Liver transplant surgery is often associated with considerable bleeding. This study was undertaken to analyse the average blood component consumption and the effectiveness of preoperative laboratory assessment and Model For End Stage Liver Disease (MELD) score in the estimation of transfusion requirements in Living Donor Liver Transplantation (LDLT).
Similaire à Transfusion requirements in living donor liver transplantation e Role of laboratory assessment and Model For End Stage Liver Disease (MELD) score
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Transfusion requirements in living donor liver transplantation e Role of laboratory assessment and Model For End Stage Liver Disease (MELD) score
1. Transfusion requirements in living donor liver
transplantation e Role of laboratory assessment
and Model For End Stage Liver Disease (MELD) score
2. Original Article
Transfusion requirements in living donor liver
transplantation e Role of laboratory assessment
and Model For End Stage Liver Disease (MELD) score
R.N. Makroo a,
*, R. Walia b
, A. Bhatia c
, M. Chowdhry d
a
Director, Senior Consultant, Department of Transfusion Medicine, Indraprastha Apollo Hospitals, Sarita Vihar,
New Delhi, India
b
DNB Resident, Department of Transfusion Medicine, Indraprastha Apollo Hospitals, Sarita Vihar, New Delhi,
India
c
Sr. Registrar, Department of Transfusion Medicine, Indraprastha Apollo Hospitals, Sarita Vihar, New Delhi,
India
d
Associate Consultant, Department of Transfusion Medicine, Indraprastha Apollo Hospitals, Sarita Vihar,
New Delhi, India
a r t i c l e i n f o
Article history:
Received 17 April 2014
Accepted 3 May 2014
Available online xxx
Keywords:
MELD score
Liver transplant
Living donor
Prediction models
a b s t r a c t
Introduction and aims: Liver transplant surgery is often associated with considerable
bleeding. This study was undertaken to analyse the average blood component consump-
tion and the effectiveness of preoperative laboratory assessment and Model For End Stage
Liver Disease (MELD) score in the estimation of transfusion requirements in Living Donor
Liver Transplantation (LDLT).
Material and methods: Univariate and stepwise regression analysis were employed to
establish the significance of correlation of the preoperative laboratory variables, including
haematocrit, platelet count, INR, total bilirubin, serum creatinine, blood urea and MELD
score with the total consumption of Packed Red Cells (PRCs), cryoprecipitates, aphaeresis
platelets and Fresh Frozen Plasma (FFP). Stepwise discriminant analysis was used to
identify those preoperative factors which have a significant predictive value for the total
consumption of each blood component and these results were employed to construct
separate prediction models for the utilization of each blood component and the respective
R square values were determined.
Results: A total of 509 patients were included. On an average, 8.44 units (SD ¼ 6.11) of PRCs,
2.58 units (SD ¼ 2.95) of cryoprecipitates, 0.81 units (SD ¼ 1.16) of aphaeresis platelets and
2074.85 ml (SD ¼ 1240.20) of FFP were consumed per LDLT. The blood component prediction
models could be employed to accurately predict the total utilisation of PRCs, cry-
oprecipitates, FFP and aphaeresis platelets in 23, 22.6, 17.8 and 20.7 per cent of our patients,
respectively.
Conclusion: We have been able to identify those preoperative factors which can be
employed to predict the consumption of various blood components in living donor liver
graft recipients. These variables were further employed to construct prediction models,
* Corresponding author.
E-mail address: makroo@apollohospitals.com (R.N. Makroo).
Available online at www.sciencedirect.com
ScienceDirect
journal homepage: www.elsevier.com/locate/apme
a p o l l o m e d i c i n e x x x ( 2 0 1 4 ) 1 e6
Please cite this article in press as: Makroo RN, et al., Transfusion requirements in living donor liver transplantation e Role of
laboratory assessment and Model For End Stage Liver Disease (MELD) score, Apollo Medicine (2014), http://dx.doi.org/10.1016/
j.apme.2014.05.010
http://dx.doi.org/10.1016/j.apme.2014.05.010
0976-0016/Copyright ª 2014, Indraprastha Medical Corporation Ltd. All rights reserved.
