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NDT Advance Access originally published online on May 8, 2008
Nephrology Dialysis Transplantation 2008 23(10):3337-3342; doi:10.1093/ndt/gfn246
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© 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


Prevalence of abnormal glucose metabolism in Chinese renal transplant recipients: a single centre study

Hoi Wong Chan, Chi Yuen Cheung, Yan Lun Liu, Yiu Han Chan, Ho Sing Wong, Wai Leung Chak, Koon Shing Choi, Ka Foon Chau and Chun Sang Li

Renal Unit, Department of Medicine, Queen Elizabeth Hospital, Hong Kong, China SAR

Dr Chi Yuen Cheung, Department of Medicine, Queen Elizabeth Hospital, 30 Gascoigne Road, Kowloon, Hong Kong, China SAR. Tel: +82-852-29588888; E-mail: simoncycheung{at}gmail.com



   Abstract
Top
 Abstract
Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. Post-transplant diabetes mellitus (PTDM) after renal transplantation is associated with adverse outcome on patient and graft survival. Fasting blood glucose alone will underestimate diabetes and also ignores diagnosis of impaired glucose tolerance (IGT). IGT has a strong correlation with diabetes and cardiovascular risk.

Methods. In this cross-sectional study, we estimate the prevalence of abnormal glucose metabolism (AGM) using oral glucose tolerance test (OGTT) and identify its predictive factors. Patients who received kidney transplantation in our centre without pre-transplant diabetes were recruited. OGTT was performed in patients with fasting glucose levels between 5.6 and 6.9 mmol/L for at least two occasions 6 months post-transplantation.

Results. Of 119 patients recruited, 31 had OGTT performed. The prevalence of PTDM, IGT and IFG was 21.8 (26/119)%, 6.7 (8/119)% and 3.4 (4/119)% respectively. Thus the overall prevalence of AGM was 31.9%. Age (P = 0.003), body mass index (P = 0.032), hepatitis B seropositivity status (P = 0.01), CMV infection (P = 0.02) and acute rejection (P = 0.002) were all associated with development of AGM. Using multivariate analysis, only older age at transplant (OR 1.09), history of acute rejection (OR 3.40) and hepatitis B seropositivity (OR 3.13) were significantly associated with the development of AGM.

Conclusion. AGM is common in our renal transplant recipients.

Keywords: abnormal glucose metabolism; renal transplant



   Introduction
Top
 Abstract
 Introduction
Subjects and methods
 Results
 Discussion
 References
 
Post-transplant diabetes mellitus (PTDM) after solid organ transplantation is a well-known serious metabolic complication. It can adversely affect the patient and graft survival [1]. Moreover, it has been shown that development of PTDM is a major determinant of cardiovascular mortality and morbidity in renal transplant recipients [2].

The prevalence of PTDM varies widely among the literature [3,4]. The main reason is that there is no consensus regarding the definition and diagnostic criteria. Clinical trials seldom included oral glucose tolerance test (OGTT) to determine the exact incidence of glycaemic abnormality in kidney transplant recipients.

Diagnosis of PTDM has been clarified by the International Consensus Guidelines, which is based on American Diabetic Association (ADA) and World Health Organization (WHO) guidelines [5–7]. Early recognition leads to early appropriate treatment. Moreover, the detection of ‘pre-diabetic state’ (impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT)) is also important because of the increased risk of development of diabetes and cardiovascular risks [8]. Fasting glucose is commonly used in clinical settings for the diagnosis of diabetes instead of OGTT because of its simplicity. However, it is less sensitive and specific than an OGTT in diagnosis [9,10]. Fasting glucose alone will underestimate diabetes [9] and also ignores the diagnosis of IGT. IGT itself can only be diagnosed with OGTT and has been shown to have a great correlation with diabetes and cardiovascular risks [11,12].

The aim of this study was to show the prevalence of abnormal glucose metabolism (AGM = PTDM + IGT + IFG) after kidney transplantation when OGTT was used. In addition, the associated risk factors for its development were also studied.



