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Table of Contents
ORIGINAL ARTICLE
Year : 2020  |  Volume : 14  |  Issue : 1  |  Page : 38-41

Delayed graft function in living donor kidney transplantation: A single-center experience


Institute of Nephrology, Madras Medical College, Chennai, Tamil Nadu, India

Date of Submission01-Jul-2019
Date of Acceptance05-Jan-2020
Date of Web Publication31-Mar-2020

Correspondence Address:
Dr. Rakesh Durai
Institute of Nephrology, Madras Medical College, Chennai - 600 003, Tamil Nadu
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijot.ijot_23_19

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  Abstract 


Aim: The aim was to study the incidence of delayed graft function (DGF) in living donor kidney transplantation (LDKT), its risk factors, and its impact on graft and patient survivals. Materials and Methods: We retrospectively analyzed the medical records of 543 patients over 12 years of age who had received kidney transplant from a living donor between 2007 and 2018. The demographic characteristics of the patients, acute rejection rates, graft function at 1 year, graft survival, and patient survival were compared between patients with and without DGF. Results: The incidence of DGF was 10.1% in our study. Cold ischemia time (CIT) (76.61 ± 33.66 vs. 53.02 ± 17.55 min; P < 0.01) and the use of tacrolimus (6.3% vs. 4.2%; P < 0.01) were associated with greater incidence of DGF. Patients with DGF had a longer duration of hospital stay (23.03 ± 11.37 vs. 13.98 ± 5.81 days; P < 0.01). There were no statistically significant differences in acute rejection rates, death-censored graft survival, and patient survival in the two cohorts. Conclusions: Our study reiterates that CIT is an important predictive factor for DGF. This is pertinent because CIT is a modifiable risk factor. However, DGF did not have a significant impact on patient and graft survivals in LDKT recipients.

Keywords: Cold ischemia time, delayed graft function, living donor kidney transplantation


How to cite this article:
Durai R, Natarajan G, Thanigachalam DK, Ramanathan S, Jeyachandran D, Kumar D. Delayed graft function in living donor kidney transplantation: A single-center experience. Indian J Transplant 2020;14:38-41

How to cite this URL:
Durai R, Natarajan G, Thanigachalam DK, Ramanathan S, Jeyachandran D, Kumar D. Delayed graft function in living donor kidney transplantation: A single-center experience. Indian J Transplant [serial online] 2020 [cited 2020 Jul 6];14:38-41. Available from: http://www.ijtonline.in/text.asp?2020/14/1/38/281761




  Introduction Top


Delayed graft function (DGF) is commonly defined as the need for dialysis during the first posttransplantation week.[1] A comprehensive definition for DGF is “the failure of the transplanted kidney to function properly in the early phase after transplantation due to ischemia-reperfusion and immunological injury.”[2] The main pathologic finding related to DGF is acute tubular necrosis. DGF incidence depends on its definition, risk profiles of the donor and the recipient, and on the transplant center.[1],[3],[4],[5],[6] There is clear evidence that DGF after deceased-donor kidney transplantation (DDKT) is associated with inferior graft survival.[2],[7],[8] Moreover, DGF may result in prolonged hospitalization, and it may predispose to acute rejection and chronic graft dysfunction.[2] DGF is rare in living donor kidney transplantation (LDKT), and there is a paucity of studies on this issue. The aim of this study is to find the incidence of DGF in LDKT, its risk factors, and its impact on graft and patient survivals in a single center.


  Materials and Methods Top


This is a retrospective study. Approval for the study was obtained from the institutional ethics committee, and our study was conducted in accordance with ethical standards prescribed in the Declaration of Helsinki. A total of 543 patients over 12 years of age who had undergone LDKTs in a public-funded tertiary care hospital between 2007 and 2018 were included in the study. Graft losses secondary to vascular thrombosis, hyperacute rejection, and primary nonfunction were excluded from the analysis. The following recipient- and transplant-related factors were reviewed: age, gender, dialysis vintage, warm ischemia time (WIT), cold ischemia time (CIT), induction and maintenance immunosuppression, DGF, and length of hospital stay. Renal allograft biopsies were performed in 23 of 55 patients with DGF. The following posttransplant data were analyzed: acute rejection episodes and serum creatinine at the 1st and 12th months. Donors' demographic information and their relationship with their recipients were gathered.