3. separately for each blood component. We also identified those preoperative variables
which significantly influence the in hospital mortality and PLOS in LDLT recipients.
Copyright ª 2014, Indraprastha Medical Corporation Ltd. All rights reserved.
1. Introduction
Liver transplant surgery is often associated with considerable
bleeding, necessitating transfusion of blood and blood com-
ponents.1,2
Bleeding occurs largely because liver is an
extremely vascular organ3
and the associated bleeding is
compounded by the presence of portal hypertension4
and
abnormalities of the haemostatic system.5,6
This poses a
challenge to the blood transfusion services, particularly when
the supply of blood components is limited.7
Therefore, pre-
operative estimation of the blood component requirements in
patients undergoing liver transplantation would prove bene-
ficial for the blood transfusion services, by improving their
preparedness for such a major surgical procedure and helping
them in better resource allocation.
In order to address this issue, various factors have been
hypothesised as the potential predictors of blood component
usage in liver transplant surgeries. The proposed factors
include the recipient characteristics including recipient’s age,
gender, underlying diagnosis and the presence of any previ-
ous abdominal surgery; preoperative laboratory parameters
like haemoglobin, platelet count, international normalized
ratio (INR), renal parameters and the preoperative Model for
End Stage Liver Disease (MELD) score.8
However, there have
been conflicting reports as to whether such estimation can be
made preoperatively.9,10
In addition, only a limited number of
such reports are available for living donor liver trans-
plantations (LDLT).2
Therefore, the present study was undertaken to document
the average blood component consumption and to analyse the
effectiveness of preoperative laboratory assessment and
MELD score in the estimation of total i.e. intraoperative as well
as the postoperative transfusion requirements in LDLT.
2. Material and Methods
After the approval of the hospital ethical committee, this
study was conducted at the Department of Transfusion
Medicine and Department of Surgical Gastroenterology &
Liver Transplant, Indraprastha Apollo Hospitals, New Delhi,
from January 2009 to May 2012. The records of all the patients
who underwent LDLT at our centre, between January 2009 and
February 2010, were analysed retrospectively and since,
March 2010 all the liver graft recipients were prospectively
followed up during their stay in the hospital.
At our centre, whenever a liver transplant surgery is
planned, a blood component request form is sent to the blood
bank for the arrangement of 10 units of cross matched and
leukoreduced Packed Red Cells (PRCs), 4 units of cry-
oprecipitates, 10 units of fresh frozen plasma (FFP), 2 units of
single donor aphaeresis fresh frozen plasma and 2 units of
single donor aphaeresis platelets, which are kept ready one
day prior to the potential liver transplant surgery. A fresh
blood component request form is sent to the blood bank in
case a further need arises. The intraoperative blood compo-
nent transfusions were based on the clinical condition of the
patient and the results of Thromboelastography (Haemoscope
Corporation, USA). Unless contraindicated, each recipient
received Tranexamic acid in an initial bolus dose of 15 mg/kg
during the induction of anaesthesia and its subsequent use
was guided by the thromboelastography results.
Relevant data, including the patient’s age, gender, history
of dialysis in the week prior to surgery and preoperative
haematocrit, platelet count, INR, total serum bilirubin, serum
creatinine and blood urea, was obtained from the patient’s
case file. The formula, MELD ¼ 9.57 Â loge [creatinine mg/
dL] þ 3.78 Â loge [bilirubin mg/dL] þ 11.20 Â loge [INR] þ 0.643
was used to calculate the MELD score of each liver graft
recipient, based on the preoperative laboratory values of
serum bilirubin, serum creatinine, INR and history of dialysis
in the week prior to surgery.11
Data pertaining to the total number of blood components
consumed by each liver graft recipient during the intra-
operative and postoperative period was obtained from the
blood bank issue records. The number of units of plasma
(FFP and single donor plasma) was converted into plasma
volume in millilitres (ml). This calculation was based on the
results of our quality control measurements which show
that on an average, 1 unit of FFP is equivalent to 200 ml and
the volume of 1 unit of single donor aphaeresis plasma
prepared on a cell separator (Haemonetics, USA) is approx-
imately 600 ml.
