The incidence of new onset diabetes after transplantation and related factors: Single center experience

Neutrophil: Lymphocyte and Platelet: Lymphocyte ratios measured before transplantation and their correlation with new-onset diabetes post-transplantation in renal transplant recipients

PURPOSE

Our goal was to evaluate the neutrophil:lymphocyte (NLR) and platelet:lymphocyte (PLR) ratios measured before transplantation and their correlation with new-onset diabetes after transplantation (NODAT) in renal transplant recipients.

PATIENTS AND METHODS

We conducted our study in 324 adult patients consecutively admitted to Military Hospital 103, Ha Noi, Viet Nam, who received kidney allografts from living donors. These patients were followed-up during the first 2 years post-transplantation for NODAT. We examined the association between NLR and PLR measured prior to transplantation in patients with NODAT: NLR and PLR were calculated based on the results of the complete blood count. The criteria for diagnosis of a fully symptomatic NODAT case were based on the guidelines established by the American Diabetes Association and included fasting venous blood glucose and glycosylated hemoglobin A1c (HbA1c) levels, with or without an oral glucose tolerance test.

RESULTS

The overall rate of NODAT during the two years after kidney transplantation was 13.6%. We found mean values of age and body mass index (BMI), and median values of NLR, PLR, high sensitivity C-reactive protein (hs-CRP) levels, and the arteriosclerosis ratio in the NODAT group to be significantly higher than those of the non-NODAT group (all p < 0.05). Furthermore, an adjusted multivariate regression analysis showed that age (area under the curve [AUC] = 0.727, p < 0.001), BMI (AUC = 0.846, p < 0.001), serum hs-CRP levels (AUC = 0.884, p < 0.001), NLR (AUC = 0.888; p < 0.001), and PLR (AUC = 0.818; p < 0.001) had predictive value for NODAT.

CONCLUSION

NLR and PLR measured before transplantation were good predictors for NODAT in the first 2 years post-renal transplantation.

Post-transplant diabetes mellitus: Findings in nutritional status and body composition

INTRODUCTION

Weight gain and changes in body composition are associated with the onset of diabetes after kidney transplantation, and detailing these changes can help prevent this situation. The study aimed to assess the prevalence of diabetes mellitus after kidney transplantation and changes in the nutritional status and body composition in patients with diabetes one year from surgery.

MATERIALS AND METHODS

This survey was a single-center, prospective cohort study. Twenty-nine patients over 18 years old who underwent isolated kidney transplantation, without diabetes, were included and followed up for one year. At hospital discharge after transplantation and one year later, anthropometric (weight, height and abdominal circumference), body composition (electrical bioimpedance), routine biochemical and dietary intake assessments were performed.

RESULTS

Most of the patients were male (75%), and the mean age was 48.0±11.8 years old. In the first-year post-surgery 27.6% of patients had DM and the diagnosis was made, on average, 4 months after transplantation. The group with diabetes had, from the beginning to the end of the study, greater weight and body fat, especially abdominal fat. The non-diabetic group, after one year, showed an increase in phase angle, body weight and body masses, more pronounced of fat-free mass, when compared with fat mass gain.

CONCLUSIONS

Both groups showed weight gain, but in the non-diabetic group these changes can be interpreted as an improvement in the nutritional profile. Metabolic abnormalities associated with immunosuppression and eating habits, combination that maintains increased the risk for diabetes for long time, keeping this group with priority in nutritional care.

The results of SGLT-2 inhibitors use in kidney transplantation: 1-year experiences from two centers

PURPOSE

Sodium-glucose co-transporter-2 inhibitor (SGLT-2i) administration is associated with some concerns in regard to the increased risk of genital and urinary tract infections (UTI) in kidney transplant recipients (KTR). In this study, we present the results of SGLT-2i use in KTR, including the early post-transplant period.

METHODS

Participants were divided into two groups: SGLT-2i-free diabetic KTR (Group 1, n = 21) and diabetic KTR using SGLT-2i (Group 2, n = 36). Group 2 was further divided into two subgroups according to the posttransplant prescription day of SGLT-2i; < 3 months (Group 2a) and ≥ 3 months (Group 2b). Groups were compared for development of genital and urinary tract infections, glycated hemoglobin a1c (HgbA1c), estimated glomerular filtration rate (eGFR), proteinuria, weight change, and acute rejection rate during 12-month follow-up.

RESULTS

Urinary tract infections prevalence was 21.1% and UTI-related hospitalization rate was 10.5% in our cohort. Prevalence of UTI and UTI-related hospitalization, eGFR, HgbA1c levels, and weight gain were similar between the SGLT-2i group and SGLT-2i-free group, at the 12-month follow-up. UTI prevalence was similar between groups 2a and 2b (p = 0.871). No case of genital infection was recorded. Significant proteinuria reduction was observed in Group 2 (p = 0.008). Acute rejection rate was higher in the SGLT-2i-free group (p = 0.040) and had an impact on 12-month follow-up eGFR (p = 0.003).

