Risk Of Post-transplant Diabetes Mellitus Research Articles

Perioperative glucose monitoring with continuous glucose monitors identifies risk factors for post-transplant diabetes mellitus in kidney transplant recipients

Post-transplantation diabetes mellitus (PTDM) negatively affects graft and patient survival after kidney transplantation (KT). This prospective study used continuous glucose monitoring (CGM) to evaluate perioperative blood glucose dynamics, identify PTDM risk factors, and compare predictive accuracy with capillary blood glucose monitoring (CBGM) in 60 non-diabetic living-donor KT recipients. Patients underwent 2-week pre- and postoperative CGM, including routine CBGM during their in-hospital stays. PTDM-related risk factors and glucose profiles were analyzed with postoperative CGM and CBG. PTDM developed in 14 (23.3%) patients and was associated with older age, male sex, higher baseline HbA1c, high-density lipoprotein cholesterol, and 3-month cumulative tacrolimus exposure levels. Male sex and postoperative time above the range (TAR) of 180 mg/dL by CGM were PTDM-related risk factors in the multivariate analysis. For predictive power, the CGM model with postoperative glucose profiles exhibited higher accuracy compared with the CBGM model (areas under the curves of 0.916, and 0.865, respectively). Therefore, we found that male patients with a higher postoperative TAR of 180 mg/dL have an increased risk of PTDM. Postoperative CGM provides detailed glucose dynamics and demonstrates superior predictive potential for PTDM than CBGM.

Hypomagnesaemia, an independent risk factor for the development of post-transplant diabetes mellitus in liver and renal transplant recipients? A systematic review.

Post-transplantation diabetes mellitus (PTDM) is common after solid organ transplantation. In the past decade, there has been increasing interest in the association between hypomagnesaemia and the development of PTDM. This systematic review aimed to investigate the current knowledge regarding the association between hypomagnesaemia and PTDM in adult liver and renal transplant recipients. A literature search of five databases, Medline, Embase, ProQuest, Scopus and Google Scholar, as well as article reference lists, was performed. Eligible studies that focused on adult liver and renal transplant recipients without pretransplantation hyperglycaemia or diabetes were included. Other eligibility criteria included quantitative studies which reported magnesium concentrations, studies with at least 6 months of follow-up, and studies published in English. The Newcastle-Ottawa Assessment Tool was used for the quality assessment. In total, 12 studies were included in the final analysis. Eleven focused on renal transplantation and one on liver transplantation. All studies were medium to high quality with eight out of 12 achieving the highest rating of nine. Eight studies found a negative association between either pretransplant or early post-transplant serum magnesium concentration and the risk of PTDM, three studies found no association between these two variables, and one study found a positive association between the magnesium concentration at 8 weeks after transplantation and glycosylated haemoglobin A1C. Further large-scale prospective studies with at least 6 months of follow-up are needed to confirm these findings, particularly in liver transplantation, to further clarify and explore the relationship between hypomagnesaemia and PTDM.

#1680 Cardiovascular disease in kidney transplant recipients with post-transplant diabetes mellitus—retrospective analysis from a randomized trial

