparability [21]. The remaining studies were assessed as having a moderate risk of bias.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this meta-analysis of four retrospective cohort studies including 27,153 adult kidney transplant recipients with type 2 DM, the use of GLP-1 RAs was associated with favorable clinical outcomes: (1) a significant reduction in all-cause mortality, with a pooled aHR of 0.52 (95% CI: 0.32\u0026ndash;0.85; I\u0026sup2; = 86%; p\u0026thinsp;=\u0026thinsp;0.009), indicating a 38% lower risk of death compared to nonusers; and (2) a significant reduction in the risk of MAKEs, with a pooled aHR of 0.62 (95% CI: 0.53\u0026ndash;0.73; I\u0026sup2; = 15%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). Although a pooled analysis could not be performed as only one study reported MACE outcomes, Lin et al. found a significant 34% reduction in risk with GLP-1 RA use (aHR 0.66; 95% CI: 0.56\u0026ndash;0.79; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in kidney transplant recipients with type 2 diabetes.\u003c/p\u003e\u003cp\u003eGLP-1 RAs have demonstrated substantial benefits beyond glycemic control, particularly in reducing kidney and cardiovascular risks in patients with type 2 diabetes. Evidence from several large randomized controlled trials, such as LEADER, SUSTAIN-6, REWIND, and the more recent SELECT trial consistently supports these effects [7, 23\u0026ndash;25]. A comprehensive meta-analysis of over 85,000 participants reported that GLP-1 RAs reduced the risk of composite kidney outcomes by 18%, kidney failure by 16%, major adverse cardiovascular events (MACE) by 13%, and all-cause mortality by 12%, with no significant increase in serious adverse events [25]. These findings highlight the therapeutic potential of GLP-1 RAs in improving kidney and cardiovascular outcomes in high-risk populations.\u003c/p\u003e\u003cp\u003eThis meta-analysis showed a significant reduction in all-cause mortality with GLP-1 RA use, with a pooled aHR of 0.52 (95% CI: 0.32\u0026ndash;0.85, I\u0026sup2; = 15%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). However, sensitivity analyses indicate that this observed benefit is not fully robust. Leave-one-out analyses revealed that excluding influential studies such as Lin et al. or Sahi et al. resulted in non-significant associations, suggesting that the overall effect is largely driven by a few studies with substantial weight or strong effect sizes. These findings underscore the need for cautious interpretation, as the evidence is somewhat inconsistent across the included studies. Nonetheless, the results provide preliminary support for a potential mortality benefit, which warrants further confirmation in larger, high-quality studies.\u003c/p\u003e\u003cp\u003eThe kidney-protective mechanisms of GLP-1 receptor agonists (GLP-1 RAs) are not yet fully elucidated but are believed to involve both direct renal and systemic effects. Proposed mechanisms include natriuresis via inhibition of sodium-hydrogen exchanger 3 (NHE3) in the proximal tubules, suppression of the intrarenal renin-angiotensin system, and improved kidney oxygenation by reducing ischemia and hypoxia [27,28]. These effects are supported by human studies demonstrating GLP-1 receptor expression in key renal structures, including proximal tubules, juxtaglomerular cells, and preglomerular vessels [28]. Furthermore, GLP-1 RAs may exert anti-inflammatory effects by inhibiting angiotensin II signaling, reducing oxidative stress, and promoting M2 macrophage polarization, as shown in experimental models of Kidney disease in patients with diabetes mellitus [30,31]. The cardioprotective effects of GLP-1 RAs are believed to result from their pleiotropic actions. Preclinical studies suggest that these agents may reduce atherosclerosis by decreasing vascular inflammation, minimizing oxidative stress, and inhibiting the proliferation and activation of vascular smooth muscle cells [32,33].\u003c/p\u003e\u003cp\u003eStudies investigating the use of GLP-1 receptor agonists (GLP-1 RAs) in kidney transplant patients are currently limited and primarily consist of small and retrospective cohort analyses. GLP-1 RAs have demonstrated promising effects on weight and glycemic control in kidney transplant recipients. Mahmoud et al. reported a reduction in BMI of 0.34 kg/m\u0026sup2; among GLP-1 RA users, while the control group showed a minimal increase of 0.015 kg/m\u0026sup2; [33]. Furthermore, after one year, recipients treated with GLP-1 RAs experienced a 0.4% reduction in HbA1c, while no change was observed in the control group (P\u0026thinsp;=\u0026thinsp;.009). Similarly, a study by Mahzari et al., involving patients with pre-existing type 2 DM or post-transplant diabetes mellitus, found that semaglutide significantly lowered HbA1c levels and body weight [10]. Singh et al. showed that, in a cohort of 63 solid organ transplant recipients, there was a sustained and statistically significant reduction in the primary endpoints, such as weight, body mass index (BMI), and insulin requirements at 6, 12, and 24 months, respectively [34].