   Subjects and methods
Top
 Abstract
 Introduction
 Subjects and methods
Results
 Discussion
 References
 
This was a cross-sectional study. All Chinese patients who received solitary living-related or cadaveric kidney transplantation from 1 July 1997 to 31 December 2005 in Queen Elizabeth Hospital, Hong Kong with follow-up >6 months were recruited.

Patients with pre-transplant diabetes mellitus were excluded. The study was performed in accordance with the Declaration of Helsinki. A written consent was obtained from each patient. Demographic and clinical data were extracted from the patients’ records.

Participants were initially classified into three categories: (1) PTDM with fasting blood glucose level ≥ 7.0 mmol/L for two occasions; (2) normal with fasting blood glucose level <5.6 mmol/L and (3) fasting blood glucose level between 5.6 and 6.9 mmol/L for at least two occasions 6 months after transplantation.

For patients under the 3rd category, an OGTT was performed. After an overnight 8-h fast, fasting blood glucose was taken. Patients were then administered 75 g of glucose (113 ml of Polycal) with post-prandial samples taken 2 h after administration of glucose. The results of the test were classified by ADA criteria (Table 1).


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  		Table 1 OGTT classification according to ADA criteria

 
Immunosuppressive regimens
Our patients were basically put on a triple immunosuppressive therapy with either tacrolimus or Neoral cyclosporine, concomitantly with prednisolone and azathioprine therapy. All patients received 500 mg of methylprednisolone at induction. This was followed by intravenous hydrocortisone 100 mg every 6 h for 3 days and followed by oral prednisolone 30 mg daily. The dose of prednisolone was gradually tapered after the first month at a rate of 2.5 mg every 2 weeks then maintained at 7.5 mg daily. Azathioprine was given at a dose of 1.5 mg/kg daily since Day 1 after transplant. Cyclosporine (CsA) was initially administered orally as a loading dose of 10mg/kg within 12 h of surgery and then 5 mg/kg b.i.d. An abbreviated formula based on limited sampling strategy was used in this study to estimate the cyclosporine area under 12-h concentration-time curve (AUC0–12). Calculation of cyclosporine AUC0–12 was based on the formula: 452.4 + C0 x 17.5 + C1.5 x 1.89 [C0: cyclosporine trough level; C1.5: 1.5-h post-dose cyclosporine level] [13]. The dose of cyclosporine was gradually titrated to maintain the abbreviated AUC0–12 at ~6000– 8000 ng x h/ml in the first 3-month post-transplant and 4000–6000 ng x h/ml from 3-month post-transplant onwards [14]. On the other hand, tacrolimus was administered orally with a loading dose of 0.3 mg/kg within 12 h of surgery and then 0.15 mg/kg b.i.d. Abbreviated tacrolimus AUC0–12 monitoring was used. Calculation of tacrolimus AUC0–12 was by the formula: 16.2 + C2 x 2.4 + C4 x 5.9 [C2: 2-h post-dose tacrolimus level; C4: 4-h post-dose tacrolimus level]. Based on a previous pilot study in stable patients on tacrolimus in our centre, AUC0–12 value was kept at ~100–150 ng x h/ml in first 3 months and ~80–100 ng x h/ml after 3 months [15]. Some of our patients have received interleukin-2 receptor antagonist during induction therapy since 2001. Patients on cyclosporine were given Basiliximab (Simulect, Norvatis, Switzerland) while patients on tacrolimus were given Daclizumab (Zenapax, Roche, NJ, USA). Basiliximab was given at a dose of 20 mg ~2 h before transplantation and the second dose was given 4 days after transplantation. Daclizumab was given at 1 mg/kg infusion ~2 h before transplantation and then every 14 days for four more doses.

Acute rejection was defined as any episode with the relevant clinical and laboratory signs and symptoms and confirmed by renal biopsy. Episodes during which treatment against acute rejection was given and for which no biopsy could be performed due to contraindications were considered as acute rejection. There was clinical suspicion of rejection in the case of an unexplained rise or insufficient decrease of serum creatinine, with or without other signs, such as fever, graft tenderness, decreased renal perfusion on nuclear scan or hypertension. Contraindications for biopsy were bleeding disorders or uncontrolled severe hypertension. Our protocol for treating acute cellular rejection was 500 mg methylprednisolone intravenously for 3 days. In the case of steroid resistant rejection, an appropriate antibody therapy was started.