Pearson’s correlation coefficients were employed in the
univariate statistical analysis to establish the significance of
correlation of the preoperative laboratory variables, including
haematocrit, platelet count, INR, total bilirubin, serum creat-
inine, blood urea and MELD score with the total consumption
of PRCs, cryoprecipitates, single donor aphaeresis platelets
and FFP. Further, stepwise regression analysis was performed
with all these variables to determine the best model that could
be employed to predict the utilization of each blood compo-
nent. A stepwise regression analysis and multivariate logistic
regression was employed to analyse the effect of various pa-
rameters on mortality during the hospital stay and post-
operative length of stay (PLOS) in the hospital. The various
parameters analysed were recipient’s age; preoperative labo-
ratory parameters including haematocrit, platelet count, INR,
total bilirubin, serum creatinine and blood urea; MELD score
and PRC use (intraoperative, postoperative and total). To
determine the effect of recipient’s gender on mortality and
PLOS in the hospital, Independent t-test and ManneWhitney
test were employed. SPSS version 15.0 was used for all sta-
tistical analyses and all the correlations were defined as sig-
nificant at p-value less than 0.05.
a p o l l o m e d i c i n e x x x ( 2 0 1 4 ) 1 e62
Please cite this article in press as: Makroo RN, et al., Transfusion requirements in living donor liver transplantation e Role of
laboratory assessment and Model For End Stage Liver Disease (MELD) score, Apollo Medicine (2014), http://dx.doi.org/10.1016/
j.apme.2014.05.010
4. 3. Results
A total of 534 patients underwent LDLT during the period of
study. Out of these, twenty-five cases were excluded, nineteen
of the recipients being under 16 years of age, three of the re-
cipients had a concomitant renal transplant and three had a
second liver transplant. None of the adult recipients included
in the study population received a cadaveric donor liver graft
and no intraoperative deaths were reported during the study
period. Out of the 509 patients remaining in the study popu-
lation, 416 (81.7%) were males and 93 (18.3%) were females.
The age of the patients included in the study ranged from 16 to
74 years, with a median of 50 years and mean age of 48.38
years (SD ¼ 10.27). The descriptive characteristics of various
parameters analysed are shown in Table 1.
On an average, a total of 8.44 units (SD ¼ 6.11) of PRCs were
consumed in a liver transplant (Fig. 1, Table 2). In the present
study, seventeen of the liver graft recipients, required no
intraoperative PRC transfusion while in eleven of them, no
PRC was transfused even in the postoperative period. Two of
the liver graft recipients did not require any transfusion dur-
ing the hospital stay. The average consumption of cry-
oprecipitates and aphaeresis platelets and per liver transplant
was 2.58 units (SD ¼ 2.95) and 0.81 units (SD ¼ 1.16),
respectively (Fig. 1, Table 2). The mean volume of FFP
consumed in a liver transplant was 2074.85 ml (SD ¼ 1240.20)
(Fig. 2, Table 2).
As shown in Table 3, univariate analysis demonstrated
that except for the preoperative serum creatinine (p value
>0.05), all the other variables correlated significantly (p < 0.05)
with the consumption of one or more blood components in a
liver transplant. Further evaluation with the stepwise
discriminant analysis, identified those preoperative factors
which have a significant predictive value for the total con-
sumption of each blood component in a liver graft recipient.
These results were further employed to construct separate
prediction models for the utilization of each blood component
and their respective R square values were determined. As
shown in Table 4, it was observed that the total PRC con-
sumption had a significant correlation with preoperative
haematocrit, blood urea and the MELD score. The total con-
sumption of cryoprecipitates was influenced by four factors
including the preoperative platelet count, haematocrit, MELD
score and INR. The total utilisation of FFP could be predicted
by employing preoperative MELD score, haematocrit and total
bilirubin while the preoperative platelet count and MELD score
influenced the total platelet transfusions (Table 4).
