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Keywords:

  • Cardiovascular risk factors;
  • diabetes mellitus;
  • morbidity;
  • mortality;
  • survival

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

An increasing proportion of kidney recipients have diabetes mellitus (DM). Herein, we assessed the impact of DM on morbidity and mortality. The study included 933 recipients of first transplants. DM was present in 212 (23%). Compared to non-diabetics (NoDM), DM were older, heavier and had more pretransplant cardiovascular (CV) disease (16% vs. 48%, p < 0.0001). DM had reduced survival (5 years, 93% vs. 70%, p < 0.0001) and higher incidence of CV events (9% vs. 37%, p < 0.0001). CV disease was the most common cause of death in DM (61%) but not in NoDM (26%). Mortality from infections was also higher in DM (p = 0.001). In NoDM, survival related to recipient age (hazard ratio (HR) = 1.07, p < 0.0001) and dialysis pretransplant HR = 2.21, p = 0.01, while in DM, survival related to dialysis (HR = 2.89, p = 0.01) and pretransplant CV disease (HR = 2.79, p = 0.007). In NoDM, the incidence of posttransplant CV events was related to traditional CV risk factors, while in DM only the pretransplant CV history related to this outcome. In conclusion, survival differs between NoDM and DM recipients quantitatively, by cause of death and by risk factors. In NoDM, survival is excellent, and the main threat to survival relates to immunosuppression. In DM, survival is inferior primarily due to CV disease generally present prior to transplantation.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

While many advances have been made in kidney transplantation over the last two decades, shortened patient survival remains an important limitation of this procedure. The survival of kidney transplant recipients is inferior to that of the general population (1,2). However, patient survival after transplantation is vastly superior to that of patients who remain on dialysis (3). Consequently, it can be stated that kidney transplantation has achieved the landmark of being the best form of therapy for patients with end-stage kidney disease. Still, improving the survival of transplant patients, aiming to approach that of the general population, is an important clinical goal. Achieving this goal is becoming more challenging as the population of patients with chronic kidney disease becomes older and the proportion of patients with diabetes mellitus (DM) increases (4). In particular, compared to patients without DM, recipients with DM contribute disproportionately to the morbidity and mortality that may follow kidney transplantation (5).

Several studies have analyzed the factors that relate to patient survival after kidney transplantation. Those analyses generally considered the kidney recipient population as a single patient cohort despite the vast differences that exist in risk between particular patient subgroups. We postulated here that those analyses might have missed important differences in the survival characteristics of particular patient subgroups. Considering that those differences may have important clinical implications in this study, we analyzed the survival of kidney transplant recipients with and without DM separately. In particular, we assessed patient survival, causes of death and risk variables associated with patient survival, focusing on factors present pretransplant and/or during the first few weeks posttransplant. Our intent was to explore variables that might be useful clinically for selecting patients with lower posttransplant risk, and perhaps to uncover new therapeutic targets. The results of these analyses emphasize the quantitative differences in survival between recipients without and with DM. In addition, these results show significant differences in causes of death and also in the risk variables that relate to survival of non-diabetics (NoDM) and DM recipients. These results can be interpreted as both encouraging and discouraging, regarding the outcomes of kidney transplantation. Thus, the majority of kidney transplant recipients, who do not have DM, have excellent survival and relatively low cardiovascular (CV) risk. In these patients, immunosuppression-related complications are the main threats to survival. In contrast, the survival of recipients with DM is significantly lower, particularly, due to higher CV risk.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Patient population

The study cohort included all adults, recipient of first kidney transplants done at the Mayo Clinic, Rochester, Minnesota from January 1998 to June 2006. Recipients of pancreas or other transplants were excluded. Clinical and laboratory information was obtained from Mayo Clinic electronic data bases. The retrieval of that information and the publication of these results were approved by the institution's review committee. The characteristics of the study cohort are displayed in Table 1. The diagnosis of DM was based on review of pretransplant medical records. All recipients with DM were receiving hypoglycemic agents prior to the transplant, and 75% of them were receiving insulin. Glycosylated hemoglobin levels are not routinely monitored in our program; thus, these data could not be analyzed in this study.

