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Volume: 17 Issue: 5 October 2019


Elevated Donor Hemoglobin A1C Impairs Kidney Graft Survival From Deceased Donors With Diabetes Mellitus: A National Analysis

Objectives: Kidney transplant is the optimal therapy for patients with end-stage renal disease. The presence of donor diabetes mellitus is a recognized risk factor for impaired kidney graft survival and is incorporated into the Kidney Donor Profile Index. At present, however, there are limited assessments of the severity of this risk factor. Hemoglobin A1c reflects glycemic control over the preceding 3 months, and we hypothesized that donor hemoglobin A1c levels could confer additional discriminatory power in assessments of deceased donors with diabetes mellitus.

Materials and Methods: The United Network for Organ Sharing/Organ Procurement and Organ Transplantation Network Standard Transplant Analysis Research file was queried for adult deceased-donor kidney transplants performed using allografts from donors with diabetes mellitus who had measurements of hemoglobin A1c before donation.

Results: The study cohort consisted of 1518 kidney transplants performed using allografts from deceased donors with diabetes mellitus. Kaplan-Meier survival analysis and log-rank test were performed to compare survival of grafts from donors with diabetes mellitus with elevated (≥ 6.5%) versus lower (< 6.5%) hemoglobin A1c levels. Graft survival at 5 years was significantly lower for recipients of donors with hemoglobin A1c ≥ 6.5% (58.9% vs 68.3%; P < .001). On multivariate analysis, hemoglobin A1c ≥ 6.5% was an independent predictor of diminished graft survival.

Conclusions: Hemoglobin A1c has potential as an additional discriminatory test for estimating outcomes of grafts from donors with diabetes mellitus and should be routinely measured in this population.

Key words : Diabetes mellitus, End-stage renal disease, Extended-criteria donor, Long-term survival, Renal transplant


Kidney transplant is the optimal therapy for patients with end-stage renal disease. The survival benefit of kidney transplant over dialysis has been demonstrated in multiple recipient populations.1-8 Although out-comes of kidney transplant are excellent in the current era, the ongoing organ shortage has limited the availability of this therapy.9,10 Due to the growth of the wait list and concomitant wait list mortality, there has been a focus on increasing the utilization of kidneys from nonideal deceased donors, such as expanded-criteria donors and donors with diabetes mellitus (DM).11,12

To safely utilize nonideal donor organs, continued refinement of risk stratification is needed. The Kidney Donor Profile Index (KDPI) was introduced in 2014 and represents an assessment of allograft quality that incorporates several validated donor factors, including age, height, weight, race/ethnicity, history of hyper-tension and diabetes, cause of death, serum creatinine level, hepatitis C status, and donation after circulatory death.13 Lower KDPI scores are associated with increased donor quality and greater graft survival. In the current allocation system, candidates with longer estimated post-transplant longevity receive priority for kidneys from lower KDPI donors.

Despite growing recognition that transplant of nonideal grafts confers a substantial survival benefit compared with remaining on dialysis, the number of deceased-donor kidney transplants performed annually in the United States has remained relatively stagnant over the past decade at around 12 000 transplants per year.1,10,14 In the context of a growing wait list, the increased utilization of nonideal deceased-donor organs appears necessary to combat the organ shortage. Given the ongoing rise of DM in the general population, refining selection criteria for donors with DM is an important issue in kidney transplantation.

Donor DM is a well-described risk factor for impaired graft survival after kidney transplant and is thus incorporated in the KDPI.13,15,16 At present, however, assessment of its severity has been limited. The only existing metric is duration of DM, and this parameter is frequently not recorded in donors. We hypothesized that a more sensitive indicator of glycemic control may improve risk stratification and prognostication of graft survival. Glycated hemo-globin (HbA1c) reflects glycemic control over the previous 3 months and has become a cornerstone for both establishing the diagnosis of DM and moni-toring its longitudinal management.17 The American Diabetes Association considers HbA1c levels ≥ 6.5% as diagnostic for DM. At present, HbA1c is not routinely measured in all deceased donors and varies by organ procurement organization. In this analysis, we sought to investigate whether donor HbA1c may confer additional discriminatory power in assess-ments of kidney grafts from donors with DM.