Multivariate logistic regression demonstrated that mor-
tality was significantly related to recipient’s age, preoperative
MELD score and total PRCs consumed. It was observed that
with a one year increase in age, the probability of mortality
increases by 4.3 per cent while with a one unit increase in
preoperative MELD score and that of total PRCs transfused,
there is an increase in the probability of mortality by 4.9 per
cent and 9.4 per cent respectively. We also calculated that the
total PRC consumption and preoperative blood urea had a
significant positive correlation with the PLOS in the hospital.
4. Discussion
In the present study, it was calculated that, on an average 8.44
units of PRCs were consumed per LDLT, with a median of 7
units. The average number of cryoprecipitates and single
donor aphaeresis platelets transfused was 2.58 units and 0.81
units, respectively while the average utilisation of FFP per liver
transplant was 2074.85 ml (Table 2). As shown in Table 4, the
total PRC consumption had a significant correlation with
preoperative haematocrit, blood urea and the MELD score
while the total consumption of cryoprecipitates was influ-
enced by the preoperative platelet count, haematocrit, MELD
score and the INR. It was also observed that the total uti-
lisation of FFP could be predicted by employing preoperative
Table 1 e Descriptive characteristics of various parameters.
Parameter Mean S.D. Median Minimum Maximum
Age (years) 48.38 10.27 50.00 16.00 74.00
Hct 0.27 0.06 0.27 0.13 0.44
Plt (Â109
/L) 74.78 51.47 62.00 7.00 469.00
INR 1.94 0.84 1.80 0.90 9.40
T. bilirubin (mmol/L) 115.25 156.81 54.72 3.42 957.26
B. urea (mg/dL) 38.29 32.10 27.00 8.00 209.00
S. crt (mmol/L) 76.27 66.40 46.98 5.00 433.16
MELD score 19.14 7.39 18.00 6.00 44.00
PLOS (days) 21.04 11.52 18.00 2.00 116.00
Abbreviations: Hct, Haematocrit; Plt, Platelet count; INR, International Normalised Ratio; T. bilirubin, Total bilirubin; B. urea, Blood urea; S. crt,
Serum creatinine; MELD, Model for End Stage Liver Disease; PLOS, Postoperative Length of Stay; SD, Standard Deviation.
Fig. 1 e Mean number (units) of blood components used in
liver transplant.
a p o l l o m e d i c i n e x x x ( 2 0 1 4 ) 1 e6 3
Please cite this article in press as: Makroo RN, et al., Transfusion requirements in living donor liver transplantation e Role of
laboratory assessment and Model For End Stage Liver Disease (MELD) score, Apollo Medicine (2014), http://dx.doi.org/10.1016/
j.apme.2014.05.010
5. MELD score, haematocrit and total bilirubin. Similarly, total
platelet transfusions were significantly correlated to preop-
erative platelet count, haematocrit and the MELD
score (Table 4).
Our study demonstrates that the preoperative haematocrit
had a negative influence on the consumption of PRCs, cry-
oprecipitates, FFPs and platelets i.e. a lower preoperative
haematocrit was associated with a higher consumption of
these blood components (Table 4). A negative association of
preoperative haematocrit with the PRC transfusion in liver
transplantation has also been reported previously by Massi-
cotte, et al.12
Moreover, the observed association of the pre-
operative haematocrit and the consumption of
cryoprecipitates, FFPs and platelets can be attributed to a
resultant decrease in haematocrit in the wake of active
bleeding that is associated with abnormalities of the coagu-
lation system and therefore, necessitates transfusion of these
blood components. A significant correlation was also
demonstrated between the preoperative INR and platelet
count with the total consumption of cryoprecipitates and
platelets, respectively (Table 4).