Table 1.  Characteristics of the study population
Patient characteristicsAll patientsNoDMDM
  1. 1Percentage of patient who did not receive dialysis pretransplant; 2p < 0.0001 t-test; 3p < 0.0001 (chi-square); 4p = 0.001 t-test; 5values represent mean ± SD (median, range).

Number of patients933721212 (23%)
Recipient age53 ± 14.451 ± 14.960 ± 9.92
Recipient sex (males)  57%  58%  54%
Recipient race (Caucasians)  92%  92%  94%
Preemptive transplants1  40%  41%  38%
Months on dialysis pretransplant13.8 ± 24 (3.02, 0–230)513.7 ± 24 (2.43, 0–285)514.1 ± 23.1 (5.38, 0–230)5
BMI at transplant27.7 ± 5.827 ± 5.630.7 ± 5.82
Obese (BMI > 30)  32%  26% 55%3
Smoking (at transplant)13.3%14.2%10.4% 
Pretransplant CV events
 Any  23%15.7%47.7%3
 Cardiac  18%12.4%37.5%3
 Stroke 5.2% 3.5%11.1%3
 Peripheral vascular disease 5.3% 2.3%15.3%3
Donor type
 Living related47.6%48.3%45.3%
 Living unrelated24.3%24.7%22.9%
 Deceased donor28.1%26.9%31.8%
Follow-up months45.7 ± 2847.3 ± 28.140.4 ± 25.34

Immunosuppressive management following transplantation has been previous described in detail (6). In brief, induction was given to most patients and consisted of thymoglobulin in 70%, anti-CD25 antibodies in 14% and alemtuzumab in 1%. Sixteen percent of patients did not receive induction immunosuppression. Maintenance immunosuppression consisted of steroids (prednisone, tapering to 5 mg daily by month 3), mycophenolate mofetil 750 mg twice daily and tacrolimus in 77% of patients. Sirolimus was used instead of tacrolimus in 12% and cyclosporine in 10%. The protocol for steroid administration was identical in patients with or without DM. Data on the use of other medications, particularly potentially cardioprotective medications, such as aspirin, statins or betablockers, was unfortunately incomplete in this data set and was not analyzed in this study.

Delayed graft function was defined as the need for dialysis starting the first week posttransplant. Graft function was assessed by serial serum creatinines; estimated glomerular filtration rate (eGFR) was calculated using the modification of diet in renal disease (MDRD) equation (7). CV events before or after transplantation were classified as follows: (i) cardiac, including acute myocardial infarction and/or coronary intervention, either percutaneous (angioplasty and/or stent placement) or surgical; (ii) peripheral vascular events, including history of amputations and/or interventions in the peripheral vascular tree, either surgical or percutaneous and (iii) central nervous system, including all forms of stroke. The cause of the patient's demise was classified according to medical record documentation, if the patient expired in our institution, or by review of external death certificates when available.

Data analysis

Data are expressed as means and standard deviation throughout the manuscript. Means of normally distributed data were compared by Student's t-test or paired t-test. Data that were not normally distributed were compared by nonparametric tests. Chi-square test was used to compare proportions. The relationships between pre- and posttransplant variables and survival were analyzed by univariate and multivariate Cox's analysis. Two survival endpoints were analyzed separately: (i) patient survival (all causes of death) and (ii) CV endpoint, including nonfatal (see list above) and fatal posttransplant CV events. For both of these analyses, survival was censored for graft loss. Survival analyses were done by univariate and multivariate Cox's analyses and Kaplan–Meier plots. Causes of death were determined by review of Mayo Clinic medical records and by request of death certificates in patients in whom the cause of death could not be determined from our records. To assess the relationship between time on dialysis prior to the transplant and patient survival, patients were divided into the following groups: no dialysis, dialysis from 3 to 12 months and dialysis for more than 12 months. This division was based upon the finding that the survival of patients dialyzed briefly (less than 3 months) did not differ from that of patients who never received dialysis.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Patient characteristics

Table 1 displays these data for the entire population and separately for patients with or without DM. As can be seen, 212 of the 933 recipients (23%) had DM. The age at diagnosis of DM was 42 ± 14 years with a median of 44 years and a range between 4 and 69 years. Sixteen patients (7.5%) had DM diagnosed prior to age 18. The number of years of DM prior to the transplant was 18 ± 9 years, with median of 19 years and range of 1–53 years. In NoDM, the cause of kidney failure included: glomerular diseases (39%), polycystic kidney disease (18%), hypertension/vascular disease (15%), other (19%) and unknown (9%).

