Pre-transplant HbA1c level as an early marker for new-onset diabetes after renal transplantation

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

BACKGROUND

Post-transplant diabetes mellitus occurs in 10-40% of kidney transplant recipients and is associated with increased risk of developing cardiovascular diseases. Early identification of patients with a higher risk of developing diabetes could allow to take timely measures. However, no validated model exists to predict the risk of post-transplant diabetes mellitus.

METHODS

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 3 months 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 3 months were established.

RESULTS

At 3 months 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%.

CONCLUSIONS

The HbA1c value at transplantation was the strongest predictor for post-transplant diabetes mellitus at 3 months post-transplant. Furthermore, at least in our population, a pre-transplant HbA1c of ≥ 5.3% can be used as an easy tool to identify patients at high risk of early post-transplant diabetes mellitus.

OGTT 2-hour serum C-peptide index as a predictor of post-transplant diabetes mellitus in kidney transplant recipients

Background

The high incidence of post-transplant diabetes mellitus (PTDM) necessitates the identification of new factors to explain its pathogenesis. This study aimed to clarify the association between the C-peptide index (CPI) and PTDM.

Methods

A total of 290 non-diabetic kidney transplant patients were analyzed. All subjects underwent a 75 g oral glucose tolerance test (OGTT). Plasma glucose concentrations, serum C-peptide levels, hemoglobin A1c (HbA1c), and other biochemical indicators were measured. CPI was calculated as the ratio of serum C-peptide to plasma glucose.

Results

Among the 290 patients, 36 (12.4%) developed PTDM at the end of 1 year. Patients with PTDM had older age (P<0.001), higher levels of body mass index (BMI) (P=0.004) and HbA1c (P=0.001), a higher proportion of deceased donors (P=0.045), and lower levels of 2 h-CPI (P=0.02) than those without PTDM. The OGTT 2 h-CPI was positively correlated with BMI, HbA1c, type of calcineurin inhibitor, albumin, and triglyceride. Multivariate logistic regression and Cox hazard model analysis showed that pre-transplant OGTT 2 h-CPI was an independent predictor for the development of PTDM, together with age, BMI, and HbA1c.

Conclusions

Of the pre-transplant factors studied, OGTT 2 h-CPI proved to be an independent predictor of PTDM.

Association of Body Mass Index and the Risk of New-Onset Diabetes After Kidney Transplantation: A Meta-analysis

OBJECTIVE

To comprehensively examine the correlation between body mass index (BMI) and the risk of new-onset diabetes after kidney transplantation (NODAT).

METHODS

The electronic databases Pubmed, Embase, and Cochrane Library, updated in December 2016, were searched, and a literature review was conducted as well to identify relevant research studies. With the use of R 3.12 software, the association between BMI and NODAT risk was analyzed by means of a meta-analysis, with the mean differences (MDs) and their 95% confidence intervals (CIs) as effect indexes. Publication bias was assessed with the use of the Egger test. A sensitivity analysis was performed by excluding 1 study at a time. And the overall morbidity of NODAT was calculated.

RESULTS

In the meta-analysis, 55 eligible studies involving 15,458 kidney transplantation cases were included. After the heterogeneity test, the random-effects model was used to calculate the pooled results of the effect indexes. The results of the meta-analysis showed that BMI was an independent risk factor of NODAT (MD, 1.88; 95% CI, 1.48-2.27). No publication bias was found among the included studies (t = 0.3417; P = 0.7339). The sensitivity analysis revealed that the pooled MD did not reverse after ignoring 1 study at a time. In addition, the overall morbidity of NODAT was 21% (95% CI, 21%-23%).

CONCLUSIONS

Our results suggest that BMI is an independent risk factor for NODAT.