CONCLUSION

SGLT-2i in KTR is not associated with an increased risk of genital infection and UTI in diabetic KTR, even in the early posttransplant period. The use of SGLT-2i reduces proteinuria in KTR and has no adverse effects on allograft function at the 12-month follow-up.

Postoperative fasting plasma glucose and family history diabetes mellitus can predict post-transplantation diabetes mellitus in kidney transplant recipients

PURPOSE

To explore whether glycated albumin (GA) or fasting plasma glucose (FPG), both routinely monitored during patients' hospital stay, can be used to predict post-transplantation diabetes mellitus (PTDM).

METHODS

All kidney transplantation recipients (KTRs) from January 2017 to December 2018 were followed-up for 1 year. PTDM was diagnosed from day 45 post-operation to 1 year. When the completeness was above 80%, FPG or GA data on the day was selected, analyzed, and presented as range parameters and standard deviation (SD) and compared between PTDM and non-PTDM groups in fluctuation and stable periods. The predictive cut-off values were determined via receiver operating characteristic (ROC) analysis. The PTDM combined predictive mode, formed by the independent risk factors derived from logistic regression analyses, was compared with each independent risk factor with the independent ROC curve test.

RESULTS

Among 536 KTRs, 38 patients developed PTDM up to 1 year post-operatively. The family history diabetes mellitus (OR, 3.21; P = 0.035), the FPG SD in fluctuation period >2.09 mmol/L (OR, 3.06; P = 0.002), and the FPG maximum in stable period >5.08 mmol/L (OR, 6.85; P < 0.001) were the PTDM independent risk factors. The discrimination of the combined mode (area under the curve = 0.81, sensitivity = 73.68%, and specificity = 76.31%) was higher than each prediction (P < 0.05).

CONCLUSIONS

The FPG standard deviation during the fluctuation period, FPG maximum during the stable period, and family history diabetes mellitus predicted PTDM with good discrimination and potential routine clinical use.

Progress of new-onset diabetes after liver and kidney transplantation

Organ transplantation is currently the most effective treatment for end-stage organ failure. Post transplantation diabetes mellitus (PTDM) is a severe complication after organ transplantation that seriously affects the short-term and long-term survival of recipients. However, PTDM is often overlooked or poorly managed in its early stage. This article provides an overview of the incidence, and pathogenesis of and risk factors for PTDM, aiming to gain a deeper understanding of PTDM and improve the quality of life of recipients.

Analysis of risk factors and establishment of a risk prediction model for post-transplant diabetes mellitus after kidney transplantation

Introduction

Post-transplant diabetes mellitus (PTDM) is a known side effect in transplant recipients administered immunosuppressant drugs, such as tacrolimus. This study aimed to investigate the risk factors related to PTDM, and establish a risk prediction model for PTDM. In addition, we explored the effect of PTDM on the graft survival rate of kidney transplantation recipients.

Methods

Patients with pre-diabetes mellitus before kidney transplant were excluded, and 495 kidney transplant recipients were included in our study, who were assigned to the non-PTDM and PTDM groups. The cumulative incidence was calculated at 3 months, 6 months, 1 year, 2 years, and 3 years post-transplantation. Laboratory tests were performed and the tacrolimus concentration, clinical prognosis, and adverse reactions were analyzed. Furthermore, binary logistic regression analysis was used to identify the independent risk factors of PTDM.

Results

Age ≥ 45 years (adjusted odds ratio [aOR] 2.25, 95% confidence interval [CI] 1.14–3.92; P = 0.015), body mass index (BMI) > 25 kg/m² (aOR 3.12, 95% CI 2.29–5.43, P < 0.001), tacrolimus concentration > 10 ng/mL during the first 3 months post-transplantation (aOR 2.46, 95%CI 1.41–7.38; P < 0.001), transient hyperglycemia (aOR 4.53, 95% CI 1.86–8.03; P < 0.001), delayed graft function (DGF) (aOR 1.31, 95% CI 1.05–2.39; P = 0.019) and acute rejection (aOR 2.16, 95% CI 1.79–4.69; P = 0.005) were identified as independent risk factors of PTDM. The PTDM risk prediction model was developed by including the above six risk factors, and the area under the receiver operating characteristic curve was 0.916 (95% CI 0.862–0.954, P < 0.001). Furthermore, the cumulative graft survival rate was significantly higher in the non- PTDM group than in the PTDM group.

Conclusions

Risk factors related to PTDM were age ≥ 45 years, BMI > 25 kg/m², tacrolimus concentration > 10 ng/mL during the first 3 months post-transplantation, transient hyperglycemia, DGF and acute rejection.