Compared to NoDM (Table 1), DM were significantly older and heavier. In addition, DM had higher incidence of CV events prior to the transplant, including cardiac, peripheral vascular disease and stroke. It should be noted that the patient follow-up period for DM was significantly shorter than that for NoDM (Table 1). This was not due to differences in the dates of transplantation but rather due to higher mortality posttransplant in DM.

Posttransplant endpoints in DM and NoDM

Death-censored graft survival was not different between patients with or without DM (hazard ratio [HR] 1.19 [0.76–1.86], p = 0.442) (Table 2). In contrast, compared to NoDM, DM had a significantly higher incidence of posttransplant CV events, death from CV causes and all-cause mortality. Figure 1 displays patient survival (left side) and the cumulative incidence of posttransplant CV events (right side). As can be seen, compared to NoDM, DM had significantly reduced survival and a significantly higher incidence of fatal and nonfatal CV events posttransplant. A significantly higher percentage of DM (4.4%) than that of NoDM (0.5%) expired during the first 3 months posttransplant (p < 0.0001). Thereafter, approximately 1% of NoDM and 6% of DM expired yearly. Similarly, CV events were significantly more common during the first 3 months posttransplant in DM than in NoDM. Thereafter, a relatively constant percentage of recipients had CV events yearly, but the rate was significantly higher in DM than that in NoDM.

Table 2.  Posttransplant endpoints achieved in the entire cohort and in subgroups of patients with NoDM or with DM
EndpointsAll patientsNoDMDM
  1. 1Values represent number of patients and percentages of all patients; 2for this tabulation, each patient was counted once even if he/she had more than one CV event; 3p < 0.0001; 4p = 0.015 by chi-square.

Number of patients933721212
Graft losses censored at death 107 (11.5%)1 82 (11.4%) 25 (11.8%)
Posttransplant CV events:
 Any2106 (11.4%)53 (7.4%)53 (25%)3
 Cardiac58 (6.2%)34 (4.7%)  24 (11.4%)3
 Stroke17 (1.8%) 9 (1.3%) 8 (3.8%)4
 Peripheral vascular disease40 (4.3%)19 (2.6%)  21 (10.0%)3
CV mortality33 (3.6%) 8 (1.1%)25 (12%)3
All-cause mortality85 (9.1%)44 (6.1%)  41 (19.3%)3
image

Figure 1. Left: Kaplan–Meier plots of patient survival after transplantation in recipients without DM (—) and those with DM (……) (log-rank, p < 0.0001). Right: Kaplan–Meier plots of the incidence of fatal and nonfatal posttransplant CV events in recipients without DM (—) and those with DM (……) (log-rank, p < 0.0001).

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Information about specific causes of death was available in 84% of patients. The distribution of causes of death was significantly different in DM and NoDM (p = 0.009) (Figure 2A). Thus, in recipients with DM, the most common cause of death was cardiac, accounting for 48% of all deaths or 61% of deaths with known cause (Figure 2B). In contrast, in recipients without DM, CV deaths accounted for 18% of all deaths and 26% of all deaths with known cause. Compared to NoDM, DM had a significantly higher cumulative mortality due to cardiac causes (log-rank, p < 0.0001), infectious causes (p = 0.001) and deaths without attributable cause (p = 0.008). In contrast, there were no significant differences between DM and NoDM in deaths due to malignancy (p = 0.122) or ‘other’ causes (p = 0.703). The groups of ‘other’ causes of death include: trauma, respiratory failure, liver failure, bowel perforation/peritonitis, and two patients with declining graft function who refused dialysis.

image

Figure 2. (A) Distribution of causes of death in NoDM (black bars) and DM (stripped bars) recipients. (B) Distribution of known causes of death in NoDM (left) and DM (right) recipients.