We also observed that the preoperative blood urea had a
positive association with the total utilization of PRCs which
can be attributed to uraemia, which is associated with
impaired renal function and may lead to disturbed coagula-
tion status and subsequent bleeding,13
requiring transfusion
with PRCs. Deakin et al, also concluded that elevated blood
urea was one of the predictors of bleeding in liver trans-
plants.7
The association of renal function impairment and
transfusion requirements in liver transplantation has also
been described in other studies.14e16
Moreover, renal
dysfunction that may be associated with End Stage Liver
Disease can aggravate anaemia as a result of reduced levels of
erythropoietin, leading to increased requirements of PRC
transfusion.17
Our findings show that the preoperative MELD score had a
positive correlation with the total consumption of all the
blood components including PRCs, cryoprecipitates, FFPs and
platelets and the observed associations were highly signifi-
cant. It was also reported by Peter E. Frasco, et al that MELD
score has a significant association with the blood component
therapy in liver transplantation.18
The observed association
of MELD score with the blood component utilization may be
due to the fact that the MELD score is calculated by using
serum bilirubin, serum creatinine and INR11
which represent
Table 2 e Blood component use in liver transplant.
Blood component Mean S.D. Median Minimum Maximum
Intraoperative PRC (units) 6.67 4.39 6.00 0.00 41.00
Cryo (units) 2.39 2.70 2.00 0.00 17.00
FFP (ml) 1735.17 845.25 1600.00 0.00 4400.00
Platelets (units) 0.57 0.73 0.00 0.00 4.00
Postoperative PRC (units) 1.77 3.45 0.00 0.00 31.00
Cryo (units) 0.19 1.13 0.00 0.00 16.00
FFP (ml) 349.02 815.11 0.00 0.00 8000.00
Platelets (units) 0.24 0.78 0.00 0.00 9.00
Total PRC (units) 8.44 6.11 7.00 0.00 41.00
Cryo (units) 2.58 2.95 2.00 0.00 17.00
FFP (ml) 2074.85 1240.20 2000.00 0.00 10,400.00
Platelets (units) 0.81 1.16 0.00 0.00 9.00
Fig. 2 e Mean volume (ml) of FFP used in liver transplant.
Table 3 e Univariate analysis of various parameters with blood component transfusion.
Total blood components Hct Plt (Â109
/L) INR T. bilirubin (mmol/L) B. urea (Mg/dl) S. crt (mmol/L) MELD
PRC (units) Correlation À0.37 À0.08 0.19 0.23 0.32 0.02 0.33
p-value 0.001 0.09 0.001 0.001 0.001 0.62 0.001
Cryo (units) Correlation À0.22 À0.21 0.34 0.27 0.13 À0.03 0.40
p-value 0.001 0.001 0.001 0.001 0.003 0.45 0.001
FFP (ml) Correlation À0.26 À0.09 0.31 0.22 0.19 À0.004 0.38
p-value 0.001 0.05 0.001 0.001 0.001 0.93 0.001
Platelets (units) Correlation À0.24 À0.36 0.17 0.13 0.15 0.014 0.25
p-value 0.001 0.001 0.001 0.004 0.001 0.76 0.001
Abbreviations: Hct, Haematocrit; Plt, Platelet count; INR, International Normalised Ratio; T. bilirubin, Total bilirubin; B. urea, Blood urea; S. crt,
Serum creatinine; MELD, Model for End Stage Liver Disease.
a p o l l o m e d i c i n e x x x ( 2 0 1 4 ) 1 e64
Please cite this article in press as: Makroo RN, et al., Transfusion requirements in living donor liver transplantation e Role of
laboratory assessment and Model For End Stage Liver Disease (MELD) score, Apollo Medicine (2014), http://dx.doi.org/10.1016/
j.apme.2014.05.010
6. a recipient’s hepatic, renal and haemostatic status,
respectively.
We observed that our blood component prediction models
could be employed to accurately predict the total utilisation of
PRCs, cryoprecipitates, FFP and aphaeresis platelets in 23, 22.6,
17.8 and 20.7 per cent of our patients, respectively (Table 4). This
shows that besides the preoperative laboratory parameters and
MELD score, other variables might also influence the blood
component consumption in liver transplants. These variables
could possibly include the intraoperative, technical and general
patient factors, which were not considered in the present study.
