Open Access

Dynamic change of glomerular filtration rate in the early stage is associated with kidney allograft status: a preliminary report

Contributed equally
European Journal of Medical Research201419:72

DOI: 10.1186/s40001-014-0072-6

Received: 14 April 2014

Accepted: 1 December 2014

Published: 24 December 2014

Abstract

Background

This study aimed to investigate the relationship between the dynamic changes of estimated glomerular filtration rate (eGFR) in the early stage post renal transplantation and renal allograft dysfunction.

Methods

We selected 9 patients with interstitial fibrosis and tubular atrophy (IF/TA) and 11 patients with stable renal function based on the Banff 2007 classification system. Pathology of the patients was evidenced with renal biopsy results. Glomerular filtration rate (GFR) was calculated continuously for 14 days post-transplantation by using an estimated GFR (eGFR) formula adjusted into Chinese. Linear regression was employed, and eGFR slopes were compared. Prisoners or organs from prisoners were not used in this study.

Results and Conclusion

The eGFR slope in the IF/TA group was significantly higher than that in the stable group (P < 0.01), and a cut-off value of 5.11 mL/min/1.73 m2/d was a reliable clinical value in a receiver operating characteristic (ROC) curve. On the basis of the ROC area under the curve, predictive accuracy of the eGFR slope was excellent (0.848). In conclusion, the eGFR in IF/TA increased faster within a period of 14 days post-transplantation, suggesting that reperfusion in the early stage may damage the glomerular filtration membrane to some extent. Furthermore, reperfusion might adversely affect long-term renal allograft survival.

Keywords

Estimated glomerular filtration rate Slope Interstitial fibrosis and tubular atrophy Renal transplantation

Background

Kidney transplantation is the standard treatment for patients with end-stage kidney disease. Acute rejection rates and early graft loss have decreased substantially over the past four decades. However, progressive chronic allograft dysfunction, particularly interstitial fibrosis and tubular atrophy (IF/TA), remains a common cause of late graft loss [1]-[5]. Early prognosis of a kidney transplant is critical for the management of subsequent therapy. A considerable number of risk factors have been identified to influence short- and long-term graft survival, such as recipient and donor age, presence of diabetes mellitus, human leukocyte antigen mismatch, prolonged cold ischemia time, cytomegalovirus infection, acute rejection episodes, and delayed graft function [6]-[8]. In the early post-transplantation stages, several important clinical factors may influence kidney graft function, such as blood residues, rejection episodes, and acute immunosuppressive drug toxicity.

For decades, serum creatinine (Scr) has been a critical clinical parameter that is widely used to evaluate the function of transplanted kidneys. However, Scr values are abnormal only in severe renal dysfunction. Thus, Scr cannot be used to detect early stages of renal disorders. The most reliable method for evaluation of renal function is measurement of GFR [9],[10]. In this study, we evaluated the relationship between prognosis and eGFR changes in the early stage post renal transplantation. Moreover, the eGFR slope was evaluated for sensitivity and specificity by using the receiver operation characteristic (ROC) curve.

Methods

Baseline characteristics of the patients

From January to December 2012, 20 living related renal transplanted recipients, whose protocol biopsy results were either normal (stable) or IF/TA, were enrolled in this retrospective study. Biopsy was performed 1 year post-transplantation, and results were defined by the Banff 2007 classification [11]. Other key inclusion criteria were panel reactive antibodies (PRA) < 20% on the day of transplant and/or before transplant, first-time renal transplantation, and over 1 year post-transplantation. Patients who received a multi-organ transplant, had undergone long-term immunosuppression before transplantation, were experiencing generalized infection at the time of transplant, had a history of malignancy, or were positive for HIV, HCV antibody, or HbsAg were excluded from the study. All these living related renal transplantat patients and this study were approved by the Ethics Committee of Zhongshan Hospital, Fudan University (Shanghai, China). Procedures in this study were in accordance with the Helsinki Declaration of 1975. No prisoners or organs from prisoners were used in this study. Informed consents were obtained from these patients and living related donors.

eGFR formula

The eGFR formula was based on the Modification of Diet in Renal Diseases (MDRD) formula and was adjusted to Chinese and called c-aGFR:
c aGFR mL / min / 1.73 m 2 = 186 × S c r 1.154 × Age 0.203 × 0.742 Female × 1.233

[12] c-aGFR was calculated for 14 days post-transplantation.