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Variables related to patient survival

In NoDM, by univariate analysis, reduced patient survival (all causes of death) related to older age (HR 1.07 [1.04–1.1] per year of age, p < 0.0001), use of dialysis (HR 2.25 [1.20–4.21], p = 0.01), delayed graft function (HR 3.67 [1.78–7.48], p < 0.0001) and lower graft function 3 weeks posttransplant (HR 0.96 [0.94–0.98], p = 0.001). Lower hemoglobin concentrations 3 weeks posttransplant also related marginally to survival (p = 0.06). Of interest, pretransplant CV disease did not relate significantly with survival in NoDM (p = 0.663). In contrast to these findings, in DM recipients, reduced survival related to: the use of dialysis (HR 2.67 [1.15–4.46], p = 0.018), history of pretransplant CV disease (HR 2.84 [1.5–5.5], p = 0.002), delayed graft function (HR 2.81 [1.39–5.67], p = 0.004) and the use of deceased donor kidneys (HR 1.48 [1.08–2.03], p = 0.013). Survival of the DM recipient was also reduced in patients with longer history of DM, although that relationship was marginally significant (p = 0.05). Age was not a significant correlate of DM survival (p = 0.293). Additional variables tested and found not significantly related to patient survival in either NoDM or DM included: donor and recipient sex or race, donor type, smoking, body mass index (BMI), induction or maintenance immunosuppression and acute rejection. The use of insulin pretransplant did not relate to DM survival.

Results of the multivariate analysis are shown in Table 3. In NoDM, older age and delayed graft function were independent correlates of patient survival. In contrast, in DM, the use of dialysis pretransplant, history of pretransplant CV disease and delayed graft function were independent correlates of survival.

Table 3.  Multivariate analysis of variables related to patient survival after kidney transplantation. Analysis was done separately in recipient without DM or with DM prior to the transplant
VariablesNoDMDM
HR (CI)1pHR (CI)1p
  1. 1Hazards ratio (HR) and confidence interval (CI); 2HR calculated per year of age; 3parameter not included in the model.

Recipient age21.07 (1.04–1.10)<0.00013 
Dialysis 0.3592.34 (1.01–5.48)0.05
Pretransplant CV disease3 2.79 (1.31–5.91) 0.017
Delayed graft function3.38 (1.60–7.16)0.0012.13 (1.02–4.46) 0.043

The relationship between pretransplant dialysis and survival related to both time on dialysis and DM status. In NoDM, when compared to patients who never received dialysis, the hazard associated with dialysis was not significantly increased if the patient was on dialysis for less than 1 year (HR 2.06 [0.85–4.97], p = 0.108). However, after 1 year on dialysis, posttransplant survival was significantly reduced (HR 2.84 [1.4–5.7], p = 0.004). In contrast, in DM, compared to patients who never received dialysis, recipient survival was significantly reduced in patients who received dialysis for less than 1 year (HR 3.31 [1.23–8.87], p = 0.017) and for more than 1 year (HR 3.00 [1.28–7.03], p = 0.011).

We next assessed whether the reduced survival of DM compared to NoDM could be explained by pretransplant CV disease (Figure 3). Compared to NoDM, DM survival was reduced whether the recipient had or did not have a history of CV disease. However, differences in survival were particularly striking among patients with CV disease pretransplant.

image

Figure 3. Kaplan-Meier plots of patient survival in NoDM (—) and DM (……). Left: patient without CV disease prior to the transplant (log-rank, p = 0.011). Right: patients with CV disease prior to the transplant (log-rank, p < 0.0001).