Materials and Methods

Patient selection
The Duke University Institutional Review Board granted exempt status for this retrospective analysis of the United Network for Organ Sharing/Organ Procurement and Organ Transplantation Network (UNOS/OPTN) Standard Transplant Analysis Research (STAR) file. The data set was queried for adults undergoing isolated kidney transplant. Donor HbA1c data were only available for transplants that occurred during or after 2010. Levels of HbA1c were reported as a percentage of total glycated hemo-globin molecules in donor blood. This measurement typically occurs during the donor evaluation period, which precedes organ retrieval by a few days, although the exact time interval was not available. Exclusion criteria were missing donor HbA1c levels and/or missing survival data of recipients.

Statistical analyses
Continuous and categorical variables were compared using the rank-sum test and the Fisher exact test, respectively. Graft survival (from date of transplant to date of graft failure or death from any cause) and recipient survival were estimated using the Kaplan-Meier method. The log-rank test was used to determine statistical significance. Secondary endpoints included hospital length of stay and incidence of delayed graft function (need for dialysis within the first week posttransplant). We then performed Cox proportional hazard modeling to assess the effects of several donor and recipient variables, including donor HbA1c, on the risk of posttransplant graft failure. Univariable analyses were conducted. All variables with a P value < .10 on univariable analysis were then incorporated into a multivariable Cox proportional hazards model to assess effect on graft survival. Hazard ratios and 95% confidence intervals were computed to estimate strength and precision of associations. Finally, we performed a restricted cubic spline analysis to assess the risk of graft loss as a function of donor HbA1c, in continuous fashion. Statistical analyses were performed using R software.18


The final study population consisted of 1518 kidney transplants performed with grafts from deceased donors with DM and available HbA1c data (Figure 1). The median follow-up of the entire cohort was 36.5 months. The cohort was divided into 2 groups based on donor HbA1c, using a value of 6.5% as the breakpoint (elevated was defined as levels ≥ 6.5%).

Donor characteristics
Donor variables are displayed in Table 1. There were relatively minor differences between groups with regard to donor age, ethnicity, and KDPI. There was a greater proportion of male donors in the group with elevated HbA1c. There were no differences between groups with regard to donor body mass index (BMI), hypertension, smoking history, or terminal creatinine.

Recipient characteristics
Recipient variables are displayed in Table 2. There were relatively minor differences with regard to recipient age and BMI. There were no differences between groups with regard to recipient sex, ethnicity, DM status, medical condition, or time on wait list.

Transplant characteristics
Transplant-related variables are displayed in Table 3. There were no differences between groups with regard to cold ischemic time or degree of HLA mismatch.

Graft and recipient survival
The Kaplan-Meier plot for graft survival, stratified by donor HbA1c status, is shown in Figure 2. Graft survival was significantly diminished for DM donors with HbA1 ≥ 6.5% compared with DM donors with HbA1c < 6.5% (P < .001, log-rank test). The 1-year survival of grafts from donors with HbA1c ≥ 6.5% was 89.7% versus 92.9% for those from donors with HbA1c < 6.5%. The 5-year survival of grafts from donors with HbA1c ≥ 6.5% was 58.9% versus 68.3% for those from donors with HbA1c < 6.5%.

The Kaplan-Meier plot for patient survival, stratified by donor HbA1c status, is displayed in Figure 3. Patient survival was significantly diminished for transplants performed using grafts from DM donors with HbA1c ≥ 6.5% compared with DM donors with HbA1c < 6.5% (P = .02, log-rank test). The 1-year survival of patients with grafts from donors with HbA1c ≥ 6.5% was 95.9% versus 96.3% for patients with grafts from donors with HbA1c < 6.5%. The 5-year survival of patients with donor HbA1c ≥ 6.5% was 70.1% versus 76.0% for patients with donor HbA1c < 6.5%.

Risk factors for graft loss
Cox proportional hazards models were used to assess risk factors for graft loss. First, univariable analysis was performed for the following variables: donor HbA1c, KDPI, donor sex, donor BMI, recipient age, recipient BMI, recipient time on wait list, recipient DM status, recipient ethnicity, recipient medical condition (hospitalized vs home), cold ischemia time, and degree of HLA mismatch. Variables with P < .10 on univariable analysis (donor HbA1c, KDPI, recipient age, and cold ischemic time) were then incorporated into a multivariable model (Table 4). The multivariable model demonstrated that donor HbA1c ≥ 6.5% (hazard ratio [HR] of 1.4; P = .004), KDPI (HR of 2.82; P = .001), recipient age (HR of 1.02; P < .001), and cold ischemic time (HR of 1.01; P = .04) were all independent predictors of graft loss.

