MELD and living donor liver transplantation outcome

MELD and living donor liver transplantation outcome

H Said, MD; M Bahaa, MD; M Rady, MD;  MostafaAbdo,MD; AAbdalaal, MD;  M Fathy, MD; Mohamed Hamdy Attya, MD; A. Hamza, MD; M El-Meteini, MD

Ain-Shams Center for Organ Transplant (ASCOT), Ain-Shams University, Cairo, Egypt.

Abstract

Introduction: MELD  score was validated  as a predictor of mortality  for a wide variety of liver diseases,8 including  cirrhotic  patients  awaiting  liver  transplantation  (LT).9 we try  to assess the impact  of MELD  score on patient survival and morbidity  post living donor liver transplantation (LDLT) .

Design: Retrospective study.

Methodology:  Between February  2007 and December  2011, 80 adults patients,  randomly selected with ESLD, had living donor liver transplantation. Nine patients were excluded,  the remaining 71 patients were divided into two groups. Group 1 included 38 patients with MELD

< 20. Group 2 included  33 patients with MELD  > 20. We compared both  groups as regard

operative data (including operative time and intra-operative blood requirement), early post­ operative course (including JCU stay, hospital stay, incidence of infection and other morbidity like renal impairment, cardiovascular, respiratory and neurological complications) and patient survival up to 1 July 2012.

Results: Eleven patients died during this study (15.2%):  three out of 38 patients (7.8%) in

group 1 and 8 outof33 patients (24.2%) [P=0.02]. Mean  hospital stay was 30±14 and 29±18 days in 1st and 2nd group respectively [P=0.937]. The mean JCU stay in group 1 and 2 was

7±3 and 9± 4  days [P=0.315]. Mean operative time in group 1 and 2 was 11.1±2 and 10.6±1.4 hours [P=0.292]. Mean  volume of blood transfusion  and cellsaver  re-transfusion  were 8±4 unit and 1668±202 ml respectively in group 1 in comparison to 10±6 unit and 1910±679  ml respectively  in group 2 [ P  =  0.09 and 0.167].  The incidence  of infection  was 39.4%  and

45.4% in group 1 and 2 respectively [P=0.48]. The incidence of systemic complications (renal, respiratory, cardiovascular and neurological complications) in group 1 and 2 were 36.8% and

45.5% [P =0.3]

Conclusion: MELD  score more than 20 can predict poor overall survival post living donor liver transplantation.  No significant relation between MELD  score and intra-operative  blood requirement, hospital, and JCU stay or post LDLT morbidity was noted.

Introduction:

Orthotopic  Liver   transplantation  (OLT) has become an established treatment approach for patients  with end-stage liver diseases (ESLD),  but the growing scarcity  of grafts compared to numbers of waiting  patients, coupled  with the high cost of this procedure, make it imperative to make difficult decisions

about how to distribute such scarce organs,l,2 and  highlight the  need  to  identify   patients likely to have relatively good outcomes after transplantation.3,4

The Child-Turcotte-Pugh (CTP) score, originally  developed   for  the  assessment of the  outcome   of  patients   with  cirrhosis   and portal hypertension, was extended for general

prognosis, and to stratify patients on the waiting list for LTx. s

The use  of CTP in  prioritizing  potential liver   transplant    recipients   is   limited   by several factors: the variables, ascites and encephalopathy, are all subjective and are influenced  by medical  therapy.  The lack of an assessment of renal function, which is a reliable  prognostic marker in cirrhosis, is an additional limiting factor.6

The model for end-stage liver disease was initially described by Malinchoc et al.7 as a mathematical  model  for  predicting  survival in  the  first   three   months   postoperatively for patients who underwent percutaneous placement of transjugular  intrahepatic porto­ systemic shunt (TIPS). The model for end­ stage liver disease (MELD) score was quickly validated  as  a  predictor  of  mortality  for  a wide  variety  of liver  diseases,8  Afterwards, to   reduce   mortality   amongst   patients   on the  waiting  listlO and  to  eliminate  possible confounding   factors,  the   MELD   criterion was incorporated as a more transparent and objective system, based on easily measurable laboratory tests.ll