Statistics

Results were expressed as mean values ± SD. IBM SPSS 19.0 (International Business Machines Corp., Armonk, NY, USA) was used for data analysis. At baseline, proportion gender ratio, primary diagnosis, and immunosuppressive protocol were compared by Chi-square test of independence. Mean age, body mass index, cold/warm ischemia time, and pre-transplant PRA levels were compared by two-tailed Student's t-tests. All other variables were presented descriptively. The slope of eGFR was calculated by linear regression. Two sample unpaired t-tests were used to compare eGFR slopes between stable and IF/TA patients. The area under the curve (AUC) of ROC was calculated to evaluate sensitivity and specificity. Overall, P < 0.05 was regarded as significant.

Results

Characteristics of the transplant recipients

Table 1 shows the characteristics of patients. Table 2 lists the grade of IF/TA according to Banff 2007 for each patient in the IF/TA group.
Table 1

Demographic characteristics of patients

 

Stable

IF/TA

P-value

Numbers

9

11

 

Gender (male/female)

4/5

5/6

>0.05

Age (years)

42.75 ± 3.51

43.22 ± 2.94

>0.05

Weight (kg)

53.11 ± 3.24

54.09 ± 4.76

>0.05

BMI

23.98 ± 1.98

24.08 ± 1.72

>0.05

Cold ischemia time (min)

36.98 ± 0.81

37.02 ± 0.91

>0.05

Warm ischemia time (min)

4.91 ± 0.55

5.01 ± 0.40

>0.05

Primary diagnosis

   

Glomerulonephritis

7

8

>0.05

Nephrotic syndrome

2

3

>0.05

Pre-transplant PRA (%)

   

Class I

1.08 ± 0.87

0

>0.05

Class II

1.11 ± 0.80

0

>0.05

ISP

   

CsA + MMF + Pred

6

7

>0.05

Tac + MMF + Pred

3

4

>0.05

IF/TA: interstitial fibrosis and tubular atrophy; BMI: body mass index; PRA: panel reactive antibody; ISP: immunosuppressive protocol; CsA: cyclosporine A; Tac: tacrolimus; MMF: mycophenolate mofetil; Pred: prednisone. Data were presented as mean values with standard error of the mean.

Table 2

Interstitial fibrosis and tubular atrophy (IF/TA) grade for each patient in the IF/TA group

Patient number

Grade

1

I

2

I

3

III

4

II

5

III

6

II

7

I

8

II

9

II

10

I

11

III

Comparison of eGFR slope

The linear trend of calculated eGFRs in each day post-transplantation was analyzed in both stable and IF/TA groups. The slope in the IF/TA group is significantly higher than that in the stable group (5.52 ± 0.29 versus 4.15 ± 0.19) (Figure 1).
Figure 1

Linear trend of calculated estimated glomerular filtration rates (eGFRs) in each post-transplant day. The slope in the interstitial fibrosis and tubular atrophy (IF/TA) group was significantly higher than that in the stable group.

Renal function

The Scr and blood urine nitrogen (BUN) were tested when biopsy was performed. Both the Scr and BUN in the IF/TA group were significantly higher than those in the stable group (Figure 2).
Figure 2

Renal function when the biopsy was performed. Both the serum creatinine (Scr) (A) and blood urine nitrogen (BUN) (B) in the interstitial fibrosis and tubular atrophy (IF/TA) group were significantly higher than those in the stable group.

The ROC curve

The ROC curve was determined to differentiate IF/TA patients from stable patients. The eGFR slope value of 5.11 mL/min/1.73 m2/d was the cut-off value of 0.848 (95% CI, 0.672 to 1.000, P < 0.01, Figure 3). The cut-off value exhibited a sensitivity of 81.8% and specificity of 88.9% in the identification of IF/TA patients, suggesting a potential clinical value and excellent ROC AUC (0.848).
Figure 3

Receiver operating characteristic curve. The circle indicates the cut-off value of 5.11 ml/min/1.73 m2/d with 81.8% sensitivity and 88.9% specificity, and the area under the curve is 0.848.