Abstract Background and Aims Kidney transplant recipients are at risk for glucometabolic deterioration. While many individuals recover their glycemic profiles, some develop posttransplant diabetes mellitus (PTDM). Previous reports have shown that PTDM is associated with increased risk for cardiovascular disease (CVD) and mortality. Here we aimed at assessing the association of PTDM with the development of CVD in kidney transplant recipients from a randomized trial. Method CVD with functioning graft (WFG), all-cause death WFG and death-censored graft loss were retrospectively investigated in N = 263 participants from the Insulin Therapy for the Prevention of New Onset Diabetes after Transplantation multicenter randomized-controlled trial (ITP-NODAT, ClinicalTrials.gov NCT03507829). The clinical trial was conducted from November 2012 through May 2018; kidney transplant recipients without previous diabetes diagnosis had received basal insulin therapy or control for afternoon hyperglycemia. For the current analysis, CVD was defined as a composite of cerebrovascular disease (stroke, transient ischemic attack), coronary artery disease (myocardial infarction, revascularization, stenting), hospitalization for heart failure and vascular/peripheral arterial disease interventions. Participants were to perform three OGTTs at 6, 12 and 24 months posttransplant, which we handled as landmarks in our present analysis. Besides PTDM versus NON-PTDM, we stratified according to basal insulin intervention and control. Cox proportional hazard models were presented unadjusted and adjusted for age, sex and pre-transplant CVD. All patients gave informed consent to participate in the trial and we obtained institutional review board approval for the present analysis. Results Cumulative incidence curves for CVD WFG are presented in Fig. 1. The associated risk of PTDM at 6, 12 and 24 months for CVD WFG tended to be higher in PTDM versus NON-PTDM. At the respective timepoints, the control versus basal insulin groups were similar (Fig. 1). Cause-specific hazard ratios for CVD WFG, all-cause death WFG and death-censored graft loss are presented in Table 1. PTDM was associated with CVD WFG in the univariable models. Corresponding Hazard Ratios (with 95% Confidence Intervals) at 6, 12 and 24 months were 2.53 (1.23, 5.18), 3.19 (1.51, 6.78) and 4.28 (1.94, 9.48), respectively. After adjustment for age, sex and pre-transplant history of CVD, corresponding HRs (95% CIs) were 1.37 (0.64, 2.91), 1.37 (0.61, 3.06) and 3.01 (1.26, 7.22), respectively. PTDM was not associated with all-cause death WFG in the univariable models. Corresponding HRs (95% CIs) at 6, 12 and 24 months were 1.97 (0.82, 4.75), 2.44 (0.95, 6.25) and 2.32 (0.89, 6.05), respectively. PTDM was also not associated with death-censored graft loss in the univariable models. Corresponding HRs (95% CIs) at 6, 12 and 24 months were 1.44 (0.62, 3.36), 2.10 (0.89, 4.94) and 1.15 (0.39, 3.37), respectively. PTDM was neither associated with all-cause death WFG or death-censored graft loss in the adjusted models. Conclusion PTDM diagnosed by OGTT at month 24 was significantly associated with cardiovascular disease independent of age, sex or pre-transplant CVD. The association, however, was not significant when PTDM was diagnosed before month 24. It is possible that transient PTDM diagnosis, early CVD events and study discontinuations before month 24 may have contributed to the differing results over time. Timely PTDM diagnosis may open a window of opportunity for interventions, such as in the form of novel glucose-lowering agents, that may reduce cardiovascular risk in kidney transplant recipients.

#2205 Varying practice patterns in prevention, screening and treatment of diabetes early after kidney transplantation: a European survey

Abstract Background and Aims Although post-transplant diabetes mellitus (PTDM) is a common complication after kidney transplantation, there is no consensus on preventive measures, nor on the optimal screening and treatment strategy. Method The European Renal Association—DESCARTES working group—distributed a web-based survey to transplant centers across Europe to gather information on the risk assessment, screening procedures and management practices for the prevention and treatment of PTDM in kidney-transplant recipients. Results Answers were obtained from 121 transplant centers across 15 European countries. Screening practices for pre-existing diabetes during the transplant work-up varied considerably, with only 13% of centers using the recommended oral glucose tolerance test (OGTT), while 14% did not screen at all. At transplantation, 19% (n = 23) of centers tailored the immunosuppressive regimen based on perceived PTDM risk, employing strategies like cyclosporin use (12/23), or early steroid withdrawal (2/23). Fifty-two percent adopted strict glycemic control with long-acting insulin in the first days post-transplant. Sixty-eight percent had defined screening protocols for early PTDM (45 days—six months), mostly based on fasting glycemia and/or HbA1c, while only 8/82 incorporated an OGTT. Changes in immunosuppression were considered by 41% in cases of early hyperglycemia (<45 days) and by 58% in established PTDM (>45 days). Besides insulin therapy, dipeptidyl peptidase-4 (DPP4) inhibitors and metformin were most frequently used to manage early hyperglycemia (<45 days) and PTDM (>45 days). Conclusion This European survey underscores significant variation in PTDM prevention, screening, and treatment practices, emphasizing the imperative for clearer guidance in approaching this complication.

An update review of post-transplant diabetes mellitus: Concept, risk factors, clinical implications and management.