In our center, basiliximab induction is given for LDKT only when the donor is a spouse or sibling. Maintenance immunosuppression is with a triple-drug regimen consisting of either tacrolimus/cyclosporine, mycophenolate mofetil/azathioprine, and prednisone. Only seven donors underwent laparoscopic nephrectomy. Graft perfusion was carried out with Ringer's lactate, heparin, and papaverine.

Definitions

  • Delayed graft function: Requirement of dialysis in the first posttransplantation week
  • Warm ischemia time: Period between clamping of renal artery and beginning of cold perfusion
  • Cold ischemia time: Period between beginning of cold perfusion and completion of vascular anastomosis and arterial clamp release
  • Acute rejection: Acute cellular- or antibody-mediated rejection occurring within 3 months posttransplant.


Statistical analysis

All data were entered in MS Excel. The statistical analysis was carried out by SPSS 20.0 version (IBM, New york, United States). A two-stage analysis was done to build a model for predictors/risk factors of DGF. In the first stage, an association between qualitative variables and DGF was assessed by univariate evaluation using independent sample t-test. Categorical variables were assessed by Chi-square test and Fisher's exact test. In the second stage, variables found to be significant by univariate analysis (P < 0.05) were subjected to logistic regression analysis to build the final prediction model. Graft survival, death-censored graft survival, and patient survival were calculated using Kaplan–Meier survival analysis. Log-rank test was used to compare survivals between DGF and non-DGF patients. Statistical significance was considered at 5% level.

The patient consent has been taken for participation in the study and for publication of clinical details and images. Patients understand that the names, initials would not be published, and all standard protocols will be followed to conceal their identity. The study has been approved by Institutional ethics committee of Madras medical College (ECR/270/Inst/TN/2013).


  Results Top


A total of 543 patients were included in the study. The mean follow-up period was 50.02 ± 31.54 months. DGF occurred in 55 (10.1%) of 543 patients. According to the preliminary univariate analysis, there were no associations between the occurrence of DGF and the age and gender of the donor or recipient, relationship between donor and recipient, dialysis vintage, use of induction agent, and WIT [Table 1] and [Table 2]. However, univariate analysis revealed that the use of tacrolimus for maintenance immunosuppression and prolonged CIT had a relationship with incidence of DGF at P < 0.01. Hence, both factors were included in multivariable logistic regression analysis. In logistic regression analysis, both tacrolimus use and CIT were found to be significantly associated with DGF [Table 3]. The length of hospital stay posttransplant was significantly prolonged in patients with DGF, with a mean duration of 23 days (P < 0.01) [Table 1]. The incidence of acute rejection was more in DGF patients (24%), but it was not statistically significant [Table 1]. The mean serum creatinine at the 1st month and 12th month posttransplantation was higher in patients with DGF, but the differences were not statistically significant [Table 1].
Table 1: Recipient characteristics

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Table 2: Donor characteristics

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Table 3: Logistic regression analysis

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The Kaplan–Meier analysis of death-censored graft survival and patient survival is given in [Figure 1] and [Figure 2]. Log-rank test was used to compare survivals between DGF and non-DGF patients. There were no statistically significant differences in death-censored graft survival and patient survival between DGF and non-DGF patients [Table 4].
Figure 1: Death-censored graft survival curves

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Figure 2: Patient survival curves

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Table 4: Log-rank test for comparing survival