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Variables related to posttransplant CV events

In NoDM, by univariate analysis, an increased CV risk related to traditional CV risk factors, including: (i) older age (HR 1.05 [1.03–1.07], p < 0.0001), (ii) male sex (0.56 [0.32–0.95], p = 0.032), (iii) smoking (2.67 [1.48–4.79], p = 0.001), (iv) low high-density lipoprotein (HDL) cholesterol pretransplant (0.98 [0.96–0.99], p = 0.024), (v) history of hypertension (2.70 [1.4–5.2], p = 0.003), (vi) history of pretransplant CV events (3.07 [1.82–5.17], p = 0001). In addition, certain transplant-related variables also related significantly with posttransplant CV events in NoDM, including: (vii) lower graft function after the transplant (0.97 [0.95–0.99], p = 0.010), (viii) delayed graft function (2.03 [1.01–4.08], p = 0.043) and (ix) deceased donor kidney (1.36 [1.05–1.76], p = 0.017). In contrast, in DM, the variables related to CV risk posttransplant included: (i) history of pretransplant CV disease (2.75 [1.65–4.56], p < 0.0001), (ii) positive cardiac stress test for ischemia (2.73 [1.50–4.99], p = 0.001) and (iii) years of DM (1.03 [1.00–1.05], p = 0.016). Of interest, traditional CV risk factors (listed above) did not relate to CV risk in DM recipients. Additional variables not significantly related to posttransplant CV disease in either NoDM or DM included: BMI, pretransplant dialysis, cholesterol (total and low-density lipoprotein [LDL]) or triglycerides pretransplant, type of immunosuppression, donor demographic characteristics, acute rejection, hemoglobin level 3 weeks posttransplant or insulin use in DM.

Table 4 displays multivariate analyses of factors related to posttransplant CV events. In NoDM, traditional CV risk factors were independent covariates of this endpoint. In contrast, in DM, pretransplant CV disease was the only factor related to posttransplant CV events, and none of the traditional CV risk factors related significantly to this outcome. Pretransplant CV disease relates to risk of posttransplant CV events. However, as shown in Figure 4, the magnitude of the risk was significantly higher in DM than that in NoDM.

Table 4.  Multivariate analysis of factors related to fatal and nonfatal posttransplant CV events in NoDM and in DM recipients
VariablesNoDMDM
HR (CI)1pHR (CI)1p
  1. 1Hazard ratio (HR) and confidence interval (CI); 2parameter not included in the model.

Recipient age1.07 (1.04–1.10)<0.00012 
Smoking3.65 (1.86–7.14)<0.00012 
Years of DM2 1.03 (1.00–1.05)0.169
Hypertension pretransplant2.08 (0.93–4.65)0.0742 
HDL pretransplant0.98 (0.96–0.99)0.0172 
Pretransplant CV disease 0.1912.75 (1.65–4.56)<0.0001
image

Figure 4. Relationship between pretransplant and posttransplant CV disease in NoDM (left panel) and in DM (right panel). Left: NoDM recipients without (—) or with (– –) pretransplant CV disease (log-rank, p < 0.0001). Right: DM recipients without (········) or with (– –) pretransplant CV disease (log-rank, p < 0.0001).

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

These results confirm and expand our knowledge on the impact of DM on the outcomes of kidney transplantation, and also clarify some of the current results of this treatment modality. Compared to NoDM, recipients with DM had significantly increased risk of posttransplant CV events (7% vs. 25%), all-cause mortality (6% vs. 19%) and CV mortality (1% vs. 12%). Regarding the latter parameter, it is frequently stated that the most common cause of death following kidney transplantation is CV, accounting for approximately 45% of all fatalities. This analysis clarified that this statistic represents an average outcome for several patient subgroups, including two with very different results: recipients without DM in whom CV disease accounts for 26% of deaths, and recipients with DM in whom 61% of deaths are due to CV disease. It is notable that in NoDM, a high percentage of deaths are due to immunosuppression-related events (38% of deaths due to infections and malignancies). Similar observations were made in a study assessing the prognosis of older (>65 years) transplant recipients in whom 53% of deaths are due to infection and malignancies (8).