The ideal allocation system would allocate livers to candidates who are most likely to die without a transplant, but who also have a high probability  of survival after OLT.l2 Since February 2002, the United Network for Organ Sharing (UNOS) introduced a new allocation policy for  cadaveric  liver transplants,  based on the model for end stage liver disease (MELD)  score.l3  This new  policy  stratifies the patients based on their risk of death while on the waiting list.l4 The impact of MELD score on postoperative mortality remains elusive.

In this  retrospective  analysis,  we  try  to

assess the impact of MELD score on patient survival and morbidity post living donor liver transplantation (LDLT).

Patients and methods:

Between  February  2007  and  December

2011,  80  adults  patients  randomly  selected with ESLD (40 patients with MELD less than

20 and 40 patients with MELD more than 20)

had living donor liver transplantation  at three

centers of liver transplantation (Ain Shams center for organ transplant [ASCOT], Wadi Elneel Hospital  and  Egypt Air hospital)  by the same surgical team. Nine patients were excluded, Three had small for size graft, one recipient with combined organ (liver and kidney) transplants and 5 recipients with incomplete follow-up records. The remaining

71 transplants were involved in this study and were followed up by 1 July, 2012.

Seventy patients had living donor liver transplantation  with  right  liver graft  (RLG) and one patient had left liver graft. Graft recipient weight ratio (GRWR) was between

0.8  and  1.7.  The  immunosuppressive regimen included cyclosporine or tacrolimus; mycophenolate mofetil (MMF), and corticosteroids in all patients except those transplanted for HCC the regimen included calcineurin inhibitor and steroid only. Trough levels of cyclosporine were maintained between  250 and  400  ng/ml for the first  1 to 3 months thereafter, 200 to 300 ng/ml. Trough levels oftacrolimus were maintained between  8 and 12 ng/ml.  Rapid withdrawal of corticosteroid within three months was routine in all patients (all transplanted for HCV).  In  cases  of  acute  rejection  therapy first consisted of optimization of maintenance level of immunosupression.  If not responding MMF   or   rapamycin   might   be   added   if not  currently  being  taken.  In  some  cases shift from cyclosporine to tacrolimus was beneficial. Small dose steroid was used if all other measure failed.

Data analysis:

Seventy   one  patients   included   in  this study were  divided into two groups.  Group

1 included 38 patients with MELD score less than 20. Group 2 included 33 patients with MELD score more than 20. MELD score was calculated using laboratory results collected immediately prior to the liver transplantation with no adjustments for malignancy. We calculated the MELD score through the following  formula:  MELD (0.957  x ln [creatinine mg/dL]+0.378 x ln [bilirubin mg/dL]+ l.12   x ln [INR]+ 0.643 x 108). We examined  the  age  and sex of the  recipient,

diagnosis,  indication  for  transplantation, Child-Turcotte-Pugh   score,   and   cold   and warm  ischemia  time.  The  diagnosis  of chronic liver disease was confirmed by histopathology of the explanted liver. The modified Child-Turcotte-Pugh  score was calculated  and each patient was categorized as A, B, or C. Operative data (including operative time and intra-operative blood transfusion), early post-operative course (including ICU stay, hospital stay, incidence of infection and other morbidity like renal impairment, cardiovascular, respiratory and neurological complications) and patient survival were compared among both groups.

Statistical analysis:

Statistical package for SPSS computer program version 15.0 was used for data analysis. Quantitative variables were summarized using median (range). Qualitative data   were   summarized   using   frequencies

and percentages. Non-parametric t-test compared  means  of  2  independent  groups. Chi-square and Fisher exact tested proportion independence.   Kaplan-Meier   method   was used to estimate  survival  and Log  rank test to compare curves. p value was significant at

<0.05 level.

