Skip Navigation


NDT Advance Access originally published online on January 3, 2008
Nephrology Dialysis Transplantation 2008 23(6):2033-2042; doi:10.1093/ndt/gfm875
This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
23/6/2033    most recent
gfm875v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (3)
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Kuypers, D. R. J.
Right arrow Articles by Vanrenterghem, Y.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kuypers, D. R. J.
Right arrow Articles by Vanrenterghem, Y.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author [2008]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org


Early clinical assessment of glucose metabolism in renal allograft recipients: diagnosis and prediction of post-transplant diabetes mellitus (PTDM)

Dirk R. J. Kuypers, Kathleen Claes, Bert Bammens, Pieter Evenepoel and Yves Vanrenterghem

Department of Nephrology and Renal Transplantation, University Hospitals Leuven, University of Leuven, Belgium

Correspondence and offprint requests to: Dirk R. J. Kuypers, Department of Nephrology and Renal Transplantation, University Hospitals Leuven, Herestraat 49, B-3000 Leuven, Belgium. Tel: +32-16-344580; Fax: +32-16-344599; E-mail: Dirk.kuypers{at}uz.kuleuven.ac.be



   Abstract
Top
 Abstract
Introduction
 Methods
 Statistical analysis
 Results
 Discussion
 Abbreviations
 References
 
Background. Post-transplant diabetes mellitus (PTDM) has serious consequences for renal allograft survival, cardiovascular risk and patient survival.

Methods. The predictive value of a fasting plasma glucose (FPG) level and oral glucose tolerance test (OGTT) on the fifth day post-transplantation were prospectively evaluated in 359 de novo renal allograft recipients. PTDM was defined as the uninterrupted need for glucose-lowering medication for at least 3 months.

Results. Sixty-four patients (17.8%) developed PTDM (follow-up 42.8 ± 16.9 months). Recipient age, body mass index (BMI), biopsy-proven acute rejection (BPAR), early graft function and proteinuria, tacrolimus-based therapy, cumulative corticosteroid dose and thiazide diuretics were associated with PTDM (univariate analysis). Multivariate logistic regression analysis identified age [OR (odds ratio): 1.05 (95% confidence interval: 1.019–1.083)], BMI [OR: 1.09 (1.013–1.189)], proteinuria on Day 5 [OR: 1.51 (1.043–2.210)] and BPAR [OR: 2.74 (1.345–5.604)] as independent risk factors for PTDM while a normal OGTT on Day 5 post-transplantation was associated with a strongly reduced risk for PTDM [OR: 0.03 (0.008–0.166)]. A similar risk reduction was conferred by a normal FPG on Day 5 [OR: 0.06 (0.012–0.338)]. OGTT had the best sensitivity (93.4%) and specificity (71.9%) with a high negative predictive value (97.6%).

Conclusion. The Day 5 OGTT is an independent predictor of PTDM that can be used for identifying recipients at reduced risk for PTDM, taking into account the impact of independent clinical risk factors like age, BMI and BPAR (treatment). This information can help clinicians in directing therapeutic management of modifiable risk factors for PTDM after renal transplantation.

Keywords: immunosuppressive drugs; new onset diabetes mellitus after transplantation (NODAT); oral glucose tolerance test (OGTT); post-transplant diabetes mellitus (PTDM); renal transplantation



   Introduction
Top
 Abstract
 Introduction
Methods
 Statistical analysis
 Results
 Discussion
 Abbreviations
 References
 
Post-transplant diabetes mellitus (PTDM) after solid organ transplantation and impaired glucose tolerance (IGT) have been recognized for many years [1]. The precise incidence of PTDM has been difficult to determine because of the use of different types of definitions (or the lack thereof), the application of various diagnostic tools, the variable length of follow-up, the often insidious onset of disease and its potential reversibility and the variable presence of associated risk factors [1–4]. The development of PTDM has serious consequences, not only for graft function and survival but also for patient survival and cardiovascular disease risk [2,5–9]. Early diagnosis and management of PTDM is paramount for avoiding or delaying the devastating effects of prolonged impaired glucose metabolism on patient and graft outcome [1,3,7,10–12]. Although in recent years tremendous efforts have been made in order to establish generally applied definitions of PTDM and IGT [1,3,13], few studies have addressed the question which clinical diagnostic tool can be best used, early after transplantation, for identifying patients at risk for developing PTDM.

We therefore prospectively evaluated three different simple clinical tests: fasting plasma glucose concentration (FPG) on the day of transplantation, FPG and oral glucose tolerance testing (OGTT) on Day 5 post-transplantation for the diagnosis and prediction of PTDM or IGT in 359 de novo renal allograft recipients. The predictive value of these tests was assessed in the presence of other known risk factors for PTDM.