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  Discussion Top


DGF is a well-known postoperative complication after DDKT. It is a form of acute kidney injury that results in posttransplantation oliguria. The incidence of DGF in published literature is 10%–60% after DDKT.[9],[10] In a study of 173 DDKT done at our center, the incidence of DGF was 48.5%, acute rejection rate was 21.8%, and the patient and death-censored graft survivals at 1 year were 80% and 82.6%, respectively,[9] whereas in the current study of LDKT, the incidence of DGF was 10.1%, acute rejection rate was 16.8%, and the patient and death-censored graft survivals at 1 year were 98.5% and 99%, respectively. The incidence of DGF in LDKT varies from 1% to 18% in different studies.[1],[3],[11] The difference in incidence of DGF between DDKT and LDKT is mainly due to short WIT and CIT in LDKT. In published literature, the risk factors for DGF are similar in LDKT and DDKT. CIT, WIT, donor age, and longer dialysis vintage are some risk factors reported to be independently associated with DGF in LDKT.[12],[13],[14],[15] Donor age is an important factor in the development of DGF. It has been shown that a donor age >60 years decreases graft survival.[16] This may be due to the fact that an aged donor kidney is more susceptible to ischemic insults. In our study, very few donors were above the age of 60 years and the mean age of donors was 44 years. It has been shown that recipient age >55 also increases the risk of DGF.[17],[18] The mean age of recipients in our study was 30 years with only one recipient above 60 years of age. In the study by Redfield et al., female gender of recipients was associated with a reduced risk of DGF.[15] The authors posit various reasons for this association: female recipient status being a surrogate for favorable recipient health, a size mismatch favoring female recipients, and female recipient milieu being more resistant to ischemia-reperfusion injury than males. In our study, the gender of donors or recipients was not associated with DGF. The relationship between donor and recipient was not shown to be associated with DGF in a study by Salamzadeh et al.[14] In a Turkish study, a longer duration of dialysis before LDKT was associated with DGF.[12] In our study, among the various predictive factors analyzed, CIT and tacrolimus use were significantly associated with DGF in multivariate analysis. CIT has been consistently shown to be a risk factor for DGF.[11] Ischemia-reperfusion injury is the predominant mechanism involved in the development of DGF, and prolonged CIT contributes to increased ischemia-reperfusion injury.

In published literature, tacrolimus was not found to be a risk factor for DGF. However, it is not clear as to why tacrolimus is associated with DGF in our study. In our center, we started using tacrolimus for all patients from the year 2015; at the same time, we started taking up donors with complicated vascular anatomy for transplants. We speculate that prolonged CIT because of difficult surgery could be the reason for increased incidence of DGF after 2015. DGF can potentially lead on to unfavorable posttransplant outcomes in the form of prolonged hospital stay, escalating treatment costs, acute rejection, and poor long-term graft outcomes in DDKT.[19] Whether the same effects are observed in LDKT is not clear. The average length of hospital stay for LD kidneys with DGF was significantly longer, 13.9 days versus 5.9 days for kidneys without DGF in the study by Redfield et al.[15] Similarly, in our study, the average length of hospital stay for LD kidneys with DGF was significantly longer, 23 days versus 13.9 days for kidneys without DGF. Poor graft outcomes have been demonstrated in patients who have both DGF and acute rejection when compared to either of them occurring alone.[8] In our study, the incidence of acute rejection was more in DGF patients compared to non-DGF patients, but the difference was not statistically significant. The long-term effects of DGF are controversial in LDKT recipients. There are varying observations on the impact of DGF on graft survival.[1],[7] In a retrospective analysis of 64,024 patients who underwent LDKT, DGF was associated with poor 5-year graft and patient survivals.[15] There were no differences in patient survival and death-censored graft survival between DGF and non-DGF patients in our study. Interestingly, there were no significant differences in mean 1 month and 1 year posttransplantation serum creatinine values between DGF and non-DGF patients. This could be the reason for lack of difference in graft and patient survivals between DGF and non-DGF patients. The limitations of our study are its retrospective nature and lack of Human leukocyte antigen (HLA) mismatch data to better characterize the immunological risk of the transplants.


  Conclusions Top


Our study reiterates that CIT is an important predictive factor for DGF. This is pertinent because CIT is a modifiable risk factor. However, DGF did not have a significant impact on patient and graft survivals in LDKT recipients.

Acknowledgment

For statistical analysis, we would like to thank Vijay Anto M. Sc., Assistant Professor, Department of Community Medicine, Velammal Medical College Hospital and Research Centre, Madurai.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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2.
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Gopalakrishnan N, Dineshkumar T, Dhanapriya J, Sakthirajan R, Balasubramaniyan T, Srinivasa Prasad ND, et al. Deceased donor renal transplantation: A single center experience. Indian J Nephrol 2017;27:4-8.  Back to cited text no. 9
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Redfield RR, Scalea JR, Zens TJ, Muth B, Kaufman DB, Djamali A, et al. Predictors and outcomes of delayed graft function after living-donor kidney transplantation. Transpl Int 2016;29:81-7.  Back to cited text no. 15
    
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Jeldres C, Cardinal H, Duclos A, Shariat SF, Suardi N, Capitanio U, et al. Prediction of delayed graft function after renal transplantation. Can Urol Assoc J 2009;3:377-82.  Back to cited text no. 19
    


    Figures

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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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