Distúrbio do eixo hipotálamo-hipófise-gonadal e sua associação com resistência à insulina em receptores de transplante renal

Resumo Objetivo: Avaliar as alterações do eixo hipotálamo-hipófise-gonadal (HHG) em 1 e 12 meses após transplante renal (TR) e sua associação com a resistência à insulina. Métodos: Foi realizado um estudo clínico retrospectivo em um centro de cuidados terciários em receptores de transplante renal (RTR) com idade entre 18-50 anos com doença renal primária e função do enxerto renal estável. LH, FSH, E2/T e HOMA-IR foram avaliados em 1 e 12 meses após o TR. Resultados: foram incluídos 25 RTR; 53% eram homens e a média de idade foi de 30,6±7,7 anos. O IMC foi de 22,3 (20,4-24,6) kg/m2 e 36% apresentaram hipogonadismo em 1 mês vs 8% aos 12 meses (p=0,001). A remissão do hipogonadismo foi observada em todos os homens, enquanto nas mulheres, o hipogonadismo hipogonadotrófico persistiu em dois RTR aos 12 meses. Ficou evidente uma correlação positiva entre gonadotrofinas e idade em 1 e 12 meses. Cinquenta e seis por cento dos pacientes apresentaram resistência à insulina (RI) em 1 mês e 36% aos 12 meses (p=0,256). O HOMA-IR mostrou uma correlação negativa com E2 (r=-0,60; p=0,050) e T (r=-0,709; p=0,049) em 1 mês, sem correlação em 12 meses. O HOMA-IR aos 12 meses após TR correlacionou-se positivamente com o IMC (r=0,52; p=0,011) e a dose de tacrolimus (r=0,53; p=0,016). Conclusão: O TR bem-sucedido restaura o eixo HHG no primeiro ano. O hipogonadismo apresentou uma correlação negativa com a RI no período inicial após o TR, mas essa correlação não foi significativa aos 12 meses.

Hypothalamic-pituitary-gonadal axis disturbance and its association with insulin resistance in kidney transplant recipients

OBJECTIVE

To evaluate hypothalamic-pi- tuitary-gonadal (HPG) axis alterations at 1 and 12 months after kidney transplan- tation (KT) and their association with in- sulin resistance.

METHODS

A retrospective clinical study was conducted in a tertiary care center in kidney transplantation recipients (KTRs) aged 18- 50 years with primary kidney disease and stable renal graft function. LH, FSH, E2/T, and HOMA-IR were assessed at 1 and 12 months after KT.

RESULTS

Twenty-five KTRs were included; 53% were men, and the mean age was 30.6±7.7 years. BMI was 22.3 (20.4-24.6) kg/m2, and 36% had hypogonadism at 1 month vs 8% at 12 months (p=0.001). Re- mission of hypogonadism was observed in all men, while in women, hypogonadotropic hypogonadism persisted in two KTRs at 12 months. A positive correlation between go- nadotrophins and age at 1 and 12 months was evident. Fifty-six percent of patients had insulin resistance (IR) at 1 month and 36% at 12 months (p=0.256). HOMA-IR showed a negative correlation with E2 (r=- 0.60; p=0.050) and T (r=-0.709; p=0.049) at 1 month, with no correlation at 12 months. HOMA-IR at 12 months after KT correlated positively with BMI (r=0.52; p=0.011) and tacrolimus dose (r=0.53; p=0.016).

CONCLUSION

Successful KT restores the HPG axis in the first year. Hypogonadism had a negative correlation with IR in the early pe- riod after KT, but it was not significant at 12 months.

Predictors of New-onset Diabetes After Kidney Transplantation During 2019-nCoV Pandemic: A Unison of Frequentist Inference and Narrow AI