   Methods
Top
 Abstract
 Introduction
 Methods
Statistical analysis
 Results
 Discussion
 Abbreviations
 References
 
Study population
All de novo renal transplant recipients transplanted in our unit between October 2000 and October 2005 were consecutively assessed for inclusion in the study. Of a total of 496 patients, 359 were eligible for the study. Patients had to perform an OGTT on Day 5 post-transplantation in order to enter the study. Reasons for exclusion were pre-existing DM (n = 93), combined or consecutive organ transplantation (n = 33), death within the first week after transplantation (n = 4), graft loss within the first week after grafting (n = 3) and mental or physical inability to perform the OGTT (n = 4). Informed consent was obtained from all patients and the study was carried out in accordance with the Declaration of Helsinki (2000) and Clinical Trials Registry NCT00442988 [ClinicalTrials.gov] (www.clinicaltrials.gov).

Study methods
An OGTT as stipulated by the WHO was performed at the end of the first week after transplantation [target postoperative day (POD) 5]. After an (10-h) overnight fast, 75 g of anhydrous glucose dissolved in water was ingested and plasma glucose concentrations were determined at time 0, 30, 60 and 120 min. The use of glucose-containing intravenous solutions was prohibited until 12 h prior and during the OGTT. FPG concentrations were measured on the day of transplantation, on Days 5, 30, 180, 270 and 360 after transplantation. At 3 months and 1 year post-transplantation, additional OGTT measurements could be performed but were not mandatory as the focus of this study was early prediction of PTDM. Glycosylated haemoglobin levels (HbA1c) were determined at the time of transplantation, on POD 30, 90 and 360 at the discretion of the clinicians.

Definitions of impaired glucose metabolism
The criteria defined by the WHO and the American Diabetic Association (ADA) [1,3,13] were used to define IGT, impaired fasting glucose (IFG) and DM. A 2-h postload plasma glucose concentration between 7.8 and 11.1 mmol/L (140–199 mg/dL) signified IGT while a 2-h postload plasma glucose concentration ≥ 11.1 mmol/L (≥200 mg/dL) confirmed the provisional diagnosis of DM. An FPG level between 5.6 and 6.9 mmol/L (100–125 mg/dL) defined IFG while an FPG ≥ 7.0 mmol/L (≥126 mg/dL) confirmed the provisional diagnosis of DM.

Treatment of impaired glucose metabolism
All patients with IGT and/or IFG (referred to as having ‘pre-diabetes’) received dietary instructions aimed at weight loss, lifestyle modifications and exercise, according to the guidelines stipulated by the consensus panel [1]. Patients with the provisional diagnosis of DM by OGTT were assessed for classical symptoms of diabetes including weight loss, polyuria, polydipsia and glucosuria. They also received dietary instructions aimed at reducing the intake of carbohydrates and fat. Instructions to loose 5–10% of body weight and to do more physical exercise were provided. If subsequent clinical follow-up indicated poor glycaemic control (usually assessed by ambulant home-monitoring of glucose profiles, follow-up FPG and HbA1c levels) oral glucose-lowering mediations were preferentially started as first-line treatment [gliquidon (GlurenormTM, Menarini, Florence, Italy) or gliclazide (DiamicronTM, Servier, Neuilly-sur-Seine, France)]. Alternatively, subcutaneous insulin therapy could be initiated as first-line treatment if deemed necessary by the clinician evaluating individual glycaemic control or insulin was used after the failure of oral therapy. PTDM was defined as the need for glucose-lowering medication for an uninterrupted period of at least 3 months.

Demographic and transplantation-related data
Data prospectively collected for all patients included age, gender, race, height, weight, calculated body mass index (BMI), renal diagnosis, blood group, history of smoking, time in renal replacement therapy prior to transplantation, type of renal replacement therapy, hepatitis C status, human leukocyte antigen (HLA) typing, total number of HLA mismatches, panel-reactive antibodies, number of prior transplantations and deceased donor versus living donor.

Transplantation outcome data
The following data were prospectively collected: occurrence of delayed graft function (DGF) defined as the need for dialysis therapy post-transplantation; incidence, number and timing of biopsy-proven acute rejection (BPAR) according to the ‘97 Banff criteria [14]; type of anti-rejection treatment, patient and graft survival and duration of follow-up.

Laboratory assessments
Renal allograft function was formally assessed on Days 5, 30, 90 and 360 per protocol by measuring serum creatinine concentration, estimated creatinine clearance using the Cockcroft–Gault formula [15] while proteinuria was measured on 24-h urine collection. Lipids (total cholesterol, HDL-cholesterol, LDL-cholesterol and triglycerides) were measured at the time of grafting, at 3 and 12 months. C-reactive protein was determined at the time of transplantation, on Days 5, 30, 90 and at 1 year while liver function tests were assessed on the days of transplantation, 5, 30 and 90 days.