Results:

This study included 72 patients classified into 2 groups according to MELD score. Demographic data, Child classification, cold and warm ischemia time were comparable between both groups.

MELD score and survival:

Overall patient survival was compared between both groups from date  of transplant to  the  end  point  of  this  study  in  1  July

2012. Eleven patients died during this study (15.2%):   three  patients  out  of  38  (7.8%) in group 1 with MELD less than 20 and 8 patients  out of 33 (24.2%)  in group  2 with

recod meld

r--"1 meld  :>o20

+ meld  <2D-alnsored

+ meld:o-2()-(;6f\ ed

50000

TOTAL_DAYS_HANY_MOO

Figure (1): overall survival of both groups.

recod meld

. meld <20

. meld >20

NO INFECTION      ACTERIAL                            VIRAL                         FUNGAL                  COMBN:D

infection

Figure (2): infection rate in both group.

rtcodmeld

. melcl c:O

·melo::IZO

complic;atlon

Figure (3)v: incidence of systemic complication in both group.

Table (1): Variables studied

MELD  more than 20 [P=0.02]. Figuer(l) MELD score and  hospital stay:

In this  study  a non significant difference was  present  between  both  groups  as regard hospital stay and ICU stay. In group  1 mean hospital stay  was 30±14  days in comparison to          29±18  days  in  group  2  [P=0.937]. The mean ICU stay in group 1 was 7±3 days while in group  2 mean ICU was 9±4 [P=0.315] MELD score and  operative data:

Comparison between  both  groups  in operative  data included  operative  time, blood loss and intra-operative blood transfusion (cellsaver, blood  product) show no statistical significant difference. Mean operative time in group  1 was  11.1±2  hours  (ranged  between

7-15 hr) and  in group  2 was 10.6±1.4 hours (ranged  between  9-14 hr)  [P=0.292]. mean volume   of  blood  transfusion and  cellsaver re-transfusion were  8±4  unit  and  1668±202 ml  respectively in group  1 in comparison to

10±6  unit  and  1910±679 ml  respectively in group 2 [ P    0.09 and 0.167].

MELD score and  postoperative complication:

Infection:

Overall incidence of infection  in this study

was 41.6% (30 out of72 patients). In group 1 with MELD  score  less than 20 the incidence of infection was 39.4%  (15/38 patients). Bacterial     infection    was    the    commonest

23.6%,  followed by viral  2.6%, fungal  2.6% and combined infection in 10.5%.  In group  2 with MELD score more than 20 the incidence of infection was 45.4%  (15/33 patients). Bacterial     infection    was    the    commonest

30.3%,  followed by viral 6%, fungal  0% and combined infection  in 9.1%.  No statistical significant  difference   was  present   between both groups [P=0.48] Figure(2).

Systemic complications:

No significant difference  was present between both  groups  in the  incidence of systemic  complications including renal, respiratory, cardiovascular and neurological complications (36.8% Vs 45.5%,  P=0.3).

Renal  impairment was the  most  common complication   in   both    groups    (10.5%    in group  1 Vs 15.2% in group  2), followed by cardiovascular complication (13.2% in group

1 Vs 12.1% in group  2) mainly  hypertension in most patients  and arrhythmia in 2 patients. Neurological complication occurred in 2.6% in  group  1  Vs 3%  in  group  2.  Respiratory

effusion,  adult respiratory distress  syndrome and respiratory infection) occurred in 7.9 % in group  1 Vs 15.2%  in group  2. Two patients in group  1 (5.3%)  and  2 patients  in group  2 (6.1%) had combined respiratory and other system complication Figure(3).