Kidney transplantation is the gold standard therapeutic alternative for patients with end-stage renal disease; nevertheless, it is not without potential complications leading to considerable morbidity and mortality such as post-transplant diabetes mellitus (PTDM). This narrative review aims to comprehensively evaluate PTDM in terms of its diagnostic approach, underlying pathophysiological pathways, epidemiological data, and management strategies. Articles were retrieved from electronic databases using predefined search terms. Inclusion criteria encompassed studies investigating PTDM diagnosis, pathophysiology, epidemiology, and management strategies. PTDM emerges as a significant complication following kidney transplantation, influenced by various pathophysiological factors including peripheral insulin resistance, immunosuppressive medications, infections, and proinflammatory pathways. Despite discrepancies in prevalence estimates, PTDM poses substantial challenges to transplant. Diagnostic approaches, including traditional criteria such as fasting plasma glucose (FPG) and HbA1c, are limited in their ability to capture early PTDM manifestations. Oral glucose tolerance test (OGTT) emerges as a valuable tool, particularly in the early post-transplant period. Management strategies for PTDM remain unclear, within sufficient evidence from large-scale randomized clinical trials to guide optimal interventions. Nevertheless, glucose-lowering agents and life style modifications constitute primary modalities for managing hyperglycemia in transplant recipients. The complex interplay between PTDM and the transplant process necessitates individualized diagnostic and management approaches. While early recognition and intervention are paramount, modifications to maintenance immunosuppressive regimens based solely on PTDM risk are not warranted, given the potential adverse consequences such as increased rejection risk. Further research is essential to refine management strategies and enhance outcomes for transplant recipients.

Collaborative inference for treatment effect with distributed data-sharing management in multicenter studies.

Data sharing barriers present paramount challenges arising from multicenter clinical studies where multiple data sources are stored and managed in a distributed fashion at different local study sites. Merging such data sources into a common data storage for a centralized statistical analysis requires a data use agreement, which is often time-consuming. Data merging may become more burdensome when propensity score modeling is involved in the analysis because combining many confounding variables, and systematic incorporation of this additional modeling in a meta-analysis has not been thoroughly investigated in the literature. Motivated from a multicenter clinical trial of basal insulin treatment for reducing the risk of post-transplantation diabetes mellitus, we propose a new inference framework that avoids the merging of subject-level raw data from multiple sites at a centralized facility but needs only the sharing of summary statistics. Unlike the architecture of federated learning, the proposed collaborative inference does not need a center site to combine local results and thus enjoys maximal protection of data privacy and minimal sensitivity to unbalanced data distributions across data sources. We show theoretically and numerically that the new distributed inference approach has little loss of statistical power compared to the centralized method that requires merging the entire data. We present large-sample properties and algorithms for the proposed method. We illustrate its performance by simulation experiments and the motivating example on the differential average treatment effect of basal insulin to lower risk of diabetes among kidney-transplant patients compared to the standard-of-care.

Does Antibiotic Use Increase the Risk of Post-Transplantation Diabetes Mellitus? A Retrospective Study of Renal Transplant Patients.

BACKGROUND This study aimed to investigate the incidence of post-transplant diabetes mellitus (PTDM) in renal transplant (RT) patients at our center and to explore new risk factors for PTDM. MATERIAL AND METHODS This retrospective study included RT patients from 2010 to 2022. Clinic data on RT patients were obtained from hospital electronic medical records. CYP3A5*3, POR*28, ABCB1 (3435 C>T), and ABCB1 (1236 C>T) were genotyped in RT patients. The associations between age, BMI, concentration of tacrolimus (TAC), polymorphism of genes, antibiotics (eg, penicillins, cephalosporins, oxazolidinones, quinolones), numbers and days of antibiotic use, and PTDM were analyzed. RESULTS In this study, 409 patients with RT were included. The cumulative incidence of PTDM in the first year after RT was 9.05%. The numbers and days of antibiotic use in PTDM patients were significantly higher than those in non-PTDM patients. Multivariate logistic regression analysis identified age (OR=1.047, P=0.014), body mass index (BMI) (OR=1.178, P=0.007), dose-adjusted trough concentration of TAC (TAC C₀/D) at 7 days after RT (OR=1.159, P=0.042), trough concentration of TAC (TAC C₀) at 28 days after RT (OR=1.094, P=0.042), and levofloxacin (OR=5.975, P=0.003) as independent risk factors for PTDM. CONCLUSIONS In addition to age, BMI, and TAC concentration after RT, antibiotic use may be a novel factor affecting PTDM. The use of antibiotics may influence the development of PTDM.

Time-updated Fibroblast Growth Factor 23 Is Predictive for Posttransplant Diabetes Mellitus in Kidney Transplant Recipients.