Immunosuppressive drug therapy
Different immunosuppressive drug regimens were used during the study, including some experimental protocols. In order to obtain clinically relevant study categories of drug combinations in relationship to the analysis of predictors and risk factors for the development of PTDM, the following treatment groups were defined: (1) Tacrolimus (PrograftTM, Astellas, Munich, Germany) group: all patients taking tacrolimus in combination with glucocorticosteroids (MedrolTM, Upjohn, Diegem, Belgium) with or without an anti-metabolite drug [mycophenolate mofetil (CellceptTM, Roche, Basel, Switzerland), azathioprine (ImuranTM, GlaxoSmithKline, Genval, Belgium) or malononitrilamides (FK-778)] or with FTY720. Induction therapy with monoclonal anti-IL-2 receptor antibodies [basiliximab (SimulectTM, Novartis, Basel, Switzerland) and daclizumab (ZenapaxTM, Roche, Basel, Switzerland)] or anti-thymocyte globulin (ThymoglobulineTM, Pasteur–Mérieux, Brussels, Belgium) was used in some of these combinations. (2) Cyclosporine (NeoralTM, Novartis, Basel, Switzerland) group: all patients taking cyclosporine emulsion in combination with glucocorticosteroids with or without an anti-metabolite drug (mycophenolate mofetil, azathioprine) or with FTY720. Induction therapy with monoclonal anti-IL-2 receptor antibodies (basiliximab and daclizumab) or anti-thymocyte globulin was used in some of these combinations. (3) Tacrolimus–sirolimus group: all patients taking tacrolimus in combination with glucocorticosteroids and sirolimus. (4) Calcineurin-inhibitor (CNI)-free group: all patients on CNI-free drug combinations consisting of sirolimus (RapamuneTM, Wyeth, Louvain-La-Neuve, Belgium) or CTLA4-analogous in combination with mycophenolate mofetil, glucocorticosteroids and induction therapy with monoclonal anti-IL-2 receptor antibodies (basiliximab) or anti-thymocyte globulin. Oral glucocorticosteroids (methylprednisolone) were started in a daily dose of 16 mg (or 20 mg if body weight >80 kg) and bi-weekly tapered to a daily maintenance dose of 4 mg by Month 2 postoperative. No switch from tacrolimus to cyclosporine or from CNI to sirolimus or mycophenolate mofetil was allowed because of the diagnosis of IGT, IFG or PTDM. It was allowed to further taper or discontinue corticosteroids as a consequence of the diagnosis of IGT, IFG or PTDM from 3 months onwards. The latter strategy was not obligatory per protocol and the individual decision and clinical risk assessment was made by the clinicians. Pre-dose trough concentrations of tacrolimus and cyclosporine were determined daily in the first postoperative week, on Days 90 and 360. Daily corticosteroid dose was noted in the first week after transplantation while cumulative steroid doses were calculated for the first 3 months after grafting, excluding the standard intra-operative dose of 500 mg methylprednisolone that was administered intravenously to all patients.

Rejection treatment
All BPAR episodes were treated with 5 days of intravenous methylprednisolone followed by an oral tapering scheme until baseline (pre-rejection) maintenance corticosteroid doses were reached. T-cell depleting agents were used in the case of steroid-resistant rejection.

Concomitant medication
The use of thiazide diuretics, β-blockers and angiotensin-converting enzyme inhibitors (ACE-I) and angiotensin receptor blockers (ARB) was recorded.



   Statistical analysis
Top
 Abstract
 Introduction
 Methods
 Statistical analysis
Results
 Discussion
 Abbreviations
 References
 
Distribution of continuous data was evaluated (Kolmogorov–Smirnov and Shapiro–Wilks) and parametric tests and non-parametric tests were applied consequently when appropriate. Data were expressed as mean ± standard deviation (SD) except when stated differentially (median + range). Risk factors for PTDM were assessed by univariate analysis (Mann–Whitney–Wilcoxon, Kruskall–Wallis, SAS 9.1 software) and correlation analysis (Pearson, Spearman and Kendall–Tau). Categorical, dichotomous and ordinal variables were analysed using non-parametric tests (Fisher's exact test, chi-square and Cochran–Mantel–Haenszel). A stepwise logistic regression model with backward elimination was used for multivariate risk analysis. Univariate risk factors with a P-value ≤ 0.20 were retained in the initial basic multivariate model and checked for correlation. OGTT and FPG results were subsequently included separately in the basic model and were interchangeable. Risk factors assessed were recipient age, gender, race, renal diagnosis, history of smoking, type of renal replacement therapy and time on renal replacement therapy prior to grafting, number of prior transplantations, hepatitis C status, blood group type, panel-reactive antibodies, HLA type, locus-specific and total number of HLA mismatches, deceased versus living donor, weight, BMI, DGF, graft function, proteinuria, BPAR (treatment), time to first acute rejection, immunosuppressive treatment group (see the Methods section), trough blood concentrations of CNI, daily dose of CNI, daily corticosteroid dose, cumulative corticosteroid dose, use of thiazide diuretics, β-blockers and ACE-I/ARB, fasting glucose concentrations, HbA1c levels, total cholesterol, HDL- and LDL-cholesterol and triglycerides concentrations, C-reactive protein concentration, liver function tests and follow-up time since transplantation. Because the outcome variable (PTDM) and the study test (OGTT) were not completely independent in the case of very early development of PTDM, the logistic regression analysis was repeated taking into account only those recipients who developed PTDM at least 2 weeks after the first postoperative week (‘delayed’ PTDM). A P-value <0.05 was considered statistically significant.