The restricted cubic spline analysis depicts hazard ratios for graft loss as a function of donor HbA1c in continuous fashion (Figure 4). We observed a nearly linear increase in risk of graft loss with increasing HbA1c, up to a value of 10.0%. Thereafter, the curve appears to plateau, but this is likely limited by the relatively few observations with donor HbA1c above this level.

Secondary outcomes
Length of stay and incidence of delayed graft function are displayed in Table 5. There were no differences in these parameters between groups.


Given the ongoing organ shortage and growing kidney transplant wait list, greater consideration of utilizing nonideal donor kidneys is warranted. As the prevalence of DM increases in the donor population, an improved understanding of how to best utilize kidneys from this population will be of importance. Mohan and colleagues previously demonstrated that kidneys from donors with diabetes had superior graft survival compared with expanded-criteria donor kidneys.19 In a more recent analysis, Cohen and colleagues demonstrated a survival benefit for patients who received kidneys from DM donors compared with remaining on dialysis, particularly for those patients listed at centers with long average wait times.20 Ongoing refinement of selection criteria for DM donors is necessary to optimize donor-recipient matching and provide accurate estimation of the risk-benefit profile. Although KDPI does account for the presence of donor DM, at present there have been limited assessments of its severity. In this analysis, we hypothesized that donor HbA1c may provide additional utility in assessing the impact of donor DM.

Using clinical data from the UNOS/OPTN STAR registry, we demonstrated that, among deceased donors with DM, those with an elevated HbA1c ≥ 6.5% yielded inferior kidney graft survival. Furthermore, on multivariable analysis, elevated donor HbA1c was an independent predictor of graft loss. As utilization of kidneys from DM donors increases, HbA1c may help provide a more comprehensive picture of donor glycemic control. Given the findings of our study and the relatively low cost of the test ($30 to $50 retail price), we propose that HbA1c should be routinely measured and reported for all deceased donors with DM. One important caveat is that the measurement of HbA1c for every donor could increase the discard rate of kidneys from DM donors. In our opinion, rather than using it as criteria for discard, the finding of elevated donor HbA1c could be used in improved matching of grafts with recipients with a lower estimated posttransplant survival.

There are some important limitations of our analyses that must be noted. The chief among these is that donor HbA1c is an optionally recorded variable in the STAR dataset; practice patterns with regard to measurement of HbA1c during donor evaluation differ by organ procurement organization. In Table 6, we compare donor, recipient, and trans-plant variables for cases with and without available donor HbA1c data. Although significant differences are shown in some donor and recipient factors due to the large size of the cohorts, in our estimation most of these differences are not clinically significant (for example, KDPI of 0.46 vs 0.45). However, we acknowledge this limitation related to study design. Furthermore, we do not know at which time point HbA1c was measured during the donor evaluation or how this measurement may have been affected by blood transfusions received by the donor. Most donors (71.1%) did not receive any red blood cell transfusions, supporting the validity of the HbA1c results used in our analysis. Finally, we do not know how donor HbA1c was used, if at all, by transplant centers to make decisions regarding either organ acceptance or donor-recipient matching; thus, we acknowledge the potential presence of unmeasured bias related to this.

In conclusion, donor HbA1c appears to provide additional discriminatory power in risk stratification of kidneys from DM donors. Among donors with a known clinical history of DM, elevated HbA1c appears to be associated with diminished graft survival. We suggest that HbA1c should be routinely tested in this population, given its low cost and potential utility. Consideration could be made for incorporating HbA1c into the KDPI if the trends demonstrated in this study can be validated in a larger cohort.