BACKGROUND: New-onset diabetes after kidney transplant (NODAT) is a severe metabolic complication that frequently occurs in recipients following transplantation. AIM: The study aims to verify NODAT, compare cases and non-cases of this entity, and explore potential predictors in recipients within 1 year following kidney transplantation. METHODS: The research is a retrospective study of 90 renal transplant recipients (n = 90). Demographic factors and clinical aspects were analyzed using non-Bayesian statistics and machine learning (ML). The clinical aspects included the glycated hemoglobin (HbA1c) level, associated viral infections (hepatitis B virus [HBV], hepatitis C virus [HCV], and cytomegalovirus [CMV]), prior kidney transplant, hemodialysis status, body mass index (BMI) at transplant time, and 3 months later, primary causes of renal failure, and post-transplant therapeutics. All individuals were on cyclosporine and prednisolone treatment. RESULTS: The mean age was 39 (±1.5) years; recipients included 27 females (30%) and 63 males (70%). Donor type was live related (16, 17.8%) or live unrelated (74, 82.2%); 27 recipients (30%) had O+ blood group, while 70% belonged to other groups. Thirteen recipients (14.4%) were not on dialysis. Only 32 individuals (35.6%) developed NODAT. Concerning virology, confirmed by real-time polymerase chain reaction before transplantation, 19 recipients (21.1%) were CMV positive, 9 (10%) were HCV positive, and 2 (2.2%) had HBV. CONCLUSIONS: In reconciliation with frequentist statistics, the dual ML model validated several predictors that either negatively (protective) or positively (harmful) influenced HbA1c level, the majority of which were significant at 95% confidence interval. Individuals who are HCV and CMV positive are predicted to develop NODAT. Further, older individuals, with blood group O+ve, prior history of hemodialysis, a relatively high BMI before the transplant, and receiving higher doses of prednisolone following the transplant are more likely to develop NODAT. The current study represents the first research from Iraq to explore NODAT predictors among kidney transplant recipients using frequentist statistics and artificial intelligence models.

Analysis of the frequency of single nucleotide polymorphisms in cytokine genes in patients with New Onset Diabetes After Transplant

New Onset Diabetes After Transplantation (NODAT) is a serious metabolic complication. While β-cell dysfunction is considered the main contributing factor in the development of NODAT, the precise pathogenesis is not well understood. Cytokines are thought to be involved in the inflammation of islet β-cells in diabetes; however, few studies have investigated this hypothesis in NODAT. A total of 309 kidney transplant recipients (KTRs) were included in this study. An association between kidney transplants, and the development of diabetes after transplant (NODAT) was investigated. Comparison was made between KTRs who develop diabetes (NODAT cases) or did not develop diabetes (control), using key cytokines, IL-6 G (− 174)C, macrophage mediator; IL-4 C (− 490)T, T helper (Th)-2 cytokine profile initiator; Th-1 cytokine profile initiator interferon-γ T (+ 874) A gene and TGF β1 C (+ 869) T gene polymorphisms were investigated. The genes were amplified using well-established polymerase chain reaction (PCR) techniques in our laboratory. Compared to the AA and AT genotypes of interferon gamma (IFNG), there was a strong association between the TT genotype of IFNG and NODAT kidney transplant recipients (KTRs) versus non-NODAT KTRs (p = 0.005). The AA genotype of IFNG was found to be predominant in the control group (p = 0.004). Also, significant variations of IL6 G (− 174) C, IL-4 C (− 590) T, interferon-γ T (+ 874) A gene and transforming growth factor β1 C (+ 869) T may contribute to NODAT. Our data is consistent with theTh-1/T-reg pathway of immunity. Further larger pan Arab studies are required to confirm our findings.

Risk factors for new-onset diabetes mellitus after kidney transplantation: A systematic review and meta-analysis

AIMS/INTRODUCTION

To systematically review the risk factors for new-onset diabetes mellitus after kidney transplantation, and to provide a theoretical basis for the prevention and management of new-onset diabetes mellitus after kidney transplantation.

MATERIALS AND METHODS

We searched PubMed, Web of Science, Embase, the Cochrane Library databases and other databases for case-control studies related to risk factors for new-onset diabetes mellitus after kidney transplantation published between January 2005 and July 2019. A meta-analysis of data on risk factors for new-onset diabetes mellitus after kidney transplantation from the included studies was carried out. A narrative review of risk factors for new-onset diabetes mellitus after kidney transplantation was also carried out.

RESULTS

A total of 24 case-control studies were included in the meta-analysis, with a total of 7,140 patients. There were 1,598 patients with new-onset diabetes mellitus after kidney transplantation, and 5,542 patients without new-onset diabetes mellitus after kidney transplantation. The meta-analysis results showed that age, polycystic kidney disease, family history of diabetes, body mass index, acute rejection, tacrolimus use, hepatitis B virus infection, hepatitis C virus infection and hypertension were associated with new-onset diabetes mellitus after kidney transplantation, whereas sex, sirolimus use, cyclosporin A use, steroid use and cytomegalovirus infection were not associated with new-onset diabetes mellitus after kidney transplantation.

CONCLUSIONS

Older age, body mass index, family history of diabetes, tacrolimus use, history of hypertension, polycystic kidney disease, acute rejection, hepatitis B virus infection and hepatitis C virus infection are risk factors for new-onset diabetes mellitus after kidney transplantation. Therefore, the clinical implications of these factors warrant attention.

Incidence and relative risk factors in posttransplant diabetes mellitus patients: a retrospective cohort study

Background

Posttransplant diabetes mellitus (PTDM) has a long-term impact on kidney transplantation outcomes, such as graft and patient survival. The incidence and risk factors of PTDM are well studied, but long-term follow-up results remain unavailable. We examined the long-term incidence and relative risk factors of PTDM.