   Results
Top
 Abstract
 Introduction
 Methods
 Statistical analysis
 Results
Discussion
 Abbreviations
 References
 
Patient demographics and transplantation-related parameters
Patients who developed PTDM during follow-up were significantly older at the time of transplantation, had a higher BMI and suffered BPAR more frequently compared with recipients who remained free of PTDM (Table 1). A total of 113 patients (31.4%) experienced at least one BPAR episode during follow-up with a median time to first rejection of 10 days (range: 2–1215 days). Ninety-one percent (n = 103) of first acute rejection episodes were diagnosed within the first 100 days after transplantation. Race and hepatitis C status were not different between groups while weight gain in the first postoperative year was not affected by PTDM (data not shown). No specific recipient HLA-A, -B or -DR type was associated with PTDM (data not shown). Renal allograft function on Day 5 post-transplantation (calculated creatinine clearance) was significantly lower in patients who developed PTDM while the latter tended to have more proteinuria on Day 5 but not significantly (Table 1). Subsequently, proteinuria became higher in the PTDM group 30, 90 and 360 days after transplantation, respectively (Day 30: 0.35 ± 0.79 g/24 h versus 0.19 ± 0.22 g/24 h, P = 0.005; Day 90: 0.41 ± 1.28 g/24 h versus 0.17 ± 0.24 g/24 h, P = 0.03; Day 360: 0.36 ± 1.0 g/24 h versus 0.16 ± 0.18 g/24 h, P = 0.05). Creatinine clearance remained significantly lower in patients who developed PTDM until Day 30 postoperative (0.72 ± 0.24 mL/s versus 0.82 ± 0.27 mL/s, P = 0.02) but by 90 days this difference disappeared (data not shown). C-reactive protein concentrations and liver function tests did not differ between patients with and without PTDM (data not shown). Triglyceride levels at the time of transplantation were significantly higher in patients developing PTDM (2.22 ± 1.27 mmol/L versus 1.73 ± 0.97 mmol/L; P = 0.008) but this difference disappeared during subsequent follow-up while total cholesterol levels, HDL- and LDL-cholesterol concentrations were comparable (data not shown).


View this table:
[in this window]
[in a new window]

  		Table 1 Univariate analysis of patient demographics and transplantation-related parameters between patients with (n = 64) and without (n = 295) PTDM

 
Immunosuppressive therapy
Table 2 summarizes the details of the four immunosuppressive treatment groups. A tacrolimus-based regimen (without sirolimus) was the most frequently used therapy (77.2%) and was significantly associated with the development of PTDM (Cochran–Mantel–Haenszel: P = 0.02) while only 1 of 42 cyclosporine-treated patients developed the latter complication (Table 3). Tacrolimus-treated recipients who developed PTDM had significantly higher predose trough blood tacrolimus concentrations in the first 4 days after grafting but this difference disappeared on subsequent POD (Table 3) until Day 360 (data not shown). In contrast, from POD 3 onwards, daily tacrolimus dose requirements corrected for body weight (mg/kg/day) remained significantly lower in the PTDM group throughout the first post-transplant year despite comparable trough concentrations from POD 5 onwards (data not shown). The cumulative corticosteroids dose in the first 3 months was higher in the PTDM group while there was a trend towards more frequent use of thiazide diuretics in the latter group(Table 3).


View this table:
[in this window]
[in a new window]

  		Table 2 Immunosuppressive drug treatment groups (n = 359)

 

View this table:
[in this window]
[in a new window]

  		Table 3 Univariate analysis of immunosuppressive and concomitant drugs between patients with (n = 64) and without (n = 295) PTDM

 
Oral glucose tolerance testing, FPG concentration and PTDM
A total of 64 patients (17.8%) developed PTDM during a mean follow-up period of 42.8 ± 16.9 months (range: 12.4–73.2 months). The median time to diagnosis PTDM was 54.5 days (range: 5–1629 days). Seventy-five percent of patients (n = 48) developed PTDM within the first 100 days after transplantation (Figure 1). Fifteen patients (23.4%) were treated with oral glucose-lowering drugs, 49 recipients (76.6%) received insulin therapy; 2 patients were on combined treatment. The mean duration of glucose-lowering drug therapy was 28.4 ± 18 months (median 25; range 3–77 months). After a mean study follow-up of 42.8 ± 16.9 months, 45 patients (70.3%) were still receiving ongoing glucose-lowering drug treatment. Of the 64 patients with PTDM, 50 (78.1%) were (or had been) on glucose-lowering drug therapy for at least 12 months; 10 recipients (15.6%) were (or had been) treated for 6–12 months while 4 patients (6.3%) were (or had been) on therapy for 3–6 months. Four additional patients received glucose-lowering therapy for respectively 5, 8, 9 and 13 days (3 insulin, 1 oral) and thus did not meet the preset criteria for PTDM.