Discussion:

The  large  disparity  between   patient demand  and donated organs is a pressing problem  for all transplant surgeons. The best solution to this problem is still in dispute. Unfortunately, prioritizing extremely sick patients   make   it  likely   that   patients   who are  not as sick  "will be forced  to  wait until their condition worsens  and their chances for success  are also  diminished",15 and patients who are very sick may have worse post­ transplant outcomes than healthier patients.16

Thus, the optimal  system  would  offer  grafts to those  who  are  sufficiently sick  to  justify the transplantation but not too sick to benefit from  it,17 that is, the urgency  of need should be  jointly  optimized with  the  likelihood of satisfactory outcomes so as to  avoid  "futile transplantation".18

An accurate  prognostic  model  could  also help  potential  transplant recipients  and their familiesmake informed decisions by providing them  with  information on the patient's post­ transplant survival  probability.19,20

MELD was implemented to help prioritize prospective liver allograft recipients. The model's  accuracy  to  predict   short-term mortality  among    patients    with   end-stage liver  disease  has  been  largely  established.21

However,   an  ideal  selection system   would incorporate  predictions  for   survival   while on  the   waiting   list   as  well   as  following transplantation.     The       development    of                              a model that could predict  post-transplantation outcome  based on pre-transplant variables is inherently  difficult   because   of  variation in surgical  skills,  chance  events  that  occur  in the  perioperative  period,  and  other  factors, such  as  graft  rejection, biliary  and  vascular complications, that are generally independent of  pre-transplant  events.  Although it  might seem  plausible   that  the  limited   number  of

could   probably   influence    the    immediate post-transplant phase, their  ability  to predict long term outcome would  appear  less likely. Recently,    several    investigators   examined the predictive value of MELD for post­ transplantation outcome, but the results  were conflicting and follow-up was limited  to 1-2 years,  and thus  a clear consensus has not yet emerged.22,23

In a systematic review  about the performance of  MELD  in the  setting  of LT, Colongita et al. concluded that MELD score is not a good  predictor  for short-term mortality after LT and that further  studies were needed to assess long term performance.9 also Batista et   al.   demonstrated  that   the   preoperative MELD score showed low overall accuracy for predicting survival  after liver transplantation, similar to that described in other Brazilian studies.24 On the other  hand,  worse survival in recipients with  higher  MELD  scores  has been   cited   by   some   authors_25,26,27   This study confirmed the relation  between MELD score  and post  liver transplantation survival. Incidence of mortality  was  7.8% in patients with  MELD  less  than  20  in  comparison to

24.2%  in patients  with MELD  more than  20

[P= 0.02].

Our  study  showed   no  significant impact of MELD  score  on hospital and ICU stay, comparable with  the  result  of  Poon  et a1.,28 while a lot of studies like Foxton et al. demonstrated that transplantation of patients with higher  MELD scores resulted  in an increased  ICU stay, overall hospital  stay, and need for  renal replacement therapy  (RRT).29

Also  Buchananet al. showed  that  patients  in the  highest   MELD   group   had  longer   ICU stays than those  in lower  MELD  groups  (P =

0.008).30

Lee and Chung,  and Massicotte et al. concluded that the MELD score did not predict blood losses and blood product requirement during   liver  transplantation.31,32  Other  like Feng et al. demonstrated that  massive  blood transfusion during  liver  transplantation  can be predicted  by preoperative MELD  score. 33

In  our  study,  no  definite   relation   between

MELD score and intra-operative blood loss or

requirement of blood transfusion was noted.

In this study,  incidence  of infection  was comparable between both groups with no significant difference between MELD score less or more than 20. This conclusion  is the same finding ofLi et al.34 in which Univariate analysis for risk factors for postoperative bacterial and fungal infection showed no statistical significant difference as regard MELD score.

Twenty eight patients suffered from postoperative  complications,  13 of them (36.8%)  were  in the   group  of  MELD  less than 20 and 15 (45.5%) were ofthe group of MELD more than  20 with P value 0.3. The non significant difference can be explained partially by the increased operative mortality in the higher MELD scores.

Conclusion:

MELD  score  more  than  20  can  predict poor   overall   survival   post   living   donor liver transplantation.  No significant relation was noted between MELD score and intra­ operative blood loss or blood requirement, hospital,  and ICU  stay  or post  LDLT morbidity.