This work aimed to study whether fibroblast growth factor 23 (FGF23) is predictive for incident posttransplant diabetes mellitus (PTDM) in kidney transplant recipients (KTRs). We repeatedly analyzed plasma C-terminal FGF23 concentrations in 170 KTRs enrolled in the TransplantLines Biobank and Cohort Study. Associations of time-updated plasma FGF23 with incident PTDM were studied by Cox regression. A total of 170 KTRs (46% female, aged 54.4 ± 12.4 years) with 540 FGF23 measurements were included. Plasma FGF23 concentrations at transplantation were 31.1 (0.76-2576) pmol/L. During a follow-up of 24 (12-24) months, 38 patients developed PTDM. The highest FGF23 tertile (compared to the lowest) was associated with an increased risk for PTDM (fully adjusted hazard ratio 20.9; 95% CI, 3.4-130.0; P < .001). In KTRs without diabetes at baseline, the highest tertile of FGF23, compared to the lowest, is predictive for development of PTDM.

Pancreatic steatosis is an independent risk factor for post-transplant diabetes mellitus in kidney transplant patients.

Post-transplant diabetes mellitus (PTDM) is associated with an increased risk of post-transplant cardiovascular diseases, and several risk factors of PTDM have been shown in the literature. Yet, the relationship between hepatic and pancreatic steatosis with post-transplant diabetes mellitus remains vague. We aimed to evaluate pancreatic steatosis, a novel component of metabolic syndrome, and hepatic steatosis association with post-transplant diabetes mellitus in a single-center retrospective cohort study conducted on kidney transplant recipients. We have performed a single-center retrospective cohort study involving all kidney transplant recipients. We have utilized pretransplant Fibrosis-4, nonalcoholic fatty liver disease fibrosis score, and abdominal computed tomography for the assessment of visceral steatosis status. We have included 373 kidney transplant recipients with a mean follow-up period of 32 months in our final analysis. Post-transplant diabetes mellitus risk is associated with older age (p<.001), higher body-mass index (p<.001), nonalcoholic fatty liver disease-fibrosis score (p=.002), hepatic (p<.001) or pancreatic (p<.001) steatosis on imaging and higher pre-transplant serum triglyceride (p=.003) and glucose levels (p=.001) after multivariate analysis. Our study illustrates that recipients' pancreatic steatosis is an independent predictive factor for post-transplant diabetes mellitus including in kidney transplant patients.

Development and Validation of a New Score to Assess the Risk of Posttransplantation Diabetes Mellitus in Kidney Transplant Recipients.

Posttransplantation diabetes mellitus (PTDM) is a serious complication of solid organ transplantation. It is associated with major adverse cardiovascular events, which are a leading cause of morbidity and mortality in transplant patients. This study aimed to develop and validate a score to predict the risk of PTDM in kidney transplant recipients. A single-center retrospective cohort study was conducted in a tertiary care hospital in Medellín, Colombia, between 2005 and 2019. Data from 727 kidney transplant recipients were used to develop a risk prediction model. Significant predictors with competing risks were identified using time-dependent Cox proportional hazard regression models. To build the prediction model, the score for each variable was weighted using calculated regression coefficients. External validation was performed using independent data, including 198 kidney transplant recipients from Tübingen, Germany. Among the 727 kidney transplant recipients, 122 developed PTDM. The predictive model was based on 5 predictors (age, gender, body mass index, tacrolimus therapy, and transient posttransplantation hyperglycemia) and exhibited good predictive performance (C-index: 0.7 [95% confidence interval, 0.65-0.76]). The risk score, which included 33 patients with PTDM, was used as a validation data set. The results showed good discrimination (C-index: 0.72 [95% confidence interval, 0.62-0.84]). The Brier score and calibration plot demonstrated an acceptable fit capability in external validation. We proposed and validated a prognostic model to predict the risk of PTDM, which performed well in discrimination and calibration, and is a simple score for use and implementation by means of a nomogram for routine clinical application.