Discussion

This study is the first to analyze eGFRs obtained on a daily basis for 14 days post-transplantation using linear regression. We found that the eGFR slope in IF/TA patients was significantly higher than that in stable patients. The eGFR slope value of 5.11 mL/min/1.73 m2/d as a cut-off value provided a sensitivity of 81.8% and specificity of 88.9% in the identification of IF/TA patients. Results revealed that the slope in the early stage post-transplantation may be an indicator of 1-year allograft dysfunction.

The eGFR is a better alternative parameter than creatinine in the evaluation of renal function in post-transplanted kidneys. Increasing eGFR in the early stage post-transplantation reflects recovery of renal function. However, the rate may not be favorable. The result showed that the rapid increase in eGFR resulted in adverse effects after 1 year. This interesting result may be attributed to early reperfusion overload in transplanted kidneys. Previous studies demonstrated that mechanical stress in the renal artery could lead to severe injury of the renal graft, independent from immune factors such as rejection or inflammation. Tovbin et al. reported a case wherein rapid reperfusion occurred because of left axillo-femoral bypass graft surgery and induced progressive glomerulonephritis in a renal transplant patient [13]. Aggravated capillary damage, inflammation, and oxidative stress following successful reperfusion are possible explanations for the case. Putative mechanisms for these phenomena are interaction of reperfusion-induced hyperfiltration, high intraglomerular capillary pressure, oxidative stress, increased polymorphonuclear cell infiltration, and inflammation [13],[14]. In the early stage post renal transplantation, the glomerular filtration membrane is constantly exposed to high pressure for several days, which may lead to proteinuria and potential tissue injury. Given that pathological examination is the standard method to evaluate the long-term outcome of a renal graft, patients in this study were divided into stable and IF/TA groups according to the protocol biopsy results. We hypothesize that immediate overload in the reperfused kidney is a critical direct risk factor in chronic graft deterioration.

eGFR is a reliable reflection of perfusion loading and recovery of the transplanted kidney. In this study, the eGFR was calculated according to the Chinese-adjusted abbreviated MDRD formula (c-aMDRD) for a more accurate GFR estimation for Chinese people compared with Nankivell or Cockcroft-Gault formula, or typical aMDRD formula [12],[15],[16]. In the long run, increasing eGFR in the post-transplant period indicates recovery of renal graft function. However, the extremely rapid rise of eGFR may not necessarily be favorable. We analyzed the eGFR of patients within 14 days after renal transplantation and examined the linear relationship of day-by-day eGFRs in both groups. Results exhibited a positive linear fit among the eGFR values with time. Slopes obtained through calculations may reflect the rate of eGFR increase and thus indicate graft perfusion load. The slope in the IF/TA group was significantly higher than that in the stable group, which was in accordance with our expectation.

We finally formulated hypotheses that may be involved in over-perfusion within the renal graft in the early stage after transplantation:
  1. 1)

    Sequence of opening of renal artery and vein at reperfusion. As one of the high perfusion organs, the kidney can filter nearly one third of the circulation volume within 1 minute. If the renal artery is opened first, the inner pressure of the kidney will rapidly reach the peak, which may injure the glomerular filtration membrane. Ideally, the renal artery and vein should be opened simultaneously. However, this procedure is difficult in practice. In our opinion, opening the renal vein immediately before opening the renal artery is safer to ensure the stability of intra-renal pressure, which may protect the glomerular filtration membrane.

     
  2. 2)

    Ligation of the minor branches of the vein. The conservation of arterial branches is a well-accepted procedure for enabling sufficient perfusion of the kidney. However, the conservation of small venous branches remains controversial. In some instances, ligated branches collect a large reservoir of blood in the kidney, which may result in high intra-renal pressure that injures the glomerular filtration membrane, even when the general blood pressure is normal.

     
  3. 3)

    Blood pressure level during perioperative period. In general, patients with end-stage chronic renal failure suffer from hypertension. This condition requires specific attention during the operation, especially before opening the vasculature. Blood pressure may vary during the perioperative period. Blood pressure for optimal recovery of kidney function is difficult to establish. Some studies report an optimal pressure ranging from 80 mmHg to 125 mmHg, whereas others claim that the systolic pressure should not be lower than 140 mmHg to avoid insufficient perfusion of the transplanted kidney [17],[18]. In uremia patients, long-term hypertension, anemia, or atherosclerosis resulted in vascular smooth muscle dysfunction, which may further deteriorate the self-regulation of renal vessels. Therefore, we recommend the use of vasoactive agents when necessary in the early post-operative stage for the maintenance of appropriate renal perfusion pressure. When the patient has suffered from hypertension for many years, the administration of an anti-hypertensive agent is highly recommended to protect the renal graft as early as possible [19],[20].