Figure 1
View larger version (10K):
[in this window]
[in a new window]
[Download PowerPoint slide]
  		Fig. 1 Cumulative percentage of patients free of PTDM during study follow-up (n = 359).

 
Thirty-four OGTT measurements (9.4%) performed in the first week after transplantation were excluded from further analysis because of violation of steady-state conditions as stipulated by the WHO, leaving 325 per protocol OGTT results. On Days 90 and 360, respectively, 205 (57.1%) and 108 (30%) additional OGTT assessments were available for analysis (Table 4). Thirty-six FPG concentrations (10%) obtained in the first week were excluded because of violation of steady-state conditions. On Days 90 and 360, respectively, 204 (56.8%) and 108 (30%) patients had an additional FPG sampled. An OGTT indicating diabetes in the first postoperative week was significantly associated with subsequent development of PTDM, while normal FPG levels on Day 5 were significantly associated with freedom of PTDM (Table 4).


View this table:
[in this window]
[in a new window]

  		Table 4 OGTT results and FPG levels over time in patients with (n = 64) and without (n = 295) PTDM

 
A multivariate logistic regression model (backward elimination) including all clinical variables retained in univariate analysis (P-value <0.20) showed an increased risk for PTDM associated with older recipient age, higher BMI, more proteinuria and BPAR (treatment) (Table 5). Including the first week OGTT in this model showed that a normal OGTT result (as opposed to a diabetic OGTT) was associated with a reduced risk (97% risk reduction) for development of PTDM while increased recipient age remained an independent risk factor (Table 5). Similarly, replacing OGGT by FPG in the regression model, a normal first week FPG concentration (as opposed to a diabetic value) was also associated with a reduced risk (94% risk reduction) of PTDM while again age and acute rejection (treatment) remained independent risk factors (Table 5). When patients who developed PTDM very early after transplantation (n = 16, see the Statistical analysis section) were excluded in order to reduce the intrinsic interdependence between the study test (OGTT) and outcome variable (PTDM), similar results were obtained. Multivariate logistic regression analysis again identified recipient age [OR: 1.04 (95% confidence interval: 1.007–1.079), P = 0.01] as an independent risk factor for ‘delayed’ PTDM while a normal OGTT (as opposed to a diabetic OGTT) was associated with a reduced risk for ‘delayed’ PTDM [OR: 0.06 (0.013–0.285), P = 0.0009].


View this table:
[in this window]
[in a new window]

  		Table 5 Estimation of odds ratio (OR) for developing PTDM using multivariate logistic regression analysis (backwards elimination)

 
An OGTT in the first week post-transplantation (normal versus diabetic) had the highest negative predictive value (97.6%) for subsequent development of PTDM, with a high sensitivity (93.4%) but a moderate specificity (71.9%) and low positive predictive power (47.2%). Compared with early FPG determinations, OGTT was superior in terms of sensitivity and negative predictive value but not specificity and positive predictive value (21.6%, 89.1%, 97.9% and 61.5%, respectively, for diabetic versus normal FPG). An OGTT indicating IGT (versus normal) had an equally high negative predictive value (97.6%) with acceptable sensitivity (83.3%) but poor specificity (56.9%) and poor positive predictive value (13.9%). For an impaired FPG result (versus normal) these values were comparable with a diabetic FPG result (91.1%, 55.7%, 91.8% and 58%, respectively). When combined impaired and diabetic OGTT results versus normal were compared no significant changes in sensitivity, specificity or predictive values were noted (data not shown).

Taking into account only recipients who developed PTDM at least 2 weeks after the Day 5 OGTT (n = 48), the OGTT (diabetic versus normal) remained superior in terms of sensitivity (90.0%), specificity (71.9%) and negative predictive value (97.6%) but had a lower positive predictive value (36.8%) for ‘delayed’ PTDM.

A fasting glucose concentration obtained in the first 24 h after transplantation while patients were nil per mouth (with nasogastric tube) was significantly higher in patients who subsequently developed PTDM (Table 4). However, this simple determination of Day 1 glucose concentration was not retained in the multivariate model as an independent risk factor for PTDM. Glycosylated haemoglobin levels at the time of transplantation were available in 202/359 (56.2%) recipients. HbA1c levels on Day 0 were significantly higher in patients subsequently developing PTDM [5.44 ± 0.64% (n = 38) versus 5.21 ± 0.51% (n = 164); P = 0.0018].

