Search Results (28)

Background: The aim of this prospective follow-up study was to evaluate changes in body composition parameters and Mediterranean diet (MeDi) adherence among kidney transplant recipients (KTRs) over a three-year period. Additionally, this study sought to investigate the associations between these changes and clinical parameters, including laboratory parameters, new onset of diseases, and death outcome. Methods: A total of 116 KTRs were initially assessed in 2019 and subsequently re-evaluated in 2022. The Mediterranean Diet Serving Score (MDSS) was used to assess dietary adherence to the MeDi at baseline and follow-up assessments. Bioelectrical impedance analysis was used to assess body composition and clinical outcomes were assessed by the data available from medical charts. Results: After three years, MeDi adherence significantly decreased (p = 0.028) from 15 (18.29%) to 5 (6%), with dominantly lower adherence for vegetable, fruit, legume, red meat, olive oil and fish intake. Regarding body composition parameters, the most prominent change was seen in muscle mass, which deteriorated from 41.77% (IQR 6.46) to 39% (IQR 6.14; p = 0.004). However, changes in fat mass level were not significant in the follow-up period. Furthermore, cereal intake, fasting blood glucose (FBG), cholesterol level, level of low-density lipoprotein cholesterol (LDL), triglyceride leve and presence of diabetes mellitus lwere shown to be predictive for the decline of skeletal muscle mass. There were no significant changes in the estimated glomerular filtration rate (eGFR) or albuminuria level during the follow-up period. Associations with the death outcome were found for the MeDi-advised intake of eggs (β = −1.06, HR = 0.35, CI (0.14–0.87), p = 0.023), phase angle (PhA) (β = −2.68, HR = 0.07, CI (0.01–0.43), p = 0.004), cholesterol level (β = 0.95, HR = 2.60, CI (1.40–4.70), p = 0.001) and calcium level (β = −7.21, HR = 0.00, CI (0.00–1.50), p = 0.063). Conclusions: This study highlights a significant decline in MeDi adherence and skeletal muscle mass among KTRs over a three-year follow-up period, with no notable changes in fat mass or kidney function. The predictors of muscle mass loss and associations with mortality underscore the importance of dietary and clinical management in this population. Full article

Diabetes mellitus (DM) in kidney transplant recipients (KTR) is a risk factor for mortality, increases the risk of infections and, in the long term, can lead to graft loss due to diabetic kidney disease. A preventive approach applied to those on the waiting list could decrease the incidence of post-transplant DM (PTDM) by detecting those patients at risk, thus allowing strategies to minimize the probability of developing a New Onset Diabetes After Transplant (NODAT). On the other hand, modifications of immunosuppressive therapy may improve glucose control in patients with KTR. In recent years, two new classes of antidiabetic drugs and non-steroidal mineralocorticoid receptor antagonists have demonstrated cardiovascular and renal benefits in randomized clinical trials where the transplant population has not been represented. Because of the potential benefit expected in this population, the clinical use of glucagon-like peptide-1 receptor agonists (GLP-1RA), sodium-glucose cotransporter 2 inhibitors (SGLT2i) and finerenone is increasing in the kidney transplant setting. This review focuses on comprehensive pharmacological interventions in KTR with glucose metabolism disorders. In-depth knowledge in this area will allow prevention and identification of potential adverse effects or drug interactions in the clinical course of KTR with DM. Full article

