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Saudi Journal of Kidney Diseases and Transplantation
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Year : 2009  |  Volume : 20  |  Issue : 6  |  Page : 984-990
Can serial eGFR, body mass index and smoking predict renal allograft survival in south Asian patients


Pondicherry Institute of Medical Sciences, Puducherry, Madras Medical Mission, Chennai, India

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Date of Web Publication27-Oct-2009
 

   Abstract 

Limited data exist regarding long-term allograft survival in South Asian patients in the era of modern immunosuppressive therapy. This retrospective cohort study was undertaken to see the graft survival based on serial eGFR, immunosuppressive therapy, BMI and other confounding factors including smoking in patients who have undergone renal transplantation in a tertiary care center in south India. Three hundred and three kidney transplant recipients including live and cadaveric transplantation performed between 2001 and 2006 were included in this study. The mean graft survival after transplantation was 6.38 ± 0.11 years, graft survival at one, two, three and five years were 95.7%, 92.72%, 91.72% and 89.21%, respectively. The mean serum creatinine and eGFR in the biopsy proven acute rejection (BPAR) group were 1.74 ± 0.94 mg/dL and 43.73 ± 13.65 mL/min com­pared with 1.24 ± 0.59 mg/ dL and 61.50 ± 17.40 mL/min in the non-BPAR group (P< 0.001 and P= 0.0159) respectively. The mean BMI in the BPAR group at one year was 26.59 ± 3.18 kg/m 2 compared with 21.63 ± 2.29 kg/m 2 in the non-BPAR group (P< 0.05). The mean graft survival in patients who were smokers at the time of pretransplant evaluation was 89.3% compared with 92.5% in the non-smokers (P=0.347). This retrospective cohort study found that serial eGFR, body mass index and smoking were significant predictors of graft survival following renal transplantation in South Asian patients.

How to cite this article:
Mohamed Ali AA, Abraham G, Mathew M, Fathima N, Sundararaj S, Sundaram V, Lesley N. Can serial eGFR, body mass index and smoking predict renal allograft survival in south Asian patients. Saudi J Kidney Dis Transpl 2009;20:984-90

How to cite this URL:
Mohamed Ali AA, Abraham G, Mathew M, Fathima N, Sundararaj S, Sundaram V, Lesley N. Can serial eGFR, body mass index and smoking predict renal allograft survival in south Asian patients. Saudi J Kidney Dis Transpl [serial online] 2009 [cited 2019 Dec 14];20:984-90. Available from: http://www.sjkdt.org/text.asp?2009/20/6/984/57250

   Introduction Top


Renal transplantation is the treatment of choice for patients with end stage renal disease even in the tertiary care center of the developing countries with scarce resources.

In the era of the newer and potent immuno­suppressive agents allograft failure in the early period following transplantation has dramati­cally decreased. [1] Acute rejection is considered as an important predictor of chronic rejection, which remains the most important cause of graft loss in long-term studies. [2],[3],[4] There are a number of prognostic variable including esti­mated GFR (eGFR), serum creatinine level, body mass index (BMI), human leukocyte an­tigen (HLA) mismatching, donor and recipient age, gender, etc. eGFR by CockGroft and Gault equation and MDRD is a sensitive tool to mea­sure renal function while the inulin clearance rate is the historical gold standard measure­ment of GFR. [5],[6],[7],[8],[9] Excess body weight (obesity) is known to be associated with overall morta­lity. The association of BMI and the risk of death are modified by smoking status, the pre­sence of diabetes mellitus and coronary artery disease. Among caucasians relative risk of death was twice when BMI was high. Obesity is a risk factor for renal graft loss and high BMI at the time of transplantation showed statistically significant association with pre­sence of renal allograft dysfunction and morta­lity within three years of post transplanta­tion. [10],[11] In this study we retrospectively ana­lyzed our renal transplant data for allograft survival and identified the important factors.


   Patients and Methods Top


Study Design

We retrospectively analyzed the outcome of all patients who underwent primary renal trans­plantation with a graft from a living and de­ceased donor in a tertiary care center between 2001 and 2006. We performed 303 renal trans­plants (three cadaveric and 300 live). The group was made up of 212 male and 92 female pa­tients, with a mean age of 42.74 ± 13.03 years. All values were obtained at post-transplanta­tion period.