In total 288, 204, 164 and 108 FPG levels were measured on Days 30, 180, 270 and 360, respectively. When compared between patients with and without PTDM, mean FPG levels remained significantly lower in the latter group (7.0 ± 2.9 versus 4.9 ± 0.6 mmol/L, P <0.0001; 6.8 ± 2.9 versus 5.0 ± 0.6 mmol/L, P < 0.0001; 6.4 ± 1.5 versus 5.0 ± 0.6 mmol/L, P < 0.0001 and 5.9 ± 0.5 versus 5.1 ± 0.7 mmol/L, P = 0.001, respectively) that also included 48 patients who had a diabetic OGTT on Day 5 but never met the criteria for PTDM during follow-up (Table 4). Twenty-eight of these 48 patients did have at least one repeat OGTT performed, either at 3 and/or 12 months after transplantation; for the remaining 20 recipients no repeat OGTT was performed. Twenty-five of the former 28 patients (89.3%) had an improvement of their repeat OGTT; 19 became normal while 6 became IGT. In only 3/28 patients with a repeat OGTT, the latter remained diabetic but still without the need for drug therapy as assessed by the clinicians.



   Discussion
Top
 Abstract
 Introduction
 Methods
 Statistical analysis
 Results
 Discussion
Abbreviations
 References
 
The high variability in reported incidences of PTDM ranging from 4 to >20% [2,4,16,17] reflects differences in applied diagnostic criteria, type of transplant, donor and recipient characteristics, type of immunosuppressive drug therapy and duration of follow-up [1–4]. Irrespective of its true incidence, once PTDM has developed, it becomes associated with reduced graft function and survival as well as reduced patient survival [2,5–9]. Whether the latter is due to the induction of post-transplant hyperglycaemia itself or rather the result of pre-existing glucose metabolic disorders (GMD) remains to be determined. Because of this important impact on transplantation outcome, a lot of recent studies have focused on the identification of risk factors for PTDM and the validation of predictive clinical diagnostic tools that would allow early diagnosis and hence adequate management of the disease [18–21].

This prospective study demonstrated that early assessment of glucose metabolism in renal recipients by performing an OGGT (and to a lesser degree by an FPG) on the fifth day post-transplantation can identify patients at reduced risk for subsequent development of PTDM, taking into account other clinical risk factors. For recipients who developed PTDM very early after transplantation, the true predictive value of an OGTT is challenged because of the intrinsic interdependence between the latter and the definition of PTDM, reducing a Day 5 OGTT to a diagnostic tool rather than a predictive tool. However, when patients who developed PTDM very early were excluded, a normal Day 5 OGTT still remained significantly associated with a reduced risk for ‘delayed’ PTDM in multivariate analysis. While 82.4% of patients remained free of PTDM during follow-up, a normal OGTT on Day 5 further increased the negative predictive value to 97.6%, irrespective of whether all or only ‘delayed’ instances of PTDM were assessed. The positive predictive values of a Day 5 OGTT and FPG were only moderate, taking into account the prevalence of PTDM in this study population of 17.6%. These limited positive predictive diagnostic powers of OGTT and FPG are not surprising when considering the large number of additional clinical risk factors that can affect development of PTDM, strongly depending on the characteristics of the studied patient population [18–20]. Secondly, pre-existing GMD were not systematically assessed in this study cohort by performing pre-transplantation OGTT [17], partly because of organisational reasons. Pre-transplantation OGTT measurements in (uraemic) transplant candidates could have shed more light on the extent of pre-existing GMD and possibly on the subsequent risk of PTDM after grafting. The slightly better positive predictive performance of FPG compared to OGTT in this patient cohort is in contradiction with a recent study showing that FPG underestimates the true prevalence of PTDM compared to OGTT [22]. However, in the latter trial FGP and OGTT were primarily tested for PTDM risk stratification of recipients with IFG beyond 6 months after transplantation, excluding patients who had developed PTDM prior to 6 months.

While several clinical variables were associated with the development of PTDM in univariate analysis, in accordance with previous reports [18–20], we could not confirm an association between PTDM and adult dominant polycystic kidney disease (ADPKD) and hepatitis C status, respectively [18,20,23]. The latter could be explained by the absolute low number of hepatitis C-positive recipients. Multivariate analysis identified patient age, BMI and BPAR (treatment) as independent risk factors for PTDM, thereby confirming other studies [18–20]. The finding that Day 5 proteinuria conferred an increased risk for subsequent PTDM is intriguing but could also be simply explained by the fact that patients experiencing BPAR also had significantly higher proteinuria on Day 5 (0.53 ± 0.47 g/24 h versus 0.48 ± 0.72 g/24 h; P = 0.01), a relationship previously documented by others [24]. Other known risk factors like a positive family history of DM and CMV infection were not captured by this study [20]. Across the different immunosuppressive drug regimens, tacrolimus in combination with corticosteroids was associated with an increased risk for PTDM, especially when very early drug exposure was high [1,18,20,25]. The inhibition of insulin secretion by tacrolimus is concentration dependent [26], and this might explain why in recent trials aiming at lower tacrolimus exposure, lower incidences of PTDM are reported [27]. Intriguingly, in patients developing PTDM, daily tacrolimus dose requirements remained significantly lower throughout the first year, a finding also reported by others [28], suggesting that potentially pre-existing metabolic characteristics of recipients prone to develop PTDM could also affect tacrolimus metabolism or disposition. Of course, the relatively low absolute number of cyclosporine-treated recipients in this study might have accentuated these differences across immunosuppressive regimens. In addition, early corticosteroid withdrawal could have potentially reduced the incidence of PTDM because of its beneficial effects on insulin resistance [29] but was not allowed by the protocol. As 75% of all instances of PTDM occurred within the first 100 days post-transplantation, the effect of later steroid withdrawal could not be properly assessed. While the higher cumulative corticosteroid dose in recipients with PTDM mainly reflects the higher incidence of BPAR, only 78.1% (25/32) of acute rejection episodes preceded the development of PTDM. This finding suggests that apart from corticosteroids, BPAR itself could have additional metabolic effects leading to IGT as supported by other studies failing to show an independent effect of high-dose steroids on the incidence of PTDM [19].