Methods

A hospital information system database for kidney transplant recipients (KTRs) for a transplantation center between 1983 and 2018 was used to perform this retrospective cohort study. KTRs with DM diagnosis and continuous use of hypoglycemic agents for more than 3 months were defined as having PTDM. Demographics and comorbidities before transplantation were also collected. Kaplan-Meier analyses were used to determine the cumulative incidence and relative risk factors.

Results

A total of 296 PTDM cases were confirmed (28.46%) in this study. An increased cumulative incidence associated with age was noted, which was significantly increased in those aged ≥40 years. Male sex, hypertension, hyperlipidemia before transplantation, cytomegalovirus (CMV) infection, and tacrolimus-based regimens were also risk factors. No significant correlation was found between the development of PTDM and the increase of human leukocyte antigen mismatches, the primary causes of end-stage renal disease, and acute rejection.

Conclusions

PTDM incidence was high in this cohort study. Characteristics such as age ≥40 years, tacrolimus use, comorbidity of hypertension and hyperlipidemia before transplantation, and CMV infection were associated with a high risk of PTDM. Monitoring and adjusting preventable risk factors such as CMV infection might be useful to prevent PTDM.

Risk Factors in and Long-Term Survival of Patients with Post-Transplantation Diabetes Mellitus: A Retrospective Cohort Study

Post-transplant diabetes mellitus (PTDM) is associated with infection, cardiovascular morbidity, and mortality. A retrospective cohort study involving patients who underwent renal transplantation in a transplantation center in Taiwan from January 2000 to December 2018 was conducted to investigate the incidence and risk factors of PTDM and long-term patient and graft survival rates. High age (45-65 vs. <45 years, adjusted odds ratio (aOR) = 2.90, 95% confidence interval (CI) = 1.64-5.13, p < 0.001), high body mass index (>27 vs. <24 kg/m², aOR = 5.35, 95% CI = 2.75-10.42, p < 0.001), and deceased organ donor (cadaveric vs. living, aOR = 2.01, 95% CI = 1.03-3.93, p = 0.04) were the three most important risk factors for the development of PTDM. The cumulative survival rate of patients and allografts was higher in patients without PTDM than in those with PTDM (p = 0.007 and 0.041, respectively). Concurrent use of calcineurin inhibitors and mammalian target of rapamycin inhibitors (mTORis) decreased the risk of PTDM (tacrolimus vs. tacrolimus with mTORi, aOR = 0.28, 95% CI = 0.14-0.55, p < 0.001). Investigating PTDM risk factors before and modifying immunosuppressant regimens after transplantation may effectively prevent PTDM development.

Determinants of Poor Glycemic Control in Patients with Kidney Transplants: A Single-Center Retrospective Cohort Study in Canada

Background:

Kidney transplant immunosuppressive medications are known to impair glucose metabolism, causing worsened glycemic control in patients with pre-transplant diabetes mellitus (PrTDM) and new onset of diabetes after transplant (NODAT).

Objectives:

To determine the incidence, risk factors, and outcomes of both PrTDM and NODAT patients.

Design:

This is a single-center retrospective observational cohort study.

Setting:

The Ottawa Hospital, Ontario, Canada.

Participant:

A total of 132 adult (>18 years) kidney transplant patients from 2013 to 2015 were retrospectively followed 3 years post-transplant.

Measurements:

Patient characteristics, transplant information, pre- and post-transplant HbA1C and random glucose, follow-up appointments, complications, and readmissions.

Methods:

We looked at the prevalence of poor glycemic control (HbA1c >8.5%) in the PrTDM group before and after transplant and compared the prevalence, follow-up appointments, and rate of complications and readmission rates in both the PrTDM and NODAT groups. We determined the risk factors of developing poor glycemic control in PrTDM patients and NODAT. Student t-test was used to compare means, chi-squared test was used to compare percentages, and univariate analysis to determine risk factors was performed by logistical regression.

Results:

A total of 42 patients (31.8%) had PrTDM and 12 patients (13.3%) developed NODAT. Poor glycemic control (HbA1c >8.5%) was more prevalent in the PrTDM (76.4%) patients compared to those with NODAT (16.7%; P < .01). PrTDM patients were more likely to receive follow-up with an endocrinologist (P < .01) and diabetes nurse (P < .01) compared to those with NODAT. There were no differences in the complication and readmission rates for PrTDM and NODAT patients. Receiving a transplant from a deceased donor was associated with having poor glycemic control, odds ratio (OR) = 3.34, confidence interval (CI = 1.08, 10.4), P = .04. Both patient age, OR = 1.07, CI (1.02, 1.3), P < .01, and peritoneal dialysis prior to transplant, OR = 4.57, CI (1.28, 16.3), P = .02, were associated with NODAT.