Tacrolimus and Diabetes in Kidney Transplantation: The Impact of Cyp3a5 Gene Polymorphism

To explore the correlation between single nucleotide polymorphisms (SNPs) of CYP3A4 rs2740574 and CYP3A5 rs776746 and post-transplant diabetes mellitus (PTDM) in Chinese renal allograft recipients treated with tacrolimus. A total of 244 patients treated with tacrolimus were included in this study, wherein DNA sequencing was detected through fluorescence in situ hybridization, and SNP genotyping was performed. Among the 244 patients, 44 (18%) developed PTDM. The PTDM group exhibited higher preoperative body mass index and fasting plasma glucose levels, with higher creatinine values one year after surgery. The CYP3A4 rs2740574 genotype was found to be unique in its homozygous AA form. For CYP3A5 rs776746, the genotypes were distributed as follows: 28 (11.5%) cases with AA, 101 (41.4%) cases with AG, and 115 (47.1%) cases with GG, respectively (P=.042). The AA genotype showed a statistically significant difference from both AG and GG genotypes. Furthermore, the A allele of CYP3A5 rs776746 was found to be associated with an increased risk for PTDM development. The occurrence of tacrolimus-related PTDM is associated with body mass index, fasting plasma glucose levels, and CYP3A5 genotype before renal transplantation. Post-transplant diabetes mellitus is correlated with unfavorable long-term renal graft function, whereas the expression of the CYP3A5 rs776746 gene is linked to an elevated risk of PTDM.

Influence of Early Postoperative Basal Insulin Treatment and Post-Transplant Diabetes Mellitus Risk on Health-Related Quality of Life in Kidney Transplant Recipients-An Analysis of Data From a Randomized Controlled Trial.

Health-related quality of life (HRQOL) improves after kidney transplantation (KT) but declines over time. Studies on the effect of early postoperative basal insulin therapy on HRQOL after KT, especially KTRs at high risk of developing post-transplant diabetes mellitus (PTDM) are missing. Data from a randomized controlled trial on 148 non-diabetic KTRs were analyzed. HRQOL using the KDQOL-SF™ was compared in KTRs who either received early postoperative basal insulin therapy or standard-of-care and in KTRs at risk of developing PTDM. Determinants of HRQOL outcomes were investigated using multivariable linear regression analysis. In total, 148 patients completed the KDQOL-SF at baseline. Standard-of-care or early basal insulin therapy after KT did not influence HRQOL. Overall, KT improved the mental (MCS) and physical component summary (PCS) scores at 6-month after KT, which remained stable during further follow-up visits. However, patients at high-risk for PTDM had significantly greater impairment in the PCS score (baseline, 24months) without differences in MCS scores. In the multivariable regression analysis, allograft function and hemoglobin levels were associated with decreased MCS and PCS scores, respectively. A limitation of the study is the fact that only around 50% of the ITP-NODAT study patients participated in the HRQOL evaluation. Still, our data clearly show that early basal insulin therapy does not affect HRQOL after KT but is negatively influenced by classical clinical factors and PTDM-risk at 24months after KT. The latter might be influenced by older age.

#4045 IMMUNOSUPPRESSION AND POST-TRANSPLANT HYPERGLYCEMIA

Abstract Background and Aims Post-transplant diabetes mellitus (PTDM) is a frequent complication after kidney transplantation (KT), with an incidence between 20-30%. PTDM increases the risk of cardiovascular disease, which is one of the main causes of death with functioning grafts. The pathophysiology of PTDM involves beta-cell dysfunction, with impaired insulin secretion and insulin resistance overlaid immunosuppression accelerating preexisting damage. The major risk factor in the post-transplant period is immunosuppression therapy, such as steroids, calcineurin inhibitors (CNI), and mTOR inhibitors (mTORi). It is also a major modifiable risk but must be balanced with rejection risk. This systematic review aims to investigate the effect of different immunosuppressive regimens on the risk of PTDM incidence. Methods Relevant studies were obtained from a systematic literature search. We searched MEDLINE and CENTRAL (Cochrane Central Register of Controlled Trials) until 1st May 2022. We searched randomized controlled trials (RCT) including KT recipients receiving any immunosuppression and reporting PTDM outcomes. The definition of PTDM was whatever was used by the authors. Meta-analysis was done by pooling data for calculating the relative risks (RR) of the outcome by comparing different immunosuppression strategies. Results We identified 1,848 reports. After removing duplicates and screening titles and abstracts 156 full-text reports were assessed. We finally included 52 studies. Eight RCTs reported the outcome of PTDM using different induction therapies at ≤7 years after KT, with a total included a population of 1,495 recipients. The meta-analysis of all studies did not show differences in the risk of post-transplant diabetes mellitus in any of the comparisons. 49 RCTs evaluated mTORi use: 32 at de novo KT and 17 long-term follow-up conversions. When comparing mTORi vs antimetabolite there was a higher risk of PTDM in the mTORi group at ≤5 years postKT (22 studies, 8,178 participants, RR 1.25, 95%CI [1.05-1.49], p = 0.01). When comparing mTORi vs CNI there were no differences in PTDM risk at ≤5 years postKT (12 studies, 2,537 participants, RR 0.81, 95%CI [0.48-1.40], p = 0.46). Conversions from CNI to mTORi at ≤2 years postKT showed an increased risk of PTDM (15 studies, 3,200 participants, RR 1.60, 95%CI [1.14-2.23], p&amp;lt;0.01). We found 39 RCTs that reported PTDM outcomes in KT receiving CNI. In de novo KT, there was an increased risk of developing PTDM with tacrolimus rather than with ciclosporin (26 studies, 5,635 patients, RR 1.71, 95%CI [1.38-2.11], p&amp;lt;0.01) after ≤5 years postKT. There were no differences comparing different doses or tacrolimus formulations. When belatacept was compared to CNI we found a 38% reduction at 1-year post-KT in the risk of developing PTDM (6 studies, 2,100 participants, RR 0.62, 95% CI [0.42-0.91], p = 0.02). Conclusion A higher risk of PTDM was observed in patients receiving TAC vs CsA, and mTORi inhibitors. Belatacept showed a 38% reduction in PTDM compared to CNI. However, the risk of PTDM should be balanced with the risk of rejection.