It was also seen that the in hospital mortality was signifi-
cantly related to recipient’s age, preoperative MELD score and
total PRCs consumed. A one year increase in the recipient’s
age, increased the probability of mortality by 4.3 per cent.
Similarly, with one unit increase in preoperative MELD score
and that of total PRCs transfused, there was an increase in the
probability of mortality by 4.9 per cent and 9.4 per cent
respectively. PLOS in the hospital was also calculated to be
positively influenced by the total PRC consumption and pre-
operative blood urea.
To the best of our knowledge, the present study is one of
the largest single centre studies that have been undertaken to
identify the significance of preoperative laboratory assess-
ment in estimating the transfusion needs in LDLT. We have
tried to present an extensive analysis of the total i.e. intra-
operative and postoperative, consumption of various blood
components in liver transplantation and have also con-
structed separate prediction models to estimate the use of
each blood component.
However, there still are some limitations in our study. The
present study is limited to the preoperative laboratory vari-
ables and the MELD score only and does not include the effect
of intraoperative, technical and general patient factors on
blood component consumption. It is possible that the inclu-
sion of all these factors might even have resulted in the con-
struction of improved prediction models with higher R square
values and better predictive power. However, the main focus
of our study was to analyse the effect of preoperative labora-
tory parameters and MELD score only, in order to draw defi-
nite conclusions with regard to their predictability by
analysing their role in such a large number of patients.
Moreover, our findings may not be applicable to centres
following a different protocol for liver transplantation and to
centres performing cadaveric donor liver transplants.
To conclude, we have calculated our blood component
consumption in 509 LDLTs. Moreover, we have been able to
identify those preoperative factors which can be employed to
predict the consumption of various blood components in
living donor liver graft recipients. These variables were
further employed to construct prediction models, separately
for each blood component. We also identified those preoper-
ative variables which significantly influence the in hospital
mortality and PLOS in LDLT recipients.
Conflicts of interest
All authors have none to declare.
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Table 4 e Blood component prediction models.
Predicted blood
component
Predicting factors R2
(%) Prediction model P-value
Total PRC (units) Hct
B. urea (mg/dL)
MELD score
23.0 12.454e30.7 Â Hct þ 0.036 Â B. urea þ 0.156 Â MELD 0.001
Cryo (units) MELD score
Plt (Â109
/L)
Hct
INR
22.6 1.775 þ 0.113 Â MELDÀ0.012 Â PltÀ4.9 Â Hct þ 0.461 INR 0.001
FFP (ml) MELD score
Hct
T. bilirubin (mmol/L)
17.8 1748.996 þ 75.310 Â MELDÀ3589.3 Â HctÀ19.870 Â (T. bilirubin/17.1) 0.001
Platelets
(units)
Plt (Â109
/L)
MELD score
Hct
20.7 1.317e7.7 Â 10À3
Plt þ 0.037 Â MELDÀ2.3 Â Hct 0.001
Abbreviations: Hct, Haematocrit; Plt, Platelet count; INR, International Normalised Ratio; T. bilirubin, Total bilirubin; B. urea, Blood urea; MELD,
Model for End Stage Liver Disease.
a p o l l o m e d i c i n e x x x ( 2 0 1 4 ) 1 e6 5
Please cite this article in press as: Makroo RN, et al., Transfusion requirements in living donor liver transplantation e Role of
laboratory assessment and Model For End Stage Liver Disease (MELD) score, Apollo Medicine (2014), http://dx.doi.org/10.1016/
j.apme.2014.05.010
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a p o l l o m e d i c i n e x x x ( 2 0 1 4 ) 1 e66
Please cite this article in press as: Makroo RN, et al., Transfusion requirements in living donor liver transplantation e Role of
laboratory assessment and Model For End Stage Liver Disease (MELD) score, Apollo Medicine (2014), http://dx.doi.org/10.1016/
j.apme.2014.05.010