Limitations:

Our study was limited by our small sample size. We also could not account for any diabetes screening performed outside of our center or follow-up appointments with family physicians or community endocrinologists.

Conclusion:

Poor glycemic control is common in the kidney transplant population. Glycemic targets for patients with PrTDM are not being met in our center and our study highlights the gap in the literature focusing on the prevalence and outcomes of poor glycemic control in these patients. Closer follow-up and attention may be needed for those who are at risk for worse glycemic control, which include older patients, those who received a deceased donor kidney, and/or prior peritoneal dialysis.

Prediabetes and older age increase the risk of post-transplantation diabetes mellitus: Qatar experience

Post-transplantation diabetes mellitus (PTDM) is a major complication in kidney transplant recipients leading to reduced allograft and patient survival. Given the high prevalence of diabetes in Qatar, which is twice the global average, we were interested in determining the incidence of PTDM, identifying risk factors, and comparing clinical outcomes in kidney transplant recipients with and without diabetes. We retrospectively followed up 191 adult kidney allograft recipients transplanted between January 1, 2012, and December 31, 2016, for a median of 41 months. A total of 76 patients (40%) had pre-existing diabetes. A total of 39 patients developed PTDM during follow-up; they represent 34% of patients who did not have diabetes prior to transplantation. Two thirds of PTDM occurred within 3-6 months post-transplantation. Prediabetes before transplant [OR = 6.07 (1.24-29.74), P = .026] older recipient's age at the time of transplantation [OR = 1.10 (1.00-1.20), P = .039] and average fasting blood sugar during 3-6 months post-transplant [OR = 1.06 (1.01-1.11), P = .010] were independently associated with PTDM. Patient and kidney allograft survival rates exceeded 97% in all groups. The incidence of PTDM in kidney transplant recipients living in Qatar is high. Older age and prediabetes are independent risk factors for developing PTDM.

Risk Factors Related to New-Onset Diabetes after Renal Transplantation in Patients of a High Complexity University Hospital in Colombia, 20 Years of Experience

INTRODUCTION

New-onset diabetes after transplantation (NODAT) is associated with immunosuppression. Its complications can negatively influence patients' quality of life, which is why it is important to study the associated risk factors and expand the possible therapies in this particular group of patients. Materials and methods. Case-control study nested in a retrospective cohort. It included patients who received kidney transplantation at the high complexity University Hospital Fundación Valle del Lili in Cali, Colombia, between 1995 and 2014. Two controls were assigned for each case, depending on the type of donor and the date of the surgery. Information was collected from clinical records and the institutional TRENAL registry. We carried out a descriptive analysis of the selected variables and identified the risk factors with conditional logistic regression.

RESULTS

122 cases were identified to which 224 controls were assigned. The median age was 44 years (IQR: 34-55), and 54% were men. Having >50 years of age at the time of transplantation (OR: 3.18, 95% CI: 1.6-6.3, p = 0.001), body mass index >30 kg/m² (OR: 3.6, 95% CI: 1.3-9.7, p = 0.010) and being afro-descendant (OR: 2.74, 95% CI: 1.1-6.5, p = 0.023) were identified as risk factors for the development of NODAT. Pretransplant fasting plasma glucose >100 mg/dl (OR: 2.9, 95% CI: 1.4-6.4, p = 0.005) and serum triglycerides >200 mg/dl (OR: 2.5, 95% CI: 1.4-4.4, p = 0.002) were also reported as independent risk factors.

CONCLUSION

We ratify some risk factors for the development of this important disease, which include certain modifiable characteristics. Interventions aimed at changes in lifestyle could be established in a timely manner before transplant surgery.

Insulin Resistance in Nonobese Renal Allograft Recipients on Maintenance Doses of Cyclosporine or Tacrolimus

PURPOSE

In comparison to cyclosporine (CsA), tacrolimus (Tac) seems to be more diabetogenic in renal transplant recipients, and post-transplant diabetes mellitus is more common in patients using Tac, especially during the first year after transplantation. However, at maintenance doses, there are no comparative data of insulin resistance (IR) in patients using Tac or CsA. The purpose of this study was to investigate the IR indexes in patients on maintenance doses of CsA or Tac.

METHODS

Forty-five nondiabetic and nonobese renal transplant recipients participated in the study (M:F, 30:15; age, 36 ± 9 years); 27 patients were on CsA, and 18 were on Tac. All had stable graft function, were transplanted at least 6 months previously, and were receiving maintenance doses of steroids (5.0 mg/d), azathioprine or mycophenolate mofetil, and calcineurin inhibitors (CsA [2.14 ± 0.46 mg/kg/d] or Tac [0.06 ± 0.03 mg/kg/d]). IR was evaluated by the homeostasis model assessment (HOMA) index and composite body insulin sensitivity index.