     

The limitations in this study should be noted. First, the sample size was small. Second, it would be very helpful to compare the surgical technique data such as the opening sequence of artery and vein, the number of ligated free veins and blood pressure fluctuation in perioperative period between the two groups. We are now, however, unfortunately unable to access the original data. Moreover, long-term follow-up is required to find a cut-off eGFR value as a prognostic reference.

Conclusion

In conclusion, a relationship exists between early eGFR variation after renal transplantation and prognosis. The rapid elevation of eGFR reflects high reperfusion, which may have disadvantages for prognosis. Therefore, in clinical settings, the blood pressure should be maintained within a certain range during or immediately after transplantation to decrease the damage caused by high reperfusion to the glomerular filtration membrane and to ameliorate the prognosis.

Notes

Abbreviations

eGFR: 

estimated glomerular filtration rate

ROC: 

receiver operating characteristic

IF/TA: 

interstitial fibrosis and tubular atrophy

Scr: 

serum creatinine

PRA: 

panel reactive antibodies

MDRD: 

Modification of Diet in Renal Diseases

BUN: 

blood urine nitrogen

Declarations

Acknowledgement

We thank Dr. Long Li for the help in data collection.

Authors’ Affiliations

(1)
Department of Urology, Zhongshan Hospital, Fudan University
(2)
Shanghai Key Laboratory of Organ Transplantation
(3)
Department of Transfusion, Zhongshan Hospital, Fudan University,