Immunosuppression

Post-transplantation variables included the presence or absence of delayed graft function, treatment with antibody such as anti-thymocyte globulin (ATG), basiliximab and daclizumab as induction therapy. Our baseline immuno­suppressive therapy consisted of prednisone 0.5 mg/kg body weight, micro-emulsion form of cyclosporine A 8 mg/kg of body weight, tacrolimus 0.15 mg/kg body weight, mycophe­nolate mofetil two gm/day in two divided doses or sodium salt of mycophenolic acid 360-720 mg twice a day, azathioprine 2-2.5 mg/kg/day and/or rapamycin two to six mg/day. Ninety­three transplant recipients received basiliximab as induction therapy of which 27 had multiple doses, 102 received daclizumab of which two had multiple doses, and seven patients had anti­thymocyte globulin single dose.

Biopsy proven acute Rejections (BPAR) were treated with pulses of methyl prednisone 250 mg-1000 mg for three to five days. Humoral rejection were treated with Rituximub 350-500 mg single dose, plasmaphresis and IV Immuno­globulin. The whole blood trough levels of cyclosporine, tacrolimus and sirolimus were done at regular intervals during the follow-up to adjust recommended trough levels.

Diagnosis of Acute Rejection

A renal core biopsy was performed if clini­cally indicated in cases of graft dysfunction or delayed graft function. Histologic findings were then classified according to the Banff '97 cla­ssification for acute rejection as borderline, tubulo-interstitial (Banff grade I), or vascular rejection (Banff grade II and III).


   Statistical Analysis Top


The Kaplan-Meier method was used to esti­mate the graft survival of the transplantation for each year. Mean values are used for mi­ssing data. In addition to graft survival, the estimated glomerular filtration rate (eGFR) was calculated according to the Modifications of Diet in Renal Disease Study (MDRD) equa­tion: GFR = 170 Χ creatinine-0.999 Χ age­0.176 Χ (0.762 if female) Χ (1.180 if black) Χ BUN-0.170 Χ albumin + 0.318. [8]


   Result Top


Among the 303 renal transplant recipients, 169 were smokers, 89 (29.4%) were diabetic, 234 (77.2%) were hypertensive, 18 (5.9%) had coronary artery disease and two underwent co­ronary artery bypass grafting [Table 1]. One recipient was positive for Hepatitis B, 17 were positive for Hepatitis C and none of them were HIV positive.

Acute rejection episode occurred in seventy­nine transplant recipients and seven were back on hemodialysis.

Mean graft survival after transplantation was 6.38 ± 0.11 in years, graft survival at one, two, three and five years was 95.7%, 92.72%, 91.72% and 89.21%, respectively. Mean serum crea­tinine and eGFR in biopsy proven acute rejec­tion (BPAR) was 1.74 ± 0.94 mg/dL and 43.73 ± 13.65 mL/min compared to 1.24 ± 0.59 mg/ dL and 61.50 ± 17.40 mL/min in others (P< 0.001 and P= 0.0159) respectively. Mean BMI in BPAR at one year was 26.59 ± 3.18 kg/m 2 compared to 21.63 ± 2.29 kg/m 2 in others (P< 0.05). Mean graft survival in patients who were smokers at the time of pretransplant eva­luation was 89.3% compared to non-smoker of 92.5%, (P= 0.347).

The HLA matching showed 202 complete mismatches in the A loci, 198 in the B loci and 86 in the DR loci. Zero mismatching in the A, B and DR loci were 13, 7 and 14 respectively. Mismatching of two to four antigens at A, B and DR loci were 85, 95 and 173 respectively. [Table 1] shows the demographics and the base­line characteristics of the patients. [Figure 1] and [Figure 2] shows graft survival related to variables that have previously reported to be predictive of later graft failure. No difference in allograft survival was noted among males and females. Survival was significantly better for younger recipients, lower BMI, and lower creatinine and GFR achieved after transplantation. [Figure 3] shows the cumulative graft survival over 7 years.