\u003c/p\u003e\u003cp\u003eIn a retrospective cohort of Japanese kidney transplant recipients, GLP-1 RA use was linked to a significantly lower risk of sustained eGFR reduction\u0026thinsp;\u0026ge;\u0026thinsp;40% at 4 months post-transplant (OR 0.105; 95% CI: 0.012\u0026ndash;0.961; p\u0026thinsp;=\u0026thinsp;0.046) after propensity score matching [12]. Similarly, Singh et al. reported a 15% increase in eGFR with dulaglutide treatment, compared to an 8% decrease with liraglutide in kidney transplant patients [34]. Krisanapan et al. conducted a meta-analysis including 338 kidney transplant recipients from nine cohort studies. Their findings showed that GLP-1 RA treatment did not lead to significant changes in eGFR (SMD \u0026minus;\u0026thinsp;0.07 mL/min/1.73m\u0026sup2;; 95% CI: \u0026minus;0.64 to 0.50) or serum creatinine levels (SMD \u0026minus;\u0026thinsp;0.08 mg/dL; 95% CI: \u0026minus;0.44 to 0.28). However, GLP-1 RA therapy was associated with significant reductions in HbA1c levels (SMD \u0026minus;\u0026thinsp;0.85%; 95% CI: \u0026minus;1.41 to \u0026minus;\u0026thinsp;0.28) and urine protein-to-creatinine ratio (SMD \u0026minus;\u0026thinsp;0.47; 95% CI: \u0026minus;0.77 to \u0026minus;\u0026thinsp;0.18) [13]. In the study by Liou et al., renal graft function showed a significant improvement, with the estimated glomerular filtration rate (eGFR) increasing from 67.7\u0026thinsp;\u0026plusmn;\u0026thinsp;18.7 to a peak of 76.5\u0026thinsp;\u0026plusmn;\u0026thinsp;18.7 mL/min/1.73 m\u0026sup2; (P\u0026thinsp;=\u0026thinsp;.024). However, no significant change was observed in the urinary protein-to-creatinine ratio [35]. Our meta-analysis demonstrated that GLP-1 receptor agonist use in kidney transplant recipients with type 2 diabetes was associated with a significantly lower risk of MAKEs, with a pooled adjusted hazard ratio of 0.65 (95% CI 0.57\u0026ndash;0.74). However, we acknowledge that the definitions of MAKE varied across the included studies. These differences may have introduced heterogeneity and limit the direct comparability of the findings, although sensitivity analyses supported the robustness of the overall effect.\u003c/p\u003e\u003cp\u003eA study by Dotan et al. reported data on MACE, the findings were notable. In this study, which included 318 diabetic transplant recipients (kidney, lungs, liver, heart) with a median follow-up of 3.1 years, GLP-1 RA use was associated with a substantial reduction in MACE risk (HR 0.46; 95% CI: 0.27\u0026ndash;0.78) [36]. This suggests a potential cardioprotective effect of GLP-1 RAs in this high-risk population, although further data are needed to confirm this observation.\u003c/p\u003e\u003cp\u003eGLP-1RAs can delay gastric emptying, potentially affecting the absorption of oral drugs like immunosuppressants. While dose adjustments are usually unnecessary and interactions are few, starting with low doses and slow titration is recommended due to GI side effects. Dose changes may depend on treatment goals, kidney function, and medication type, but data on dosing in kidney transplant patients are limited. Careful dose management is important to avoid hypoglycemia when GLP-1RAs are combined with other glucose-lowering drugs [37].\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eStrength and Limitations\u003c/h2\u003e\u003cp\u003eWhile previous meta-analyses have primarily focused on the effects of GLP-1 RAs on kidney function, weight loss, glycemic control, or short-term safety outcomes in kidney transplant recipients, to our knowledge, this is the first meta-analysis to assess their impact on overall mortality and major adverse kidney events (MAKEs).\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, all included studies were retrospective cohorts, which are inherently subject to confounding and selection bias. Although adjustments were made for baseline characteristics, residual confounding cannot be ruled out. Second, the number of studies and sample sizes were relatively small, particularly for outcomes such as MAKE, MACE, and mortality, which limits the statistical power and generalizability of the findings. Third, there was heterogeneity in the definitions of MAKE among the included studies. Although all outcomes reflected clinically meaningful adverse kidney events, the lack of a standardized definition may have affected the comparability of results and should be considered when interpreting our findings. Fourth, the number of studies and events for MACE was limited, precluding a robust meta-analysis of cardiovascular outcomes. Fifth, variability in study populations, GLP-1 RA agents used, dosages, and follow-up durations may have contributed to heterogeneity. Finally, important clinical details such as baseline kidney function, immunosuppressive regimens, and comorbidities were not uniformly reported across studies, restricting the ability to perform more detailed subgroup analyses.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis meta-analysis suggests that GLP-1 RAs may be associated with reduced risks of all-cause mortality and major adverse kidney events in kidney transplant recipients; however, the observed benefit appears to be influenced by a few large, high-weight studies, highlighting variability across the evidence and the need for cautious interpretation. Further well-designed, large-scale studies are warranted to confirm the potential mortality benefit and to better understand which patient populations are most likely to derive clinically meaningful effects.