RESULTS

We did not determine any significant difference in the HOMA and composite body insulin sensitivity index levels among patients using CsA or Tac (1.5 ± 1.3 vs 1.5 ± 1.1, P > .05, and 9.9 ± 5.8 vs 14.6 ± 11.7, P > .05, respectively). There was a significant correlation between creatinine and HOMA values.

CONCLUSION

There was no difference in IR indexes in renal transplant recipients receiving maintenance doses of either CsA or Tac.

Regulatory T Cells in the Context of New-Onset Diabetes After Renal Transplant: A Single-Center Experience

BACKGROUND

New-onset diabetes mellitus after transplant (NODAT) is a well-known complication of renal transplant that severely affects graft and patient survival. It is necessary to explore further risk factors and reveal the underlying pathomechanism.

METHODS

Renal transplants performed between January 2010 and June 2018 were involved. Exclusion criteria were the recipient age younger than 18 years, follow-up period less than 6 months, and patients with diabetes at the time of transplant. Only primary kidney transplants were involved in our study, which totaled 223 cases. Besides donor and recipient demographic data, the type of immunosuppression, the average fasting glucose level, and T-subset profiles were compared.

RESULTS

Of 223 cases there were 33 patients (14.8%) with NODAT (17 female; mean age, 54.2 [SD, 10.3] years; mean body mass index [calculated as weight in kilograms divided by height in meters squared], 27.8 [SD, 5.1]; mean follow-up, 43.3 [SD, 25.5] months). The control group consisted of 190 patients. The average fasting blood glucose level was higher in the NODAT group vs the control group (P < .001). The average fasting blood glucose level above diabetic threshold (≥7 mmol/L) was in association with a 6-fold higher risk of NODAT (odds ratio, 5.86; 95% CI, 2.46-13.97; P < .001). Absolute value of CD4⁺CD25^brightCD127^dim regulatory T cells was lower in the NODAT group at the first month after transplant (P = .048) Immunosuppressive protocol and survival data did not differ.

CONCLUSIONS

Intensive management of the carbohydrate excursions during the early post-transplant period may decrease the incidence of NODAT. Further investigations will be required to decide whether the reduced CD4⁺CD25^brightCD127dim/regulatory T-cell count contributes the development of NODAT.

Prevalence and Predictors of "New-onset Diabetes after Transplantation" (NODAT) in Renal Transplant Recipients: An Observational Study

OBJECTIVE

New-onset diabetes after transplantation (NODAT) develops frequently after renal transplant. The study aims at the prevalence of NODAT, predictors for developing it and therapeutic glycemic responses in NODAT.

MATERIALS AND METHODS

Consecutive renal transplant recipients excluding Diabetic Kidney Disease (DKD) or pretransplant diabetes were evaluated. Forty-three out of 250 persons were found to have NODAT. Ninety age-matched transplant recipients from the rest were recruited as control. Fasting blood sugar (FBS), HbA1c, lipid profile, and trough tacrolimus level (T₀) were examined in all. HOMA IR C-peptide and HOMA-beta C-peptide were calculated.

RESULTS

Prevalence of NODAT in renal transplant recipients was 17.2% (43/250). Twenty-four (55.8%) developed early NODAT (<1 year) and 19 (44.2%) developed late NODAT (>1 year). Significantly higher pretransplant body mass index (BMI) (kg/m²) (P < 0.001), waist circumference (WC) (cm) (P < 0.001), pretransplant cholesterol (mg%) (P = 0.04), triglyceride (mg%) (P < 0.001), and FBS (mg%) (P < 0.001) were found in NODAT compared with non-NODAT. Trough tacrolimus (ng/mL) was found to be higher in NODAT (10.2 vs. 5.37, P < 0.001). Though HOMA IR was not found to be different between groups, HOMA-beta C-peptide was low in NODAT compared with non-NODAT (P = 0.03). Predictors of NODAT were WC [odds ratio (OR) = 01.15] and trough tacrolimus level (OR = 1.316). Best cut-off of WC for predicting NODAT was 87.5 cm for male and 83.5 cm for female. Best cut-off of T₀ was 8.5 ng/mL. In NODAT, 9.3% were treated by lifestyle modification, 67.4% by oral hypoglycemic agents, 11.6% by insulin, and 11.6% by combined insulin and oral antidiabetic agents with HbA1c <7%.

CONCLUSION

NODAT in renal transplant recipients is more common in those with higher pretransplant BMI, WC, pretransplant total cholesterol, triglyceride, and FBS. Beta-cell secretory defect is more relevant as etiological factor rather than insulin resistance. Higher WC and trough tacrolimus level above 8.5 ng/mL may be important factors for predicting NODAT.