References

  1. Dalinkeviciene E, Kuzminskis V, Petruliene K, Skarupskienė I, Bagdonaviciutė G, Bumblytė IA: Ten-year experience of kidney transplantation at the Hospital of Kaunas University of Medicine: demography, complications, graft and patient survival. Medicina (Kaunas) 2010, 46(8):538–543.Google Scholar
  2. Hashiani A, Rajaeefard A, Hasanzadeh J, Kakaei F, Behbahan AG, Nikeghbalian S, Salahi H, Bahador A, Salehipour M, Malek-Hosseini SA: Ten-year graft survival of deceased-donor kidney transplantation: a single-center experience. Ren Fail 2010, 32(4):440–447. 10.3109/08860221003650347PubMedView ArticleGoogle Scholar
  3. de Fijter JW: Rejection and function and chronic allograft dysfunction. Kidney international. Supplement 2010, S38–S41.
  4. Farris AB, Colvin RB: Renal interstitial fibrosis: mechanisms and evaluation. Curr Opin Nephrol Hypertens 2012, 21: 289–300. 10.1097/MNH.0b013e3283521cfaPubMedPubMed CentralView ArticleGoogle Scholar
  5. Ganji MR, Harririan A: Chronic allograft dysfunction: major contributing factors. Iran J Kidney Dis 2012, 6: 88–93.PubMedGoogle Scholar
  6. Fuggle S, Allen JE, Johnson RJ, Collett D, Mason PD, Dudley C, Rudge CJ, Bradley JA, Watson CJE: Factors affecting graft and patient survival after live donor kidney transplantation in the UK. Transplantation 2010, 89(6):694–701. 10.1097/TP.0b013e3181c7dc99PubMedView ArticleGoogle Scholar
  7. Moghani-Lankarani M, Assari S, Kardavani B, Einollah B: Kidney transplantation in Afghan refugees residing in Iran: the first report of survival analysis. Ann Transplant 2010, 15(2):55–60.PubMedGoogle Scholar
  8. Serur D, Saal S, Wang J, Sullivan J, Bologa R, Hartono C, Dadhania D, Lee J, Gerber LM, Goldstein M, Kapur S, Stubenbord W, Belenkaya R, Marin M, Seshan S, Ni Q, Levine D, Parker T, Stenzel K, Smith B, Riggio R, Cheigh J: Deceased-donor kidney transplantation: improvement in long-term survival. Nephrol Dial Transplant 2011, 26(1):317–324. 10.1093/ndt/gfq415PubMedView ArticleGoogle Scholar
  9. Thomas C, Thomas L: Renal failure - measuring the glomerular filtration rate. Dtsch Arztebl Int 2009, 106: 849–854.PubMedPubMed CentralGoogle Scholar
  10. Soares AA, Eyff TF, Campani RB, Ritter L, Camargo JL, Silveiro SP: Glomerular filtration rate measurement and prediction equations. Clin Chem Lab Med 2009, 47: 1023–1032. 10.1515/CCLM.2009.263PubMedView ArticleGoogle Scholar
  11. Solez K, Colvin RB, Racusen LC, Haas M, Sis B, Mengel M, Halloran PF, Baldwin W, Banfi G, Collins AB, Cosio F, David DS, Drachenberg C, Einecke G, Fogo AB, Gibson IW, Glotz D, Iskandar SS, Kraus E, Lerut E, Mannon RB, Mihatsch M, Nankivell BJ, Nickeleit V, Papadimitriou JC, Randhawa P, Regele H, Renaudin K, Roberts I, Seron D, et al.: Banff 07 classification of renal allograft pathology: updates and future directions. AmJ Transplant 2008, 8: 753–760. 10.1111/j.1600-6143.2008.02159.xView ArticleGoogle Scholar
  12. Ma Y, Zuo L, Chen JH, Luo Q, Yu XQ, Li Y, Xu JS, Huang SM, Wang LN, Huang W, Wang M, Xu GB, Wang HY: Modified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease. J Am Soc Nephrol 2006, 17(10):2937–2944. 10.1681/ASN.2006040368PubMedView ArticleGoogle Scholar
  13. Tovbin D, Shnaider A, Kachko L, Basok A, Vorobiov M, Rogachev B, Abramov D, Zlotnik M: Post-reperfusion rapidly progressive glomerulonephritis in post-transplant IgA nephropathy. J Nephrol 2004, 17: 130–133.PubMedGoogle Scholar
  14. Bailey KL, Wyatt TA, Wells SM, Klein EB, Robinson JE, Romberger DJ, Poole JA: Dimethylarginine dimethylaminohydrolase (DDAH) overexpression attenuates agricultural organic dust extract-induced inflammation. J Environ Immunol Toxicol 2014, 2(2):72–78. 10.7178/jeit.15PubMedPubMed CentralView ArticleGoogle Scholar
  15. Gera M, Slezak JM, Rule AD, Larson TS, Stegall MD, Cosio FG: Assessment of changes in kidney allograft function using creatinine-based estimates of glomerular filtration rate. Am J Transplant 2007, 7(4):880–887. 10.1111/j.1600-6143.2006.01690.xPubMedView ArticleGoogle Scholar
  16. Harzallah K, Sellam A, Mhiri A, Slim I, Halouas M, Mezzigue C, Belhadj R, Hmida J, Hammami H, Manaa J: Creatinine clearance estimation after kidney transplantation: an analysis of three methods. Transplant Proc 2007, 39(8):2571–2573. 10.1016/j.transproceed.2007.08.011PubMedView ArticleGoogle Scholar
  17. Gu YL, Cai XA, Shen N, Zeng FJ: The effect of blood pressure of recipients on the grafted kidney during renal transplantation. Chin J Organ T ransplant 1998, 19(1):25–26.Google Scholar
  18. Ma LL, Xie ZL, Tang YW, Sun W, Guo HB, Zhang L, Lin J, Tian Y: Prevention and treatment of hypertension after renal transplantation. Acta Acad Med Sci 2009, 31(3):259–262.Google Scholar
  19. Wang ZG, Tan H, Zhang LY, Liu DC, Xiao HL, Du WH: Effect of intra-abdominal volume increment on kidneys in minipigs with intra-abdominal hypertension after hemorrhagic shock and resuscitation. Military Med Res 2014, 1: 4. 10.1186/2054-9369-1-4View ArticleGoogle Scholar
  20. Hsu NY, Lee H, Yen Y, Cheng YW. Human papillomavirus and non-small cell lung cancer. Thoracic Cancer 2013, 4: 345–353.

Copyright

© Qi et al.; licensee BioMed Central. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Advertisement