References:

1- Merion RM, Schaubel DE, Dykstra DM, Freeman RB, Port FK, et al: The survival benefit of liver transplantation. Am J Transplant 2005; 5: 307-313.

2- Biggins SW: Beyond the numbers: Rational and ethical application of outcome models for organ allocation in liver transplantation. Liver Transplant 2007; 13: 1080-1083.

3-  Schaubel  DE,  Sima  CS,  Goodrich  NP, Feng S, Merion RM:  The survival benefit of deceased donor liver transplantation as a function  of candidate disease severity and donor  quality. Am J  Transplant  2008;  8:

419-425.

4-  Schaubel   DE,  Guidinger  MK,  Biggins SW, Kalbfleisch JD, Pomfret EA, et al: Survival  benefit-based  deceased  donor liver allocation. Am J Transplant  2009; 9:

970-981.

5- Christensen E: Prognostic models including the  Child-Pugh,   MELD  and  Mayo  risk

scores-where are we and where should we go? J Hepatol2004; 41: 344-350.

6-  Durand  F, Valla  D:  Assessment  of  the

prognosis  of cirrhosis: Child-Pugh  versus

MELD. J Hepatol2005; 42: 100-107.

7- Malinchoc M, Kamath PS, Gordon FD, Peine CJ, RanK J, ter Borg PC: A model to predict poor survival in patients undergoing transjugular     intrahepatic    portosystemic shunts. Hepatology 2000; 31: 864-871.

8- Boursier J, Cesbron E, Tropet AL, Pilette C:         Comparison    and   improvement    of MELD  and  Child-Pugh  score  accuracies for  the  prediction  of  6-  month  mortality in cirrhotic  patients. J Clin Gastroenterol

2009; 43: 580-585.

9- Cholongitas E, Marelli L, Shusang V, Senzolo M, Rolles K, Patch D, et al: A systematic review of the performance of the model for end-stage liver disease (MELD) in the setting of liver transplantation. Liver Transpl2006; 12: 1049-1061.

10-Teno'   rio   AL,    Macedo   FI,    Miranda

LE,  Fernandes  JL,  da  Silva  CM,  Neto OL,  et  al:  Survival  on  waiting   list  for liver transplantation before and after introduction  of  the  model  for  end-stage liver disease score. Transplant Proc 2010;

42: 407-411.

11-Freeman RB, Wiesner RH, Edwards E, Harper A, Merion R, WolfeR, et al: Results of the first year of the new liver allocation plan. Liver Transpl 2004; 10: 7-15.

12-Ghobrial  RM, Gombein  J,  Steadman  R,

Danino N, MarkmannJF, etal: Pretransplant model to predict posttransplant survival in liver transplant  patients.  Ann  Surg  2002;

236: 315-322.

13-MartinAP,  Bartels M, Hauss J, Fangmann J:  Overview   of  the   MELD   score  and the UNOS adult liver allocation system. Transpl antProc 2007; 39: 3169-3174.

14-Ravaioli   M,  Grazi   GL,   Ballardini   G,

Cavrini G, Ercolani G, Cescon M, Zanello M, Cucchetti A, Tuci F, Del Gaudio M, Varotti G, Vetrone G, Trevisani F, Bolondi L, Pinna AD: Liver transplantation with the Meld system: A prospective study from a single  European  center.  Am J Transplant

2006; 6: 1572-1577.

15-UNOS:    Rationale     for    Objectives     of Equitable  Organ  Allocation.  Available at: http://www.unos.org/resources/bioethics. asp?index = 10, Accessed August 15, 2011.

16-Neuberger J, Gimson A, Davies M, Akyol M, O'Grady J, et al: Selection  of patients for liver transplantation and allocation of donated  livers  in the  UK. Gut  2008;  57:

252-257.