In conclusion, a normal OGTT result on Day 5 post-transplantation can be used for identifying recipients at reduced risk for PTDM, taking into account the impact of independent clinical risk factors such as age, BMI and BPAR (treatment). This information can help clinicians in planning therapeutic management of modifiable risk factors for PTDM after renal transplantation. Pre-transplant OGTT measurement should be considered as a potentially valuable alternative in future studies assessing the risk of PTDM in renal allograft recipients.



   Abbreviations
Top
 Abstract
 Introduction
 Methods
 Statistical analysis
 Results
 Discussion
 Abbreviations
References
 
ADA, American Diabetes Association; ADPKD, adult dominant polycystic kidney disease; BMI, body mass index; BPAR, biopsy-proven acute rejection; DGF, delayed graft function; DM, diabetes mellitus; FPG, fasting plasma glucose; GMD, glucose metabolic disorders; HLA, human leukocyte antigen(s); IFG, impaired fasting glucose; IGT, impaired glucose tolerance; NODAT, new onset diabetes mellitus after transplantation; OGTT, oral glucose tolerance test; PTDM, post-transplant diabetes mellitus; POD, postoperative day(s).



   Acknowledgments
 
We thank the clinical nurses H. Wielandt, R. Eerdekens and A. Herelixcka for their continuous efforts in this study. We also thank the entire Leuven Collaborative group for Renal Transplantation (LSGN) for their continuous support. Finally, we thank our colleagues from the Department of Endocrinology, Professor Dr Chantal Mathieu and Dr Pieter Gillard, for their valuable scientific advice.

Conflict of interest statement. None declared.



   References
Top
 Abstract
 Introduction
 Methods
 Statistical analysis
 Results
 Discussion
 Abbreviations
 References
 

