Background and Objectives: Post-transplant diabetes mellitus (PTDM) is a significant risk factor for the survival of graft recipients and occurs in 10–30% of patients after kidney transplant (KT). PTDM is associated with premature cardiovascular morbidity and mortality. Weight gain, obesity, and dyslipidemia are strong predictors of PTDM, and by modifying them with an active lifestyle it is possible to reduce the incidence of PTDM and affect the long-term survival of patients and grafts. The aim of our study was to determine the effect of regular physical activity on the development of PTDM and its risk factors in patients after KT. Materials and Methods: Participants in the study had to achieve at least 150 min of moderate-intensity physical exertion per week. The study group (n = 22) performed aerobic or combined (aerobic + strength) types of sports activities. Monitoring was provided by the sports tracker (Xiaomi Mi Band 4 compatible with the Mi Fit mobile application). The control group consisted of 22 stable patients after KT. Each patient underwent an oral glucose tolerance test (oGTT) at the end of the follow-up. The patients in both groups have the same immunosuppressive protocol. The total duration of the study was 6 months. Results: The patients in the study group had significantly more normal oGTT results at 6 months compared to the control group (p < 0.0001). In the control group, there were significantly more patients diagnosed with PTDM (p = 0.0212) and with pre-diabetic conditions (impaired plasma glucose and impaired glucose tolerance) at 6 months (p = 0.0078). Conclusions: Regular physical activity after KT provides significant prevention against the development of pre-diabetic conditions and PTDM.

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 < 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 <0.5 is independent risk factor for prediabetes and PTDM 1 year post-transplant.

Background: Glycemic variability (GV) may play an important role in metabolic outcomes after kidney transplantation (KT). This study aimed to evaluate the association between early post-transplant GV, assessed by continuous glucose monitoring (CGM), and the subsequent development of post-transplant dysglycemia. Methods: This prospective exploratory pilot study included adult recipients of primary deceased-donor KT at Martin University Hospital, Slovakia. The Dexcom G6 CGM system was applied immediately before KT and continuously measured interstitial glucose for seven days after KT. Demographic, clinical, and biochemical data were collected on day 0, and 7, and at months 3, 12. Results: Twenty patients completed the 12-month follow-up. PTDM/prediabetes developed in 10 (50%) and had higher HbA1c on day 7 (p = 0.038) and lower postprandial insulin (p = 0.042). At 3 and 12 months, HbA1c (p = 0.006), fasting insulin (p = 0.0219), and HOMA-IR (p = 0.006) were significantly elevated in this group. CGM demonstrated higher mean glucose (p = 0.021), SD (p = 0.001), and estimated HbA1c (p = 0.017), with longer time above range (p = 0.042) and shorter time in range (p = 0.037). In exploratory regression analyses, CV ≥ 36% (aOR 7.31, p = 0.049) and TAR (aOR 1.35, p = 0.045) were associated with subsequent PTDM/prediabetes. Conclusions: In this prospective exploratory pilot study, higher early postoperative GV was associated with subsequent post-transplant dysglycemia. These findings suggest that CGM-derived metrics may help identify patients at higher metabolic risk after KT; however, given the small sample size and exploratory design, the results should be interpreted as hypothesis-generating.