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003cbr\u003e\u003c/strong\u003eThis study is a meta-analysis and did not involve direct human or animal subjects; therefore, ethics approval and consent to participate were not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003cbr\u003e\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003cbr\u003e\u003c/strong\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003cbr\u003e\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003cbr\u003e\u003c/strong\u003eNo financial support was received for this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eS. 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Liou, Y.-M. Liu, ve C.-H. Chen, \u0026ldquo;Management of Diabetes Mellitus With Glucagonlike Peptide-1 Agonist Liraglutide in Renal Transplant Recipients: A Retrospective Study.\u0026rdquo;, \u003cem\u003eTransplant. Proc.\u003c/em\u003e, c. 50, sy 8, ss. 2502-2505, Eki. 2018, doi: 10.1016/j.transproceed.2018.03.087.\u003c/li\u003e\n\u003cli\u003eI. Dotan \u003cem\u003evd.\u003c/em\u003e, \u0026ldquo;Glucagon-like Peptide 1 Receptor Agonists and Cardiovascular Outcomes in Solid Organ Transplant Recipients With Diabetes Mellitus.\u0026rdquo;, \u003cem\u003eTransplantation\u003c/em\u003e, c. 108, sy 7, ss. e121-e128, Tem. 2024, doi: 10.1097/TP.0000000000004945.\u003c/li\u003e\n\u003cli\u003eP. Singh, M. Taufeeq, T. E. Pesavento, K. Washburn, D. Walsh, ve S. Meng, \u0026ldquo;Comparison of the glucagon-like-peptide-1 receptor agonists dulaglutide and liraglutide for the management of diabetes in solid organ transplant: A retrospective study.\u0026rdquo;, \u003cem\u003eDiabetes Obes. Metab.\u003c/em\u003e, c. 22, sy 5, ss. 879-884, May. 2020, doi: 10.1111/dom.13964.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"GLP-1 RAs, kidney transplantation, mortality, MACE, MAKE","lastPublishedDoi":"10.21203/rs.3.rs-7859743/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7859743/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003cbr\u003e\n \u003c/strong\u003eGlucagon-like peptide-1 receptor agonists (GLP-1 RAs) are increasingly used in patients with type 2 diabetes and chronic kidney disease. However, their safety and efficacy in kidney transplant recipients remain uncertain. This study aims to evaluate the impact of GLP-1 RAs on all-cause mortality, major adverse cardiovascular events (MACE), and major adverse kidney events (MAKE) in adult kidney transplant recipients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003cbr\u003e\n \u003c/strong\u003eWe conducted a systematic review and meta-analysis of retrospective cohort studies reporting outcomes in adult kidney transplant recipients treated with GLP-1 RAs. A comprehensive search of PubMed, Embase and Cochrane Library was performed up to July 2025. Studies were included if they reported on at least one of the following outcomes: all-cause mortality, MACE, or MAKE. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using a random-effects model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003cbr\u003e\n \u003c/strong\u003eA total of four retrospective cohort studies involving 27,153 were included. A total of 5,479 (20.2%) patients received GLP-1 RAs. The median follow-up period across studies ranged from 1.38 to 3.1 years. GLP-1 RAs treatment was associated with a significant reduction in all-cause mortality, with an aHR of 0.52 (95% CI: 0.32–0.85, I² = 86%; p = 0.009). Similarly, a significant reduction in MAKEs was observed, with a pooled aHR of 0.62 (95% CI, 0.53-0.73; I² = 15%; p \u0026lt; 0.00001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003cbr\u003e\n \u003c/strong\u003eIn kidney transplant recipients, GLP-1 RAs appear to be associated with reduced risks of all-cause mortality and MAKEs. These findings support the potential role of GLP-1 RAs in this population, however prospective studies are needed to confirm long-term safety and efficacy.\u003c/p\u003e","manuscriptTitle":"GLP-1 Receptor Agonists in Kidney Transplant Recipients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis on Mortality and Major Adverse Kidney Events","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 14:53:07","doi":"10.21203/rs.3.rs-7859743/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9e730c84-eb67-4c58-83e8-f56353b3fef5","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:00:52+00:00","versionOfRecord":{"articleIdentity":"rs-7859743","link":"https://doi.org/10.1007/s40200-025-01801-7","journal":{"identity":"journal-of-diabetes-and-metabolic-disorders","isVorOnly":false,"title":"Journal of Diabetes \u0026 Metabolic Disorders"},"publishedOn":"2026-01-08 15:57:22","publishedOnDateReadable":"January 8th, 2026"},"versionCreatedAt":"2025-10-29 14:53:07","video":"","vorDoi":"10.1007/s40200-025-01801-7","vorDoiUrl":"https://doi.org/10.1007/s40200-025-01801-7","workflowStages":[]},"version":"v1","identity":"rs-7859743","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7859743","identity":"rs-7859743","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}