New onset diabetes mellitus after organ transplantation (NODAT) is a frequent and serious complication of solid organ transplantation. It significantly impacts graft function, patient survival, and quality of life. NODAT is diagnosed based on the criteria for type 2 diabetes, with the oral glucose tolerance test (OGTT) serving as the gold standard for diagnosis. The development of NODAT is influenced by a range of risk factors, which are classified into modifiable and non-modifiable categories. Post-transplant, regular glycemic monitoring at specific intervals is essential for timely diagnosis and initiation of therapy. Early intervention can help prevent or delay the onset of diabetes-related complications. The treatment strategy for NODAT involves lifestyle modifications and pharmacological interventions. These include medications such as metformin, sulfonylureas, glinides, thiazolidinediones, DPP-4 inhibitors, GLP-1 agonists, SGLT-2 inhibitors, and insulin. Adjusting immunosuppressive therapy—either by reducing dosages or substituting drugs with lower diabetogenic potential—is a common preventative and therapeutic measure. However, this must be performed cautiously to avoid acute graft rejection, which poses a greater risk to the patient compared to NODAT itself. In addition to managing diabetes, addressing comorbidities such as hypertension and dyslipidemia is crucial, as they elevate the risk of cardiovascular events and mortality. Patients with NODAT are also prone to developing common diabetes-related complications, including diabetic nephropathy, neuropathy, retinopathy, and peripheral vascular disease. Therefore, regular follow-ups and appropriate treatment are vital to maintaining quality of life and improving long-term outcomes. Full article

Background/Objectives: ABO-incompatible live-donor kidney transplantation (ABOi-LDKT) has become an established treatment for end-stage renal disease. Non-inferiority in the long-term graft function compared to ABO-compatible live-donor kidney transplantations (ABOc-LDKTs) has been shown. However, the assumed burden due to complications owing to increased immunosuppression inherent to ABOi-LDKTs has not yet been quantified. The aim of this study was to determine if ABOi-LDKT recipients suffer from additional morbidity and whether the resulting burden is justified. Methods: We retrospectively analyzed 45 matched pairs of ABOi-LDKTs and ABOc-LDKTs transplanted over a twenty-year period from January 2000 to March 2020. The number and duration of postoperative readmissions, surgical complication rates according to Clavien–Dindo and its comprehensive complication index (CCI), kidney function, occurrence of new-onset diabetes, and infections as well as tumor incidence were analyzed. Results: Patient and graft survival, as well as graft function, were comparable between the two groups. There were no significant differences in terms of complications, readmission rates, and length of readmission, as well as infection and rejection rates. The median CCIs for ABOi-LDKTs and ABOc-LDKTs at primary discharge and 3, 6, 12, and >12 months were 20.9 vs. 20.9 (p = 0.363), 31.4 vs. 33.7 (p = 0.438), 33.7 vs. 33.7 (p = 0.875), 20.9 vs. 33.1 (p = 0.25), and 27.1 vs. 31.9 (p = 0.163), respectively. Conclusions: ABOi-LDKT seems safe, with comparable outcome, complication, and readmission rates to ABOc-LDKT. In recipients with ABOi living donors, transplantation should not be delayed solely due to concerns over increased perioperative risks. Full article

Human Leukocyte Antigen (HLA) is like a device that monitors the internal environment of the body. T lymphocytes immediately recognize the HLA molecules that are expressed on the surface of the cells of the different individual, attacking it defeats microorganisms that is one of the causes of rejection in organ transplants performed between people with unmatched HLA types. Over 2850 and 3580 different polymorphisms have been reported for HLA-A and HLA-B respectively, around the world. HLA genes are associated with the risk of developing a variety of diseases, including autoimmune diseases, and play an important role in pathological conditions. By using a deep learning method called multi-task learning to simultaneously predict the gene sequences of multiple HLA genes, it is possible to improve accuracy and shorten execution time. Some new systems use a model called convolutional neural network (CNNs) in deep learning, which uses neural networks consisting of many layers and can learn complex correlations between SNP information and HLA gene sequences based on reference data for HLA imputation, which serves as training data. The learned model can output predicted values of HLA gene sequences with high accuracy using SNP information as input. To investigate which part of the input information surrounding the HLA gene is used to make learning predictions, predictions were made using not only a small number of nearby SNP information but also many SNP information distributed over a wider area by visualizing the learning information of the model. While conventional methods are strong at learning using nearly SNP information and not good at learning using SNP information located at distant locations, some new systems are thought that prediction accuracy may have improved because this problem was overcome. HLA genes are involved in the onset of a variety of diseases and are attracting attention. As an important area from the perspective of elucidating pathological conditions and realizing personalized medicine. The applied multi-task learning to two different HLA imputation reference panels—a Japanese panel (n = 1118) and type I diabetes genetics consortium panel (n = 5122). Through 10-fold cross-validation on these panels, the multi-task learning achieved higher imputation accuracy than conventional methods, especially for imputing low-frequency and rare HLA alleles. The increased prediction accuracy of HLA gene sequences is expected to increase the reliability of HLA analysis, including integrated analysis between different racial populations, and is expected to greatly contribute to the identification of HLA gene sequences associated with diseases and further elucidation of pathological conditions. Full article