Statistical analyses
The statistical software SPSS (SPSS 13.0, Inc., Chicago, IL, USA) was used to perform the analyses. Continuous data are expressed as means ± standard deviation (SD); categorical data are expressed as percentages. Continuous data were analysed by the independent sample t-test to detect the difference between groups; categorical data are analysed by the chi-square test. Associations between the clinical variables and the development of AGM were estimated using both univariate and multivariate logistic regression analyses. The multivariate model incorporated a backward and stepwise elimination method using variables with a P-value of <0.05 from the univariate analysis. A P-value of <0.05 was defined as statistically significant in this study.



   Results
Top
 Abstract
 Introduction
 Subjects and methods
 Results
Discussion
 References
 
From a total of 147 patients receiving a kidney allograft between July 1997 and December 2005, 14 patients were excluded due to pre-transplant diabetes mellitus, 4 due to primary non-functioning grafts or surgical complications requiring graft nephrectomy and 10 due to patient death or graft loss (4/10 had PTDM). As a result, 119 renal transplant recipients were included in our study. The baseline demographic and clinical variables were depicted in Table 2. The median follow-up duration after kidney transplant was 62 (15–120) months. The mean age at transplantation was 39 ± 11 years, and 54.6% were male patients. All enrolled patients did not have past history of gestational diabetes mellitus, and none of them were hepatitis C carrier. All the patients were on prednisolone 7.5 mg daily. None of them were on thiazide diuretics.


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  		Table 2 Baseline demographic and clinical variables

 
Of the 119 patients, 22 patients were classified as PTDM and 66 patients were normal based on fasting blood glucose level alone. The remaining 31 patients fulfilled our criteria of OGTT (fasting blood glucose level between 5.6 and 6.9 mmol/L for at least two occasions 6 months after transplantation). Based on the results from OGTT, 4/31 (12.9%) patients were diagnosed IFG, 8/31 (25.8%) patients were diagnosed IGT, 4/31 (12.9%) patients were diagnosed PTDM and 15/31 (48.4%) patients were normal.

As a result, total 26 patients were classified as PTDM. Among them, 7 patients were treated with diet only and 19 patients required medications. For patients requiring medical treatment, 13 patients required oral hypoglycaemic agents alone while 6 required insulin therapy.

The prevalence of PTDM, IGT and IFG in our study was 21.8 (26/119)%, 6.7 (8/119)% and 3.4 (4/119)%, respectively. Thus the overall prevalence of AGM was 31.9%.

Table 3 showed the factors associated with the development of AGM by univariate analysis. Age (P = 0.003), body mass index (P = 0.032), hepatitis B seropositivity status (P = 0.01), CMV infection (P = 0.02) and acute rejection (P = 0.002) were all associated with the development of AGM. The follow-up duration after transplantation was significantly longer in the patients with AGM than the normal patients. Using multivariate analysis, only older age at transplant (OR 1.09), history of acute rejection (OR 3.40) and hepatitis B seropositivity (OR 3.13) were associated with the development of AGM (Table 4).


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  		Table 3 Comparison between patients who developed AGM and normal

 

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  		Table 4 Factors predicting development of AGM according to multivariate analysis

 
The types of acute rejection were shown in Table 5. All patients with acute rejection were given 500 mg methylprednisolone intravenously for 3 days. For the 16 patients in the AGM group, 5 developed AGM before episodes of acute rejection. The median time for the development of AGM after acute rejection in the remaining 11 patients was 49 (1–104) months.


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  		Table 5 Types of acute rejection according to Banff 1997 classification [30]

 
For patients who were finally classified as AGM (n = 38), there was no significant difference between those sorted out before OGTT (n = 22) and those diagnosed during OGTT (n = 16) (Table 6). On the other hand, there was also no significant difference between the patients sorted out as normal in the beginning (n = 66) and those diagnosed as normal during OGTT (n = 15) (Table 7).