MTOR-inhibitors and post-transplant diabetes mellitus: a link still debated in kidney transplantation.

The mammalian target of rapamycin inhibitors (mTOR-Is, Sirolimus, and Everolimus) are immunosuppressive drugs widely employed in kidney transplantation. Their main mechanism of action includes the inhibition of a serine/threonine kinase with a pivotal role in cellular metabolism and in various eukaryotic biological functions (including proteins and lipids synthesis, autophagy, cell survival, cytoskeleton organization, lipogenesis, and gluconeogenesis). Moreover, as well described, the inhibition of the mTOR pathway may also contribute to the development of the post-transplant diabetes mellitus (PTDM), a major clinical complication that may dramatically impact allograft survival (by accelerating the development of the chronic allograft damage) and increase the risk of severe systemic comorbidities. Several factors may contribute to this condition, but the reduction of the beta-cell mass, the impairment of the insulin secretion and resistance, and the induction of glucose intolerance may play a pivotal role. However, although the results of several in vitro and in animal models, the real impact of mTOR-Is on PTDM is still debated and the entire biological machinery is poorly recognized. Therefore, to better elucidate the impact of the mTOR-Is on the risk of PTDM in kidney transplant recipients and to potentially uncover future research topics (particularly for the clinical translational research), we decided to review the available literature evidence regarding this important clinical association. In our opinion, based on the published reports, we cannot draw any conclusion and PTDM remains a challenge. However, also in this case, the administration of the lowest possible dose of mTOR-I should also be recommended.

Metabolic-Related Index to Predict Post-Transplantation Diabetes Mellitus After Kidney Transplantation.

Metabolic-related markers are novel tools for assessing insulin resistance. Early identification of post-transplantation diabetes mellitus (PTDM) before hyperglycemia can be helpful to attenuate the rapid development of diabetic complications. This article aims to explore the convenient and inexpensive values of metabolic-related markers, including TyG, TyG-BMI, TG/HDL-C, and non-HDL-C/HDL-C for predicting PTDM. The data of 191 kidney transplant recipients in our center were collected retrospectively. The association between TyG, TyG-BMI, TG/HDL-C, non-HDL-C/HDL-C and the risk of PTDM was examined by the area under the curve and logistic regression analyses. During 6 months follow-up, 12.04% of KT recipients developed PTDM, and significantly higher values of TyG-BMI, TyG, and non-HDL-C/HDL-C was found in patients with PTDM than in nondiabetic patients, especially among the recipients taking tacrolimus, regardless of gender. The incidence of PTDM increased along with the values of TyG or TyG-BMI. After adjusting for multiple potential factors, recipients with the highest trisector of TyG or TyG-BMI still had a higher risk of PTDM morbidity. In conclusion, TyG, TyG-BMI, TG/HDL-C and non-HDL-C/HDL-C can be used as cost-effective and promising monitors to identify individuals at high risk of PTDM, and TyG-BMI was the best alternative marker among the four markers.