Kidney transplantation is the most effective treatment for end-stage renal failure but is associated with complications, including post-transplant diabetes mellitus (PTDM). It affects the quality of life and survival of patients and the transplanted organ. It can cause complications, including infections and episodes of acute rejection, further threatening graft survival. The prevalence of PTDM, depending on the source, can range from 4 to 30% in transplant patients. This article aims to discuss issues related to diabetes in kidney transplant patients and the latest treatments. Knowledge of the mechanisms of action of immunosuppressive drugs used after transplantation and their effect on carbohydrate metabolism is key to the rapid and effective detection of PTDM. Patient therapy should not only include standard management such as lifestyle modification, insulin therapy or pharmacotherapy based on well-known oral and injection drugs. New opportunities are offered by hypoglycemic drugs still in clinical trials, including glucokinase activators, such as dorzagliatin, ADV-1002401, LY2608204, TMG-123, imeglimine, amycretin and pramlintide. Although many therapeutic options are currently available, PTDM often creates uncertainty about the most appropriate treatment strategy. Therefore, more research is needed to individualize therapeutic plans and monitor these patients. Full article

New-Onset Diabetes Mellitus after Transplantation (NODAT) emerges as a prevalent complication post-kidney transplantation, with its incidence influenced by variations in NODAT definitions and follow-up periods. The condition’s pathophysiology is marked by impaired insulin sensitivity and β-cell dysfunction. Significant risk factors encompass age, gender, obesity, and genetics, among others, with the use of post-transplant immunosuppressants intensifying the condition. NODAT’s significant impact on patient survival and graft durability underscores the need for its prevention, early detection, and treatment. This review addresses the complexities of managing NODAT, including the challenges posed by various immunosuppressive regimens crucial for transplant success yet harmful to glucose metabolism. It discusses management strategies involving adjustments in immunosuppressive protocols, lifestyle modifications, and pharmacological interventions to minimize diabetes risk while maintaining transplant longevity. The importance of early detection and proactive, personalized intervention strategies to modify NODAT’s trajectory is also emphasized, advocating for a shift towards more anticipatory post-transplant care. Full article

Similar microorganisms, via similar mechanisms, play a role in the development of both pancreatic cancer (PC) and type 2 diabetes (T2D). Since the new onset of T2D is potentially one of the earliest signs of PC, it is highly plausible that a common denominator might be responsible for both, as the growth of the cancer will take a longer time to manifest compared to the insulin resistance. Although a variety of host-dependent factors and susceptibility play a role, and the mechanisms connecting the two diseases remain poorly understood, future well-designed trials should hypothesize whether a microbial intervention (modification and/or transplantation) results in a lower incidence and the better treatment of both diseases since the T2D–PC–gut microbiome interconnection seems scientifically logical. Full article

Obesity and diabetes mellitus epidemics exert a measurable impact on the liver transplant (Ltx) population. This study aimed to investigate the metabolic profile of Ltx recipients and its association with body fat distribution. Adults who underwent de novo elective cadaveric-donor Ltx were eligible. Metabolic syndrome (MS) was diagnosed based on the adapted International Diabetes Federation, the American Heart Association, and the National Heart, Lung, and Blood Institute guidelines. We recruited 100 patients with a mean age of 54 years, of whom 70% were men. Overall, 54% met the criteria for MS, most of which comprised new-onset cases. Excessive fat accumulation in liver donors was found to be associated with an increased metabolic risk in liver recipients. Haemoglobin A1C (OR: 8.962, 95% CI: 2.188–84.545, p = 0.013), ferritin (OR: 1.024, 95% CI: 1.005–1.054, p = 0.038), and de novo hypertriglycaeridemia (OR 27.957, 95% CI: 2.626–752.121, p = 0.014) were found to be independently associated with de novo MS. After a step-wise multivariate analysis, only the anthropometric obesity indices were significantly associated with abdominal fat distribution in Ltx recipients. Metabolic complications were common in liver recipients. Both pre- and post-Ltx factors impacted MS development in liver recipients and determined abdominal fat distribution. Full article