  1. Schold JD, Segev DL. Increasing the pool of deceased donor organs for kidney transplantation. Nat Rev Nephrol. 2012;8(6):325-331.
    CrossRef - PubMed
  2. Ojo AO, Hanson JA, Meier-Kriesche H, et al. Survival in recipients of marginal cadaveric donor kidneys compared with other recipients and wait-listed transplant candidates. J Am Soc Nephrol. 2001;12(3):589-597.
  3. Wolfe RA, Ashby VB, Milford EL, et al. Comparison of mortality in all patients on dialysis, patients on dialysis awaiting transplantation, and recipients of a first cadaveric transplant. N Engl J Med. 1999;341(23):1725-1730.
    CrossRef - PubMed
  4. Gaylin DS, Held PJ, Port FK, et al. The impact of comorbid and sociodemographic factors on access to renal transplantation. JAMA. 1993;269(5):603-608.
    CrossRef - PubMed
  5. Glanton CW, Kao TC, Cruess D, Agodoa LY, Abbott KC. Impact of renal transplantation on survival in end-stage renal disease patients with elevated body mass index. Kidney Int. 2003;63(2):647-653.
    CrossRef - PubMed
  6. McDonald SP, Russ GR. Survival of recipients of cadaveric kidney transplants compared with those receiving dialysis treatment in Australia and New Zealand, 1991-2001. Nephrol Dial Transplant. 2002;17(12):2212-2219.
    CrossRef - PubMed
  7. Meier-Kriesche H, Port FK, Ojo AO, et al. Deleterious effect of waiting time on renal transplant outcome. Transplant Proc. 2001;33(1-2):1204-1206.
    CrossRef - PubMed
  8. Oniscu GC, Brown H, Forsythe JL. How great is the survival advantage of transplantation over dialysis in elderly patients? Nephrol Dial Transplant. 2004;19(4):945-951.
    CrossRef - PubMed
  9. Matas AJ, Smith JM, Skeans MA, et al. OPTN/SRTR 2013 Annual Data Report: kidney. Am J Transplant. 2015;15 Suppl 2:1-34.
    CrossRef - PubMed
  10. Hart A, Smith JM, Skeans MA, et al. OPTN/SRTR 2015 Annual Data Report: Kidney. Am J Transplant. 2017;17 Suppl 1:21-116.
    CrossRef - PubMed
  11. Cohen JB, Bloom RD, Reese PP, Porrett PM, Forde KA, Sawinski DL. National outcomes of kidney transplantation from deceased diabetic donors. Kidney Int. 2016;89(3):636-647.
    CrossRef - PubMed
  12. Rege A, Irish B, Castleberry A, et al. Trends in usage and outcomes for expanded criteria donor kidney transplantation in the United States characterized by kidney donor profile index. Cureus. 2016;8(11):e887.
    CrossRef - PubMed
  13. Rao PS, Schaubel DE, Guidinger MK, et al. A comprehensive risk quantification score for deceased donor kidneys: the kidney donor risk index. Transplantation. 2009;88(2):231-236.
    CrossRef - PubMed
  14. Ojo AO, Morales JM, Gonzalez-Molina M, et al. Comparison of the long-term outcomes of kidney transplantation: USA versus Spain. Nephrol Dial Transplant. 2013;28(1):213-220.
    CrossRef - PubMed
  15. Port FK, Bragg-Gresham JL, Metzger RA, et al. Donor characteristics associated with reduced graft survival: an approach to expanding the pool of kidney donors. Transplantation. 2002;74(9):1281-1286.
    CrossRef - PubMed
  16. Schold J, Srinivas TR, Sehgal AR, Meier-Kriesche HU. Half of kidney transplant candidates who are older than 60 years now placed on the waiting list will die before receiving a deceased-donor transplant. Clin J Am Soc Nephrol. 2009;4(7):1239-1245.
    CrossRef - PubMed
  17. Speeckaert M, Van Biesen W, Delanghe J, et al. Are there better alternatives than haemoglobin A1c to estimate glycaemic control in the chronic kidney disease population? Nephrol Dial Transplant. 2014;29(12):2167-2177.
    CrossRef - PubMed
  18. R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2014.

  19. Mohan S, Tanriover B, Ali N, et al. Availability, utilization and outcomes of deceased diabetic donor kidneys; analysis based on the UNOS registry. Am J Transplant. 2012;12(8):2098-2105.
    CrossRef - PubMed
  20. Cohen JB, Eddinger KC, Locke JE, Forde KA, Reese PP, Sawinski DL. Survival benefit of transplantation with a deceased diabetic donor kidney compared with remaining on the waitlist. Clin J Am Soc Nephrol. 2017;12(6):974-982.
    CrossRef - PubMed

Volume : 17
Issue : 5
Pages : 613 - 618
DOI : 10.6002/ect.2017.0322

PDF VIEW [173] KB.

From the Department of Surgery, Duke University Medical Center, Durham, North Carolina, USA
Acknowledgements: The authors have no sources of funding for this study and have no conflicts of interest to declare. This analysis was presented as an oral presentation at the 2017 American Transplant Congress in Chicago, Illinois on May 2, 2017. *V. A. Bendersky and M. S. Mulvihill contributed equally to this work.
Corresponding author: Andrew S. Barbas, Department of Surgery, Division of Abdominal Transplant Surgery, Duke University, Medical Center, Durham, NC, USA
Phone: +91 96683424