Pre-transplant HbA1c and risk of diabetes mellitus after kidney transplantation: a single center retrospective analysis.

Post-transplant diabetes mellitus occurs in 10-40% of kidney transplant recipients and is associated with increased risk ofdevelopingcardiovascular diseases. Early identification of patients with a higher risk of developing diabetescould allow to take timely measures. However, no validated model exists to predict the risk of post-transplant diabetes mellitus. This retrospective study includes 267 adult patients who underwent kidney transplantation at the Antwerp University Hospital between January 2014 and August 2021. Post-transplant diabetes mellitus was diagnosed based on the American Diabetes Association definition at 3months post-transplant. First, a logistic regression analysis was used to identify predictors for post-transplant diabetes mellitus. Second, criteria to identify patients with a high risk (> 35%) of developing post-transplant diabetes mellitus at 3months were established. At 3months post-transplantation, 54 (20.2%) patients developed post-transplant diabetes mellitus. Univariable analysis showed that age, body mass index and HbA1c on the day of transplantation were associated with post-transplant diabetes mellitus. However, in a multivariable model with the same parameters, only HbA1c remained statistically significant. An absolute increase in HbA1c of 0.1% increases the odds for developing post-transplant diabetes mellitus by 28% (95% confidence interval 1.15-1.42). An HbA1c level ≥ 5.3% at transplantation, regardless of age or body mass index, is sufficient to identify patients with a post-transplant diabetes mellitus risk of ≥ 35% with a positive predictive value of 39% and a negative predictive value of 88%. The HbA1c value at transplantation was the strongest predictor for post-transplant diabetes mellitus at 3months post-transplant. Furthermore, at least in our population,a pre-transplant HbA1c of ≥ 5.3% can be usedas an easy tool to identify patients at high risk of early post-transplant diabetes mellitus.

Incidence of Statin-Associated Adverse Events in Kidney Transplant Recipients.

Statins are the third most prescribed drug class in kidney transplant recipients as cardiovascular disease is the leading cause of death in this population. However, statins' safety profile remains unclear in kidney transplant recipients who are uniquely burdened by concomitant immunosuppression and comorbidities. We conducted a national study to characterize the association of statin use with adverse events in kidney transplant recipients. We studied adult (18 years or older) single-organ kidney transplant recipients in 2006-2016 with Medicare as primary payer ( n =57,699). We used prescription drug claims to capture statin use and International Classification of Diseases 9/10 diagnosis codes to capture statin-related adverse events (post-transplant diabetes mellitus, hemorrhagic stroke, cataract, liver injury, and rhabdomyolysis). We conducted multivariable Cox regression for each outcome with statin use as a time-varying exposure. Post-transplant diabetes mellitus was the most common outcome (5-year Kaplan-Meier incidence; 43% in statin users versus 35% in nonusers), followed by cataract (22% versus 12%), liver injury (2% versus 3%), hemorrhagic stroke (1.9% versus 1.4%), and rhabdomyolysis (1.5% versus 0.9%). In our multivariable analysis, statin use was associated with higher hazard of post-transplant diabetes mellitus (adjust hazard ratio [aHR], 1.12; 95% confidence interval [95% CI], 1.07 to 1.18), cataract (aHR, 1.22; 95% CI, 1.14 to 1.31), and rhabdomyolysis (aHR, 1.37; 95% CI, 1.10 to 1.71) but lower hazard of liver injury (aHR, 0.82; 95% CI, 0.71 to 0.95). Statin use was not associated with hemorrhagic stroke (aHR, 1.04; 95% CI, 0.86 to 1.26). Statins seem to be generally well tolerated in kidney transplant recipients. However, statin use might be associated with slightly higher risk of post-transplant diabetes mellitus, cataract, and rhabdomyolysis.