Background: Liver transplantation (LT) is a routine therapeutic approach for patients with acute liver failure, end-stage liver disease and/or early-stage liver cancer. While 5-year survival rates have increased to over 80%, long-term outcomes are critically influenced by extrahepatic sequelae of LT and immunosuppressive therapy, including diabetes mellitus (DM). In this study, we used machine learning (ML) to predict the probability of new-onset DM following LT. Methods: A cohort of 216 LT patients was identified from the Disease Analyzer (DA) database (IQVIA) between 2005 and 2020. Three ML models comprising random forest (RF), logistic regression (LR), and eXtreme Gradient Boosting (XGBoost) were tested as predictors of new-onset DM within 12 months after LT. Results: 18 out of 216 LT patients (8.3%) were diagnosed with DM within 12 months after the index date. The performance of the RF model in predicting the development of DM was the highest (accuracy = 79.5%, AUC 77.5%). It correctly identified 75.0% of the DM patients and 80.0% of the non-DM patients in the testing dataset. In terms of predictive variables, patients’ age, frequency and time of proton pump inhibitor prescription as well as prescriptions of analgesics, immunosuppressants, vitamin D, and two antibiotic drugs (broad spectrum penicillins, fluocinolone) were identified. Conclusions: Pending external validation, our data suggest that ML models can be used to predict the occurrence of new-onset DM following LT. Such tools could help to identify LT patients at risk of unfavorable outcomes and to implement respective clinical strategies of prevention. Full article

There is much evidence confirming the crucial role played by the gut microbiota in modulating the immune system in the onset of autoimmune diseases. In this article, we focus on the relationship between alterations in the microbiome and the onset of diabetes mellitus type 1 and LADA, in light of the latest evidence. We will then look at both how the role of the gut microbiota appears to be increasingly crucial in the pathogenesis of these disorders and how this aspect may be instrumental in the development of new potential therapeutic strategies that modulate the gut microbiota, such as probiotics, prebiotics, and fecal microbiota transplantation. Full article

Background and objectives: New-onset diabetes after transplantation (NODAT) represents a primary cause of morbidity and allograft loss. We assessed prevalence and risk factors for NODAT in a population of Italian kidney transplant (KT) recipients. Methods: Data from 522 KT performed between January 2004 and December 2014 were analyzed. Participants underwent clinical examination; blood and urine laboratory tests were obtained at baseline, one, six, and 12-month of follow-up to detect glucose homeostasis abnormalities and associated metabolic disorders. An oral glucose tolerance test (OGTT) was performed at six months in 303 subjects. Results: Most patients were Caucasian (82.4%) with a mean age of 48 ± 12 years. The prevalence of abnormal glucose metabolism (AGM) and NODAT was 12.6% and 10.7%, respectively. Comparing characteristics of patients with normal glucose metabolism (NGM) to those with NODAT, we found a significant difference in living donation (16.6% vs. 6.1%; p = 0.03) and age at transplant (46 ± 12 vs. 56 ± 9 years; p = 0.0001). Also, we observed that patients developing NODAT had received higher cumulative steroid doses (1-month: 1165 ± 593 mg vs. 904 ± 427 mg; p = 0.002; 6-month:2194 ± 1159 mg vs. 1940 ± 744 mg; p = 0.002). The NODAT group showed inferior allograft function compared to patients with NGM (1-year eGFR: 50.1 ± 16.5 vs. 57 ± 20 mL/min/1.73 m²; p = 0.02). NODAT patients were more likely to exhibit elevated systolic blood pressure and higher total cholesterol and triglyceride levels than controls. Conclusions: The prevalence of NODAT in our cohort was relatively high. Patient age and early post-transplant events such as steroid abuse are associated with NODAT development. Full article