   Discussion Top


In our South Asian renal transplant population better survival was obtained with lower BMI and younger age. In the general population, obesity is defined as the body mass index (BMI) > 30 kg/m 2 and associated with higher rates of hypertension, diabetes, cardiovascular disease and premature death. [12],[13] Prevalence of obesity is high among renal transplant patients, ran­ging between 25% and 35%. [14],[15] Better survi­val among higher BMI patients on mainte­nance hemodialysis basically represents nutri­tional status contrary to the transplant patients where steroid and other medications cause higher BMI and decreased survival. [16],[17],[18],[19],[20],[21],[22],[23] There are only limited data on renal graft survival correlated with body mass index on the trans­plant outcomes of South Asians. In our population, patients of South Asian ethnicity who had BMI more than 25 kg/m 2 had significant decrement in graft survival. (P= 0.0033). In a recent analysis of 51,927 renal transplant reci­pients registered in the USRDS database bet­ween 1988 and 1997, BMI followed a U-shaped curve, with significantly increased risk at both the high and low extremes and the lowest risk was observed in patients between a BMI of 22 and 32 kg/m 2 . [24] This same U-shaped associa­tion held true for cardiovascular as well as infection related death.

Excess body weight predisposes to changes in the metabolic status of these patients on kid­ney function, such as hypertension, cardiovas­cular disease (hyperlipidemia, insulin resistance, and heart dysfunction) as well as glomerular hyperfiltration. [15],[25],[26] Changes in the immuno­logical responses via secretion of cytokines, such as tumor necrosis factor alfa, interleukin­6, and plasminogen activator inhibitor-1 during acute rejection episodes may be altered in higher BMI patients. [14],[27] Thus, normalization of body weight is of paramount importance in renal transplant recipients

The importance of early renal function as a marker of long-term graft survival are well known, with many studies using serum crea­tinine to assess renal function. [28],[29],[30],[31],[32],[33],[34],[35] However, serum creatinine measurement has significant limitations, including the inability to detect functional impairment of less than 50%, error­prone variability in assay techniques, and the impact of age, sex, and nutritional status on creatinine production. Our study used the Mo­difications of Diet in Renal Disease Study (MDRD) to calculate renal creatinine clearance as an estimate of GFR, rather than serum crea­tinine.

Glomerular filtration rate using renal clea­rance of 51Cr EDTA is used to evaluate long­term graft function in a study of cadaveric kidney recipients [36] where it was shown that measured GFR at one year was a highly sen­sitive marker of graft quality and was pro­foundly influenced by donor risk factors, such as age and previous morbidity. Among our renal transplant recipients who had eGFR of more that 60 mL/min had a better graft sur­vival and cumulative graft survival were 95.7% at one year (P= 0.0242) and 85.49% at the end of six years (P= 0.0159). Long-term success of renal transplantation depends upon the quality of the donor organ, avoidance of peri-transplant and early post transplant damage (rejection), and optimal maintenance of graft function after the first six to 12 months.

In our study, Zero mismatching in the A, B and DR loci were 13, seven and 14 respec­tively and large majority had mismatching of two to four antigen. The importance of HLA mismatch and long-term renal outcome was reported by Coupel et al [31] who found that the degree of HLA matching was one of the most significant risk factors for ten-year survival of second grafts. In contrast, a recent report by Su et al [37] stated the significance of HLA matching has diminished over recent years in favor of non-immunological risk factors, such as donor age and cold ischemia time.

In a multivariate analysis conducted by Sung, Randall et al showed that pretransplant smoking was significantly associated with reduced overall graft and death-censored graft survival. [38]

We did not find the same significance, how­ever, death-censored graft survival was signi­ficantly higher for those who quit smoking before transplant evaluation.

In conclusion, this analysis has shown that serial eGFR, body mass index and smoking are significant predictors of graft survival following renal transplantation in South Asian patients. Utilizing this information, interventions must be initiated to improve the outcome of patients with renal transplantation.