  1. Davidson J, Wilkinson A, Dantal J, et al. New-onset diabetes after transplantation: 2003 international consensus guidelines. Transplantation (2003) 75:SS3–SS24.[CrossRef][Web of Science][Medline]
  2. Kasiske BL, Snyder JJ, Gilbertson D, et al. Diabetes mellitus after kidney transplantation in the United States. Am J Transplant (2003) 3:178–185.[CrossRef][Web of Science][Medline]
  3. Davidson JA, Wilkinson A. New-onset diabetes after transplantation 2003 international consensus guidelines: an endocrinologist's view. Diabetes Care (2004) 27:805–812.[Free Full Text]
  4. Montori VM, Basu A, Erwin PJ, et al. Posttransplantation diabetes: a systematic review of the literature. Diabetes Care (2002) 25:583–592.[Abstract/Free Full Text]
  5. Roth D, Milgrom M, Esquenazi V, et al. Posttransplant hyperglycemia. Increased incidence in cyclosporine-treated renal allograft recipients. Transplantation (1989) 47:278–281.[Web of Science][Medline]
  6. Cosio FG, Pesavento TE, Kim S, et al. Patient survival after renal transplantation: IV. Impact of post-transplant diabetes. Kidney Int (2002) 62:1440–1446.[CrossRef][Web of Science][Medline]
  7. Jindal Rm, Hjelmesaeth J. Impact and management of posttransplant diabetes mellitus. Transplantation (2000) 70:S58–S63.
  8. Revanur VK, Jardine AG, Kingsmore DB, et al. Influence of diabetes mellitus on patient and graft survival in recipients of kidney transplantation. Clin Transplant (2001) 15:89–94.[CrossRef][Web of Science][Medline]
  9. Kasiske BL, Chakkera HA, Roel J. Explained and unexplained ischemic heart disease risk after renal transplantation. J Am Soc Nephrol (2000) 11:1735–1743.[Abstract/Free Full Text]
  10. Woodward RS, Schnitzler MA, Baty J, et al. Incidence and cost of new onset diabetes mellitus among U.S. wait-listed and transplanted renal allograft recipients. Am J Transplant (2003) 3:590–598.[CrossRef][Web of Science][Medline]
  11. Markell M. New-onset diabetes mellitus in transplant patients: pathogenesis, complications, and management. Am J Kidney Dis (2004) 43:953–965.[CrossRef][Web of Science][Medline]
  12. Benhamou PY, Penfornis A. Natural history, prognosis and management of transplantation-induced diabetes mellitus. Diabetes Metab (2002) 28:166–175.[Web of Science][Medline]
  13. American Diabetes Association. Diabetes Care (2003) 26:S5–S20. Report of the expert committee on the diagnosis and classification of diabetes mellitus.[CrossRef][Medline]
  14. Racusen L, Colvin RB, Solez K, et al. Antibody-mediated rejection criteria—an addition to the Banff ‘97 classification of renal allograft rejection. Am J Transplant (2003) 3:708–714.[CrossRef][Web of Science][Medline]
  15. Cockcroft D, Gault M. Prediction of creatinine clearance from serum creatinine. Nephron (1976) 16:31–41.[Web of Science][Medline]
  16. Vesco L, Busson M, Bedrossian J, et al. Diabetes mellitus after renal transplantation: characteristics, outcome, and risk factors. Transplantation (1996) 61:2465–2466.
  17. van Hooff JP, Christiaans MH, van Duijnhoven EM. Tacrolimus and posttransplant diabetes mellitus in renal transplantation. Transplantation (2005) 79:1465–1469.[CrossRef][Web of Science][Medline]
  18. Shah T, Kasravi A, Huang E, et al. Risk factors for development of new-onset diabetes mellitus after kidney transplantation. Transplantation (2006) 82:1673–1676.[CrossRef][Web of Science][Medline]
  19. Joss N, Staatz CE, Thomson AH, et al. Predictors of new onset diabetes after renal transplantation. Clin Transplant (2007) 21:136–143.[CrossRef][Web of Science][Medline]
  20. Rodrigo E, Fernandez-Fresnedo G, Valero R, et al. New-onset diabetes after kidney transplantation: risk factors. J Am Soc Nephrol (2006) 17:S291–S295.[Abstract/Free Full Text]
  21. van Hooff JP, Christiaans MH, van Duijnhoven EM. Evaluating mechanisms of post-transplant diabetes mellitus. Nephrol Dial Transplant (2004) 19:vi8–vi12.
  22. Sharif A, Moore RH, Baboolal K. The use of oral glucose tolerance tests to risk stratify for new-onset diabetes after transplantation: an under diagnosed phenomenon. Transplantation (2006) 82:1667–1672.[CrossRef][Web of Science][Medline]
  23. Hamer RA, Chow CL, Ong AC, et al. Polycystic kidney disease is a risk factor for new-onset diabetes after transplantation. Transplantation (2007) 83:36–40.[CrossRef][Web of Science][Medline]
  24. Halimi JM, Laouad I, Buchler M, et al. Early low-grade proteinuria: causes, short-term evolution, and long-term consequences in renal transplantation. Am J Transplant (2005) 5:2281–2288.[CrossRef][Web of Science][Medline]
  25. Vincenti F, Friman S, Scheuermann E, et al. Results of an international, randomized trial comparing glucose metabolism disorders and outcome with cyclosporine versus tacrolimus. Am J Transplant (2007) 7:1506–114.[CrossRef][Web of Science][Medline]
  26. van Duijnhoven EM, Christiaans MH, Boots JM, et al. Glucose metabolism in the first 3 years after renal transplantation in patients receiving tacrolimus versus cyclosporine-based immunosuppression. J Am Soc Nephrol (2002) 13:213–220.[Abstract/Free Full Text]
  27. Abramowicz D, Vanrenterghem Y, Squifflet JP, et al. Efficacy and cardiovascular safety of daclizumab, mycophenolate mofetil, tacrolimus, and early steroid withdrawal in renal transplant recipients: a multicenter, prospective, pilot trial. Clin Transplant (2005) 19:475–482.[CrossRef][Web of Science][Medline]
  28. Rodrigo E, Pinera C, de Cos MA, et al. Evolution of tacrolimus blood levels and concentration-dose ratios in patients who develop new onset diabetes mellitus after kidney transplantation. Transpl Int (2005) 18:1152–1157.[CrossRef][Web of Science][Medline]
  29. Boots JM, van Duijnhoven EM, Christiaans MH, et al. Glucose metabolism in renal transplant recipients on tacrolimus: the effect of steroid withdrawal and tacrolimus trough level reduction. J Am Soc Nephrol (2002) 13:221–227.[Abstract/Free Full Text]
Received for publication: 11.10.07
Accepted in revised form: 16.11.07


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?



This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
23/6/2033    most recent
gfm875v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (3)
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Kuypers, D. R. J.
Right arrow Articles by Vanrenterghem, Y.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kuypers, D. R. J.
Right arrow Articles by Vanrenterghem, Y.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?