Pretransplant BMI Should Be

The aim of this study was to determine the appropriate body mass index (BMI) in Japanese kidney transplant (KTx) recipients. We analyzed the effects of pre- and post-transplant (Tx) obesity on graft and patient survival, perioperative complications, post-transplant diabetes mellitus (PTDM), and cardiovascular disease (CVD) in Japanese KTx recipients. This retrospective study included 269 recipients who underwent KTx from 2008 through 2020 at Niigata University Hospital. Obesity was defined as a body mass index (BMI) ≥25 kg/m2. We examined the association between pre- and post-Tx obesity and graft survival, patient survival, the incidence of PTDM and CVD, and perioperative surgical complications. The graft survival rate was lower in the pre-Tx BMI ≥25 kg/m2 group, although there was no significant difference in patient survival. There was no difference in graft and patient survival between the post-Tx BMI ≥25 kg/m2 group and the <25 kg/m2 group. A pre-Tx BMI ≥25 kg/m2 was an independent risk factor for biopsy-proven allograft rejection. New-onset DM after transplantation was significantly more common in the BMI ≥25 kg/m2 group than in the BMI <25 kg/m2 group (36% vs 13%; P=.002). The incidence of CVD was significantly higher in the post-Tx BMI ≥30 kg/m2 group than in the BMI <30 kg/m2 group (50% vs 11%; P=.023). There were no differences in surgical operating time, intraoperative blood loss, or perioperative complications between the obese and non-obese groups. Pre-Tx BMI ≥25 kg/m2 may be a risk factor for allograft rejection and graft loss. Post-Tx BMI should be <25 kg/m2 to reduce the risk for PTDM.

Adiponectin/Leptin Ratio as an Index to Determine Metabolic Risk in Patients after Kidney Transplantation.

Background and Objectives: It has been confirmed that adiponectin/leptin (A/L) ratio correlates better with cardiometabolic risk factors than hormone levels alone. The aim of our study was to determine the risk of developing post-transplant diabetes mellitus (PTDM) and other metabolic conditions depending on A/L ratio after kidney transplantation (KT). Material and Methods: In a prospective analysis, the studied samples were divided into three groups: control group, prediabetes and PTDM group. Pre-transplantation, at 3, 6 and 12 months after KT, we recorded basic characteristics of donor and recipient. We also monitored levels of adipocytokines and calculated A/L ratio. Results: During observed period, we recorded significant increase in A/L ratio in control group (p = 0.0013), on the contrary, a significant decrease in PTDM group (p = 0.0003). Using Cox regression Hazard model, we identified age at time of KT (HR 2.8226, p = 0.0225), triglycerides at 1 year (HR 3.5735, p = 0.0174) and A/L ratio &lt; 0.5 as independent risk factors for prediabetes and PTDM 1-year post-transplant (HR 3.1724, p = 0.0114). Conclusions: This is the first study to evaluate the relationship between A/L and risk of PTDM and associated metabolic states after KT. We found out that A/L ratio &lt;0.5 is independent risk factor for prediabetes and PTDM 1 year post-transplant.

A Lipotoxic Medium Decreases the Number of Lipid Droplets in β Cells: One Possible Explanation of the β-Cell Failure in Patients With Hyperlipidemia Receiving Tacrolimus.

Dyslipidemia is a risk factor for post- transplant diabetes mellitus, especially in patients who are taking tacrolimus. Although lipotoxicity of dyslipidemia leads to β-cell failure, the handling of lipids by β cells is a mystery in molecular endocrinology. Likewise, lipid droplet homeostasis is appreciated as a key component of lipid metabolism in cells like hepatocytes, but its role in β cells remains to be elucidated. To evaluate the morphologic changes in β cells with special focus on lipid droplets, we evaluated electron micrographs under metabolic stress conditions of glucotoxicity, lipotoxicity, and glucolipotoxicity in isolated rat insulinoma INS-1E β cells. Cells were treated with palmitic acid (0.5 mM), glucose (33 mM), or both for 16 hours, after which morphologic changes were observed with an electron microscope. Many lipid droplets were observed in the cytoplasm of healthy β cells in the control group (no treatment). Lipid droplets were also visible in the cytosol, and the cytoplasm was rich in organelles and insulin vesicles under high glucose stimulation. However, after treatment with palmitic acid, almost no lipid droplets were observed. Endocrine vesicles were also depleted, with severe morphologic disruption of other organelles. Under glucolipotoxic conditions, β cells showed a decreased number of lipid droplets and insulin vesicles compared with controls. Lipid droplet dynamics seemed important in the homeostasis of β-cell metabolism. In this preliminary study, healthy β cells appeared rich in lipid droplets under normal conditions. However, lipotoxicity depleted and glucolipotoxicity decreased the number of lipid droplets in β cells. Because dyslipidemia causing lipotoxicity is one of the most frequent metabolic problems in transplant patients and increases risk of posttransplant diabetes mellitus, understanding the mystery of lipid droplets in β cells and the pathophysiology of diabetes in transplant patients is important, especially for those taking tacrolimus.