Pretransplant HbA1c and Glucose Metabolism Parameters in Predicting Posttransplant Diabetes Mellitus and Their Course in the First 6 Months After Living-Donor Renal Transplant

OBJECTIVES

Posttransplant diabetes mellitus is a common and serious metabolic complication after renal transplant. Patients with uremia are known to have abnormal glucose metabolism characterized by insulin resistance and defects in insulin secretion, which are ameliorated to some extent with renal replacement therapy and more so with renal transplant. However, the diabetogenicity of calcineurin inhibitors compounds this state of dysglycemia and promotes the development of diabetes in some patients. It is not clear whether pretransplant dysglycemia is a risk factor for posttransplant diabetes mellitus and, if so, which between insulin resistance and pancreatic β-cell dysfunction is a major determinant in predicting posttransplant diabetes mellitus. Here, we examined the roles of the pretransplant oral glucose tolerance test, glycated hemoglobin (HbA1c) levels, and homeostatic model assessment-derived insulin resistance and beta-cell function in the prediction of posttransplant diabetes mellitus and the course of these indexes posttransplant. Our aim was to examine the correlations between these factors and their changes posttransplant with the development of posttransplant diabetes mellitus.

MATERIALS AND METHODS

Pretransplant fasting blood was drawn from patients for plasma glucose, insulin, C-peptide, and HbA1c levels, which was followed by a 2-hour oral glucose tolerance test. After transplant, patients were followed for 6 months to detect posttransplant diabetes mellitus. Serum insulin, C-peptide, and glycated hemoglobin levels were reexamined in patients with posttransplant diabetes mellitus at 1 and 6 months.

RESULTS

Twenty-one patients (29%) developed posttransplant diabetes mellitus. Pretransplant HbA1c was associated with development of posttransplant diabetes mellitus (odds ratio 27.04) on logistic regression. Homeostatic model assessment-derived insulin resistance improved significantly at 6 months posttransplant, whereas beta-cell function remained lower than pretransplant levels in patients with posttransplant diabetes mellitus.

CONCLUSIONS

Pretransplant HbA1c may be used as a predictive marker for posttransplant diabetes mellitus. Insulin resistance but not beta-cell function improves in patients with posttransplant diabetes mellitus at 6 months posttransplant.

Higher Pretransplantation Hemoglobin A1c Is Associated With Greater Risk of Posttransplant Diabetes Mellitus

Introduction

Posttransplantation diabetes mellitus (PTDM) is a common complication among kidney transplant recipients and is associated with a higher risk of cardiovascular events and poorer graft and patient survival. The association of pretransplantation hemoglobin A1c (HbA1c) with PTDM remains unclear. Identifying recipients at greatest risk for PTDM may help guide monitoring and treatment strategies to prevent or delay the onset of PTDM.

Methods

We analyzed data from 1499 nondiabetic primary kidney transplant recipients with available pretransplantation HbA1c values in the United States Renal Data System (USRDS) from 2005 to 2011. Recipients with pretransplantation diabetes diagnosis or HbA1c ≥ 6.5% were excluded. We assessed the association of pretransplantation HbA1c with PTDM using Cox proportional hazards models. Pretransplantation HbA1c level as a continuous variable was modeled using restricted cubic splines with knots at the 25th, 50th, and 75th percentiles. Based on results from this model, pretransplantation HbA1c was further modeled using a linear spline with a single knot at 5.4%.

Results

A total of 395 recipients (26.4%) developed PTDM over a median follow-up of 1.8 years. Pretransplantation HbA1c was not significantly associated with risk of PTDM below 5.4%, whereas each 1% higher HbA1c above 5.4% was associated with an adjusted hazard ratio of 1.84 (95% confidence interval = 1.28, 2.66; P for change in slope = 0.04).

Discussion

Higher pretransplantation HbA1c above 5.4% is independently associated with greater risk of PTDM among kidney transplant recipients. A continuous relationship between pretransplantation HbA1c and risk of PTDM suggests that increased risk starts at HbA1c levels well below current thresholds for prediabetes.