The majority of the recipients with DM, in this study, had the phenotypic characteristics of type 2 DM (see Table 2), although the lack of C peptide levels does not allow us to confirm this diagnosis. Considering the differences in causes of death between DM and NoDM, it is not surprising that the variables related to patient survival are also different in these two groups of patients. Among these differences, it is perhaps most striking to note the impact of pretransplant CV disease on posttransplant outcomes. In NoDM, this variable did not relate statistically to survival likely because death in these patients is most often due to non-CV causes. In contrast, in DM, pretransplant CV disease is the strongest covariate of survival and posttransplant CV events. In DM, pretransplant CV disease is not only more common than in NoDM, but it has a greatly magnified negative impact on posttransplant morbidity and mortality. These results are consistent with previous studies showing that the variable ‘diabetes’ has a significantly greater negative statistical ‘impact’ on the survival of kidney transplant recipients than that in the general population (9). These authors suggested, reasonably, that this result might be due to the longer exposure to the diabetic milieu in transplant recipients than that in individuals from the general population who presumably have not developed kidney disease yet. However, we should also consider the possibility that DM/hyperglycemia may have particularly deleterious effects on the survival of transplant recipients and/or generally in patients with kidney disease. Several observations support this hypothesis. Thus, levels of glycosylated hemoglobin relate significantly with the survival of patients with chronic kidney disease but without DM (10). Furthermore, when DM develops de novo after transplantation, it relates to increased CV risk despite its short duration (11). Finally, it is of interest that some studies noted that in DM, patient survival after kidney transplantation relates to glucose control (12). A corollary to these observations is that possibly, as in the general population, tight glucose control may be effective in reducing CV risk and mortality in DM kidney transplant recipients.

These analyses confirmed previous studies showing a strong association between the use of dialysis pretransplant and survival posttransplant (13,14). Furthermore, these results showed that compared to NoDM, the impact of dialysis on survival is of greater magnitude in DM, where periods of dialysis of less than 1 year are associated with reduced posttransplant survival. This observation is in agreement with previous studies (15). The cause for this association is not clear, but these studies and others do not support the notion that the effect of dialysis is due to an increased risk of posttransplant CV disease (13). Contributing to the less favorable outcome of transplantation in DM are the observation made here that, compared to NoDM, DM have a higher risk of infectious-related and ‘other’ causes of death. The latter includes multiple causes that cannot be easily classified into a single category. In these analyses, we focused on risk factors identifiable pretransplant or during the first month posttransplant. These results clearly showed that in high-risk patients delayed graft function is a significant and independent survival risk.

In agreement with previous studies (5,9), posttransplant CV outcomes in NoDM relate principally to traditional CV risk factors, including: older age, smoking, low HDL cholesterol levels and hypertension. In contrast, these relationships are not present in DM, where only the presence of pretransplant CV relate to posttransplant CV risk. This result should not lead to the conclusion that traditional CV risk factors are not relevant to DM recipients or to the notion that in these recipients the CV risk is irreversible. In fact, these patients' survival greatly improves after kidney transplantation compared to remaining on dialysis (3,15,16). In addition, other studies showed previously that graft function and modification of CV risk factors, such as lowering LDL cholesterol, successfully reduces CV risk posttransplant (17,18).

These analyses were conducted in a population of transplant recipients who have several salient features, including: a high proportion of living donor transplants, a high percentage of preemptive transplants and a high proportion of Caucasian recipients. These characteristics are, in part, a reflection of the demographics of our region, but are also indicative of this program's strong belief on the benefits of living donation and preemptive transplantation. The results in these studies should be taken in the context of the population studied, and whether these results apply to other populations with differing characteristics needs to be evaluated.

These results strongly support the current focus of the transplant community in investigating and treating CV disease in kidney transplant recipients. However, these analyses also suggest the following considerations: improving posttransplant survival will require a reduction in immunosuppression-related complications, particularly in NoDM recipients. These results also suggest that in NoDM recipients, treating CV risk factors would likely be particularly effective in reducing risk (18). In patients with DM, it is clear that current protocols to prevent the development of CV disease pretransplant, to identify patients at risk and to treat CV disease are at best partially effective. Current approaches to the management of the patient with DM and chronic kidney disease needs to be reevaluated.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

This work was supported by grants from the Mayo Clinic Transplant Center and from the Division of Nephrology and Hypertension. We thank the kidney-pancreas transplant coordinators for their dedication to the care of transplant recipients and their help in the collection of data from these patients. We also thank Ms. Cynthia Handberg for her excellent secretarial assistance. Data presented in part at the American Society of Transplantation meeting, San Francisco, May 2007.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
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