Despite continuous advances in surgical and immunosuppressive protocols, the long-term survival of transplanted kidneys is still far from being satisfactory. Antibody-mediated rejection, recurrent autoimmune diseases, and death with functioning graft are the most frequent causes of late-kidney allograft failure. However, in addition to these complications, a number of other non-immunologic events may impair the function of transplanted kidneys and directly or indirectly lead to their failure. In this narrative review, we will list and discuss the most important nonimmune causes of late death-censored kidney graft failure, including quality of the donated kidney, adherence to prescriptions, drug toxicities, arterial hypertension, dyslipidemia, new onset diabetes mellitus, hyperuricemia, and lifestyle of the renal transplant recipient. For each of these risk factors, we will report the etiopathogenesis and the potential consequences on graft function, keeping in mind that in many cases, two or more risk factors may negatively interact together. Full article

Background: De novo cancers are feared complications after heart or lung transplantation. Recent data suggest that diabetes mellitus (DM) might also be a risk factor for cancer. We hypothesized that transplanted diabetic patients are at greater risk of developing cancer compared to non-diabetic ones. Methods: We reviewed 353 patients post-heart and/or -lung transplantation from our center between October 1999 and June 2021. Patients with follow-up <180 days (n = 87) were excluded from the analysis. The remaining 266 patients were divided into patients who had preoperative DM (n = 88) or developed it during follow-up (n = 40) and patients without DM (n = 138). Results: The diabetic cohort showed higher rates of malignancies in all patients (30.33 vs. 15.97%, p = 0.005) and in the matched population (31.9 vs. 16.1%, p < 0.001). There were also significantly more solid tumors (17.9 vs. 9.4%, p = 0.042; matched: 16.6 vs. 9.1%, p = 0.09) The presence of diabetes was associated with a 13% increased risk of cancer when compared to non-diabetic patients. New-onset post-transplant diabetes doubled the likelihood of cancer development. Conclusions: Pre-transplant diabetes mellitus increases the risk of cancer after heart and/or lung transplantation. However, new-onset diabetes after transplantation is associated with a much greater cancer risk. This information is relevant for screening during follow-up. Full article

Background and objectives: For patients with end-stage renal disease (ESRD), the best replacement therapy is renal transplant (RTx) to ensure life with good quality. Autosomal dominant polycystic kidney disease (ADPKD) is a genetic disorder and a common cause of ESRD. Different from ESRD of other causes, ADPKD patients need careful pre-RTx evaluations like detecting the presence of intracranial aneurisms, cardiac manifestations, and complications of liver and renal cysts. Materials: We retrieved a total of 1327 RTx patients receiving 1382 times RTx (two recipients with three times, 48 recipients with two times) over the last 35 years. Only 41 of these patients were diagnosed with ADPKD. Results: At the first RTx, patients’ ages were 42.9 ± 12.6 (mean ± SD) years. Ages of the ADPKD group (52.5 ± 10.1 years) were older than the non-ADPKD group (42.7 ± 12.7 years, p = 0.001). We found more cell mediated and antibody mediated rejection (29.3% vs. 26.0%, and 22.0% vs. 7.0%; both p < 0.001), new onset diabetes after transplant (NODAT) (21, 51.2% vs. 326, 25.3%; p = 0.005), and worse graft survival (p < 0.001) in the ADPKD group, and with the development of more malignancies (18; 43.9% vs. 360; 28.0%; p = 0.041). The long-term patient survivals were poorer in the ADPKD group (38.9% vs. 70.3%; p = 0.018). ADPKD was found as an independent risk factor for long-term patient survival (HR = 2.64, 95% CI 1.03–6.76, p = 0.04). Conclusions: Patients with ADPKD-related ESRD developed more NODAT, and also more malignancies if not aggressively surveyed before surgery. Due to poor long-term graft and patient survivals, regular careful examinations for NODAT and malignancies, even in the absence of related symptoms and signs, are highly recommended in the follow-ups. Full article