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  		Table 6 Comparison between patients who were diagnosed as AGM before and during OGTT

 

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  		Table 7 Comparison between patients classified as normal before OGTT and during OGTT

 


   Discussion
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
References
 
The incidence and prevalence of PTDM varies widely in the literature because of the lack of standard definition for the condition. Many studies used fasting blood glucose alone or need for insulin and/or oral hypoglycaemic agents for at least 30 days as definition of PTDM [16,17]. Moreover, heterogeneity between study groups on background parameters (age, ethnicity) and types and dosage of immunosuppressive regimen may also attribute to the great difference in incidence of PTDM among the literature. The International Consensus Guidelines in 2003 [6] attempted to bring consistency in the diagnosis and management of PTDM. Diagnosis was to be based on ADA and WHO criteria that included the OGTT for the diagnosis of diabetes.

The ADA guidelines in 2006 [10] highlight the increased sensitivity and specificity of the OGTT, compared to fasting glucose alone in diagnosing diabetes in the general population. Armstrong et al. have shown that the prevalence of PTDM is much higher with OGTT and fasting blood glucose alone will miss 65% of patients with diabetes in renal transplant recipients [18]. The ADA guidelines also recommend screening for pre-diabetes and diabetes in high-risk patients such as transplant recipients. Early detection of IFG and IGT is very important due to the associated increased risk of developing both PTDM and cardiovascular disease. Early diagnosis can allow early education for lifestyle modification and appropriate intensive intervention can be given to reduce different diabetic complications.

There are different criteria of defining IFG according to WHO and ADA guidelines. If ADA classification is used, more people will require OGTT and more people will be classified as IFG. The Decode study [9] assessed the impact of sensitivity and specificity of variable cutoffs for IFG. If OGTT were performed in people with a fasting glucose level between 5.6–6.9 mmol/L, 46% of the population would require an OGTT. This would identify 93% of all people with diabetes and 69% of people with IGT. On the other hand, if OGTT were performed in people with a fasting glucose between 6.1–6.9 mmol/L, only 12% of the population would require an OGTT. This would only identify 82% of all people with diabetes and 29% of people with IGT. In our study, we recruited patients for OGTT according to ADA classification. Twenty-six percent (31/119) of patients required OGTT. Among those with OGTT, 51.6% (16/31) had AGM including IFG, IGT and PTDM.

There is consistent evidence that PTDM is more common in older individuals. Cosio et al. reported that recipients >45 years old were 2.9 times more likely to become diabetic post-transplant when compared with younger recipients [19]. Our results also showed that older recipients at the time of transplant were significantly associated with the development of AGM. The odds ratio corresponding to an increase of 1 year of recipient's age was 1.09.

Calcineurin inhibitors are important factors for the development of PTDM. There is consistent evidence that tacrolimus is more diabetogenic than cyclosporine [17,20]. A meta-analysis has revealed that the odds ratio for the development of PTDM in renal transplantation with tacrolimus was 5.03 (95% confidence interval 2.04–12.36) [21]. However, the above findings were not shown in our study. This can be explained by the use of limited sampling strategy and abbreviated AUC for drug monitoring and titration, resulting in lower tacrolimus dose used in our centre [22]. Patients receiving tacrolimus experienced a delay in the restoration of glucose metabolism when compared with patients on cyclosporine. This delay could be caused by slow recovery of insulin secretion, possibly the result of high exposure to tacrolimus [23]. The target abbreviated AUC0–12 in our patients was ~ 80–100 ng x h/ml after 3 months, corresponding to a tacrolimus trough level of ~6 ng/ml [22]. Maintaining a low tacrolimus trough level may diminish the development of impaired glucose metabolism [23]. The mean age of our patients was 39 years. On the other hand, the United States Renal Data System Annual Report for 2007 showed an older recipient age. Sixty-two percent were >45 years. Our patients were young and had a low body mass index, thus counteracting the diabetogenic effect of tacrolimus and reducing the difference between tacrolimus- and cyclosporine-based therapy. However, the overall prevalence of AGM in our patients is 31.9%. All the patients were on prednisolone 7.5 mg daily during the study and they were relatively lean. The dosage of maintenance steroids might be high if expressed in milligram per body weight. This can explain the relatively high prevalence of AGM in our patients. In a recent comparative cohort study [24], 321 patients were recruited with 301 of them had OGTT 10 weeks after kidney transplantation. The incidence of PTDM and IGT/IFG was 13% and 18% respectively, which was significantly lower when compared with a historical cohort. The major explanation of this beneficial change in glucose tolerance is probably related to the lower doses of steroids used in the early post-transplantation period. They found that 1-mg increase in daily prednisolone was associated with an 11% increased risk of PTDM in the multivariate model.