17-Dawwas MF, Gimson AE: Candidate selection and organ allocation in iver transplantation.  Semin Liver Dis 2009; 29:

40-52.

18-Zhang  M,  Yin  F, Chen  B,  Li  YP, Yan LN, et al: Pretransplant prediction of posttransplant survival for liver recipients with benign end-stage liver diseases: A nonlinear  model.  PLoS  ONE  2012;  7(3):

1256.

19-Jacob M, Lewsey JD, Sharpin C, Gimson A, Rela M, et al: Systematic review and validation of prognostic models in liver transplantation. Liver Transplant 2005; 11:

814-825.

20-Lewsey     JD,     Dawwas     M,     Copley LP, Gimson A, Van der Meulen JH: Developing  a  prognostic  model  for  90- day mortality after liver transplantation based on pretransplant recipient factors. Transplantation 2006; 82: 898-907.

21-Kamath PS, Wiesner RH, Malinchoc M, Kremers W, Themeau TM, Kosberg CL, et al: A model to predict survival  in patients with  end-stage  liver  disease.  Hepatology

2001; 33: 464-470.

22-Brown RS Jr, Kumar KS, Russo MW, Kinkhabwala M, Rudow DL, Harren P, et al: Model for end-stage liver disease and Child-Turcotte-Pugh   score   as  predictors of pre-transplantation disease severity, posttransplantation outcome, and resource utilization in United Network for Organ Sharing status  2A patients.  Liver  Transpl

2002; 8: 278-284.

23-Jacob M, Copley LP, Lewsey JD, Gimson A, Toogood GJ, RelaM, etal: Pretransplant MELD score and post liver transplantation survival in the UK and Ireland. Liver Transpl2004; 10: 903-907.

LEC, Fonseca Neto OCL, Amorim AG, Lacerda CM:  Employment  of meld score for the prediction of survival after liver transplantation.  Rev  Col  Bras  Cir  2012;

39(2).

25-Branda-o A, Fuchs SC, Gleisner AL, Marroni C, Zanotelli ML, Cantisani  G, et al: MELD and other predictors of survival after liver transplantation.  Clin Transplant

2009; 23: 220-227.

26-Monteiro F, Coria SA, Boni R, Pereira LA.

Model for end-stage  liver disease: Impact of the new deceased donor liver allocation policy  in  Sa-o  Paulo,  Brazil.  Transplant Proc 2009; 41: 226-228.

27-Yoo   HY,   Thuluvath    PJ:    Short-term post liver transplant survival after the introduction of MELD scores for organ allocation  in the  United  States.  Liver  Int

2005; 25: 536-541.

28-Poon KS, Chen TH, Jeng LB, Yang HR, Li PC, Lee CC, Yeh CC, Lai HC, Su WP, Peng CY, et al: A high model for end-stage liver disease score should not be considered a contraindication to living donor liver transplantation.         Transplant   Proc   2012;

44(2): 316-319.

29-Foxton   MR,  Al-Freah   MA,  Portal  AJ, Sizer  E, Bernal  W, Auzinger  G,  Rela M, Wendon  JA,  Heaton   ND,  O'Grady  JG, et al: Increased model for end-stage liver disease score at the time of liver transplant results in prolonged hospitalization and overall intensive care unit costs. Liver Transpl2010; 16(5): 668-677.

30-Buchanan P, Dzebisashvili N, Lentine KL,

Axelrod DA, Schnitzler MA, Salvalaggio PR: Liver transplantation cost in the model for end-stage liver disease era: Looking beyond the transplant admission. Liver Transpl2009; 15(10): 1270-1277.

31-Lee  J, Chung  MY: Does the  model  for

end-stage liver disease score predict transfusion amount, acid-base imbalance, haemodynamic and oxidative abnormalities during living donor liver transplantation? J Int Med Res 2011; 39(5): 1773-1782.

32-Massicotte    L,   Beaulieu   D,   Roy   JD,

Marleau  D,  Vandenbroucke   F, Dagenais