Immunogenetics of new onset diabetes after transplantation in Kuwait

Introduction and aim: New onset diabetes after transplantation (NODAT) is a serious metabolic complication following kidney transplantation. Although beta-cell dysfunction is considered the main contributing factor in the development of this complication, its exact etiology is yet to be identified. We aimed to investigate NODAT among kidney transplant cohort in Kuwait with special stress on correlation between its risk factors and interferon gamma genotyping. Materials and methods: We surveyed 309 kidney transplant recipients from Hamed Al Essa Transplantation Centre, Kuwait. The participants were categorized into cohorts according to the development of NODAT diagnosed based on the American Diabetes Association guidelines. Statistical analyses were performed using SPSS software. We genotyped interferon gamma as the leading immunosignature for T lymphocyte. Results: No relationship between ethnicity and the development of NODAT was identified. However, there was a significant difference in age between cohorts. Younger patients demonstrated a lower rate of NODAT while, NODAT reached its maximum in 40-60-year age group. IFNG TT genotype was significantly associated with NODAT (p=0.005), while IFNG AA was considerably higher in the non-NODAT group. Conclusion: Beside the conventional contributing factors of NODAT, our results might represent a suitable platform for a larger cytokine and chemokine spectrum genotyping.

A SEVERE CASE OF HYPERGLYCEMIA IN A KIDNEY TRANSPLANT RECIPIENT UNDERGOING INTERFERON-FREE THERAPY FOR CHRONIC HEPATITIS C

CONTEXT

Hepatitis C and diabetes represent important health problems globally. The new-onset diabetes after transplantation is a particular entity that appears due to the use of immunosuppression among transplanted patients.

OBJECTIVE

We aim to describe the clinical and biological aspects of severe hyperglycemia in a kidney transplant recipient undergoing Interferon-free therapy for chronic hepatitis C, discussing the interference of different factors with the glucose metabolism.

DESIGN

The occurrence of diabetes in a patient with history of renal transplantation and Interferon-free treated hepatitis C was studied from both clinical and paraclinical points of view.

SUBJECTS AND METHODS

When presenting to the hospital, extensive blood tests were performed on the patient, revealing significant hyperglycemia and an elevated level of blood tacrolimus. Creatinine clearance was calculated. ECG presented T-wave alterations. Intensive insulin protocol was applied, the case being managed in a multidisciplinary approach.

RESULTS

Blood glucose and tacrolimus were slowly normalized, under therapy. The antiviral treatment was continued, with the achievement of sustained virologic response.

CONCLUSIONS

Diabetes mellitus can have many causes, hepatitis C and transplantation both having an impact on glucose metabolism. The association of the three entities should be carefully managed, due to its enhancing effect on morbidity and mortality.

Incidence and Risk Factors of Posttransplantation Diabetes Mellitus in Living Donor Kidney Transplantation: A Single-Center Retrospective Study in China

BACKGROUND

Posttransplantation diabetes mellitus (PTDM) is a frequent metabolic complication following solid organ transplantation and was proven to be associated with adverse outcome. This study aimed to identify the incidence and risk factors of PTDM under the background of relative-living renal transplantation in China.

METHODS

We conducted a retrospective cohort study that included 358 recipients who underwent relative-living donor kidney transplantation in the Organ Transplant Institute of 309th Hospital of People's Liberation Army between January 1, 2010, and December 31, 2014. PTDM was defined based on American Diabetes Association criteria. Demographics and laboratory results were compared between patients with PTDM and non-PTDM; multivariate analysis was performed using a logistic regression model.

RESULTS

One hundred ten out of a total of 358 recipients were diagnosed with PTDM (30.72%) within 3 years after transplantations. Seven risk factors for PTDM were identified in multivariate analysis: body mass index ≥25 (odds ratio [OR] 1.905, 95% confidence interval [CI]: 1.114-3.258), family history of diabetes (OR 1.898, CI: 1.051-3.258), hypomagnesemia pretransplantation (OR 1.871, CI: 1.133-3.092), acute rejection episodes in 3 months posttransplantation (OR 2.312, CI: 1.015-5.268), tacrolimus use (OR 1.952, CI: 1.169-3.258), impaired fasting glucose diagnosed pretransplantation (OR 1.807, CI: 1.091-2.993), and hyperglycemia in the first week posttransplantation (OR 1.856, CI: 1.133-3.043).

CONCLUSION

Our study suggests high body mass index, family diabetes history, hypomagnesemia pretransplantation, acute rejection episodes within the first 3 months after transplantation, tacrolimus use, impaired fasting glucose diagnosed pretransplantation, and hyperglycemia within the first week after transplantation are independent risk factors of PTDM in relative-living donor transplantation.