Dysglycemia after renal transplantation: Definition, pathogenesis, outcomes and implications for management

New-onset diabetes after transplantation (NODAT) is major complication following renal transplantation. It commonly develops within 3-6 mo post-transplantation. The development of NODAT is associated with significant increase in risk of major cardiovascular events and cardiovascular death. Other dysglycemic states, such as impaired glucose tolerance are also associated with increasing risk of cardiovascular events. The pathogenesis of these dysglycemic states is complex. Older recipient age is a consistent major risk factor and the impact of calcineurin inhibitors and glucocorticoids has been well described. Glucocorticoids likely cause insulin resistance and calcineurin inhibitors likely cause β-cell toxicity. The impact of transplantation in incretin hormones remains to be clarified. The oral glucose tolerance test remains the best diagnostic test but other tests may be validated as screening tests. Possibly, NODAT can be prevented by administering insulin early in patients identified as high risk for NODAT. Once NODAT has been diagnosed altering immunosuppression may be acceptable, but creates the difficulty of balancing immunological with metabolic risk. With regard to hypoglycemic use, metformin may be the best option. Further research is needed to better understand the pathogenesis, identify high risk patients and to improve management options given the significant increased risk of major cardiovascular events and death.

New-onset diabetes and glucose regulation are significant determinants of left ventricular hypertrophy in renal transplant recipients

BACKGROUND

New-onset diabetes after transplantation (NODAT) is associated with decreased graft survival and an increased risk for cardiovascular disease. The objective of this study was to evaluate the risk factors for development of NODAT and its' relationship with arterial stiffness and left ventricular mass index (LVMI) in kidney transplant recipients.

METHODS

159 kidney transplant recipients were selected from our transplantation center who underwent renal transplantation between years 2007 and 2010.

RESULTS

Among 159 patients, 57 (32.2%) patients were with NODAT who were significantly older than patients without diabetes (P: 0.0001). Patients with NODAT had significantly higher pulse wave velocity (PWv) (P: 0.033) and left ventricular mass index LVMI (P: 0.001) compared to patients without NODAT. Further analysis was done according to LVMI as follows: LVMI > 130 g/m(2) (n: 57) and LVMI ≤ 130 g/m(2) (n: 102). We observed higher office systolic and diastolic BP, serum trygliceride, glucose, creatinine, age, and HbA1c (P: 0.0001) levels in patients with LVMI > 130 g/m(2). Linear regression analysis revealed that HbA1c was the major determinant of LVMI (P: 0.026, β: 0.361).

CONCLUSIONS

HbA1c is the major determinant of LVMI, so strict control of serum glucose levels is essential for preventing cardiovascular disease in patients with NODAT.

Pretransplant HbA1c Is a Useful Predictor for the Development of New-Onset Diabetes in Renal Transplant Recipients Receiving No or Low-Dose Erythropoietin

Aims. To evaluate the predictive power of pretransplant HbA1c for new-onset diabetes after transplantation (NODAT) in kidney transplant candidates, who had several predispositions for fluctuated HbA1c levels. Methods. We performed a retrospective study of 119 patients without diabetes who received kidney transplantation between March 2000 and January 2012. Univariate and multivariate logistic regression analyses were used to investigate the association of several parameters with NODAT. Predictive discrimination of HbA1c was assessed using a receiver-operating characteristic curve. Results. Seventeen patients (14.3%) developed NODAT within 1 year of transplantation. Univariate logistic regression analysis revealed that recipient age, gender, and HbA1c were predictors of NODAT. In the multivariate analysis, the association between pretransplant HbA1c and NODAT development did not reach statistical significance (P = 0.07). To avoid the strong influence of high-dose erythropoietin on HbA1c levels, we performed subgroup analyses on 85 patients receiving no or low-dose (≤6000 IU/week) erythropoietin. HbA1c was again an independent predictor for NODAT. Receiver-operating characteristic analysis revealed a cut-off value of 5.2% with an optimal sensitivity of 64% and specificity of 78% for predicting NODAT. Conclusions. Our results reveal that the pretransplant HbA1c level is a useful predictor for NODAT in patients receiving no or low-dose erythropoietin.