There is limited evidence that PTDM is associated with at least one acute rejection episode (64% versus 27%, P <0.01) [25]. It may be related to higher cumulative corticosteroid dose for the treatment of acute rejection. Kasiske et al. have proposed that early acute rejection may explain the relationship between graft loss and onset of diabetes. Acute rejection predisposes to graft loss and tends to prompt an increase in intensity of immunosuppressive agents that in turn exacerbates the risk of PTDM [20]. In our centre, rejection episodes were treated with 500 mg methylprednisolone intravenously for 3 days and temporary increment of oral prednisolone. As a result, the cumulative dosage of steroid was much higher in patients treated with acute rejection. In fact our results also showed that acute rejection was significantly associated with the development of AGM.

Chronic hepatitis C infection is associated with an increased incidence of PTDM in liver transplantation [26]. A meta-analysis has also shown a significant relationship between anti-HCV seropositive status with the development of PTDM after renal transplantation with adjusted odds ratio 3.97 [4]. All patients in our study were hepatitis C seronegative, thus the association of AGM with HCV status could not be verified. In Hong Kong, chronic HCV infection is of minor epidemiological significance. On the other hand, chronic hepatitis B infection is endemic with a prevalence rate of 8.8% [27]. The association of hepatitis B status with PTDM in renal transplant recipients is rarely addressed in the literature. A study by Hirakauva et al. showed that there was no difference in prevalence of PTDM in patients infected with HBV in renal transplant recipients [28]. There are limited data concerning the prevalence of hepatitis B carrier in renal transplant recipients. In our study, the prevalence of hepatitis B seropositive status was 14.5%. To the best of our knowledge, this was the first published single centre observational study which revealed that hepatitis B seropositive status was a predictive factor for the development of AGM after renal transplantation, although it is only marginally significant (O.R.: 3.13, P = 0.05). In populations with a low prevalence of HBV infection, this association may not be demonstrable. In fact, hepatitis B carrier is found to be significantly associated with the development of gestational diabetes in Chinese women in Hong Kong [29]. The authors postulate that hepatitis B carrier status can aggravate pregnancy-induced hepatic insulin resistance leading to gestational diabetes. Similarly hepatitis B virus may also worsen steroid-induced insulin resistance in susceptible individuals. Further studies are necessary to evaluate the association, pathophysiological mechanisms and prognostic implications of hepatitis B status with AGM in renal transplant recipients.

A limitation in our study might be the underestimation of patients with pre-transplant diabetes mellitus. In the pre-transplant examination, the diagnosis of diabetes mellitus was based on routine fasting blood glucose only. Lack of mandatory use of OGTT might include patients with diabetes in our study and overestimate the prevalence of AGM after transplantation.

In conclusion, the prevalence of AGM including IFG, IGT and PTDM in our renal transplant recipients was 31.9%. Older patients at time of transplant, history of acute rejection and hepatitis B seropositivity status were all independent predictive factors of the development of AGM. A large-scale prospective study with longer duration of follow-up is necessary to assess whether the use of OGTT in renal transplant recipients can risk stratify each patient for the development of PTDM and cardiovascular disease.

Conflict of interest statements. None declared.



   References
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

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Received for publication: 9. 2.08
Accepted in revised form: 10. 4.08


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