 
   References Top

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2.Tejani A, Corres L, Stablein D. Clinical corre­lates of chronic rejection in pediatric renal transplantation: a report of the North American Pediatric Renal Transplant Cooperative Study: Transplantation1996;61:1054-8.  Back to cited text no. 2      
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13.13. Obesity Epidemic Increases Dramatically in the United States. Atlanta, Center for Disease Control, National Center for Chronic Disease revention and Health Promotion, ­http://www.cdc.gov/nccdphp/dnpa/obesityepidemic.htm   Back to cited text no. 13      
14.Friedman AN, Miskulin DC, Rosenberg IH, et al. Demographics and trends in overweight and obesity in patients at time of kidney transplan­tation. Am J Kidney Dis 2003;41:480.  Back to cited text no. 14      
15.Teplan V, Schuck O, Stollova M, et al. Obesity and hyperhomocystenemia after kidney trans­plantation. Nephrol Dial Transplant 2003;18 (suppl 5):v71.  Back to cited text no. 15      
16.Drafts HH, Anjum MR, Wynn JJ, et al. The impact of pre-transplant obesity on renal trans­plantation outcomes. Clin Transplant 1997;11: 493-6.  Back to cited text no. 16      
17.Meier-Kreiesche HU, Arndorfer JA, Kaplan B. The impact of body mass index on renal trans­plant outcomes. A significant independent risk factor for graft failure and patient death. Trans­plantation 2002;73:70-4.  Back to cited text no. 17      
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19.Wolfe RA, Ashby VB, Daugirdas JT, et al. Body size, dose of hemodialysis, and morta­lity. Am J Kidney Dis 2000;35:80-8.  Back to cited text no. 19      
20.Leavey SF, McCullough K, Hecking E, et al. Body mass index and mortality in healthier vs. sicker hemodialysis patients. Results from the Dialysis Outcomes and Practice Patterns Study (DOPPS). Nephrol Dial Transplant 2001;16: 2386-94.  Back to cited text no. 20      
21.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;341:1725-30.  Back to cited text no. 21      
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23.Longnecker JC, Coresj J, Klag MJ, et al. Validation of co morbid conditions on the end­stage renal disease medical evidence report; The CHOICE study. Choices for Healthy Out­comes in Caring for ESRD. J Am Soc Nephrol 2000;11:520-9.  Back to cited text no. 23      
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25.EBFG Expert Group on Renal Transplantation: European best practice guidelines for renal transplantation. Section IV: long-term manage­ment of the transplant recipient. IV.5.7. Cardio­vascular risks. Obesity and weight gain. Nephrol Dial Transplant 2002;17(suppl 4):29.  Back to cited text no. 25      
26.EBFG Expert Group on Renal Transplantation: European best practice guidelines for renal transplantation. Section IV: long-term manage­ment of the transplant recipient. IV.2.3. Chro­nic graft dysfunction. Non-alloimmune factors. Nephrol Dial Transplant 2002;17(suppl 4):11.  Back to cited text no. 26      
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31.Coupel S, Giral-Classe M, Karam G, et al. Ten­year survival of second kidney transplants: Im­pact of immunological factors and renal func­tion at 12 months. Kidney Int 2003;64:674.  Back to cited text no. 31      
32.First MR. Renal function as a predictor of long term graft survival in renal transplant patients. Nephrol Dial Transplant 2003;18(S1):i3.  Back to cited text no. 32      
33.Siddiqi N, McBride M, Hariharan S. Similar risk profiles for post-transplant renal dysfunc­tion and long-term graft failure: UNOS/OPTN database analysis. Kidney Int 2004;65:1906.  Back to cited text no. 33      
34.Hariharan S, McBride M, Cohen EP. Evolution of endpoints for renal transplant outcome. Am J Transplant 2003;3:933.  Back to cited text no. 34      
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37.Cecka JM. The UNOS scientific renal trans­plant registry. In: Clinical Transplants 1999. Cecka JM, Terasaki PI (eds). Los Angeles, UCLA Tissue Typing Laboratory, 1999.  Back to cited text no. 37      
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Correspondence Address:
Georgi Abraham
Pondicherry Institure of Medical Sciences, Kalapet, Puducherry
India
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