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Myocardial infarction
Myocardial infarction (MI) is a relatively uncommon complication of early post-LT CVD mortality, which may
be reflective of the preoperative CAD evaluation of these LT patients
[3]. Furthermore, in two recent studies by
VanWagner et al., MI and/or need for revascularization only accounted for 12% of all CVD complications, and
only 7% of hospital readmissions within 90 days of LT were due to MI (
Fig. 20.4) [4,59]. In addition, using the
data from the Nationwide Inpatient Sample and the American Hospital Association Annual Survey, hospitaliza-
tion for MI after LT has decreased in the past decade from approximately 10% in 2002 to 7% in 2011
[60]. In par-
allel, there has been a significant increase in the admissions for HF and dysrhythmias. Dec et al. found that only
5.4% of 146 patients suffered from myocardial ischemia or infarction within the first 6 months following LT
[37].
Patel et al. conducted a retrospective study of LT patients who were evaluated preoperatively with coronary
angiography and found that only 3.9% of 283 patients had non-ST elevation MI, which was thought to be likely
due to demand ischemia from surgery. Moreover, this study found no evidence of relationship between early
composite cardiovascular events and the presence or severity of CAD
[58].
Stroke
Stroke is a relatively rare but also understudied cardiovascular event in the LT population. VanWagner et al.
found that stroke accounted for the second leading cause of CVD mortality at 12.5% in a multicenter study
[3].
Patel et al. fou nd only two patients out of 283 to have a stroke within four weeks after LT
[58]. In another study,
stroke accounted for 9% of hospital readmissions within 90 days after transplantation (
Fig. 20.4). Importantly, AF
significantly increases the risk of MACE, particularly stroke, after transplantation
[61]. Risk factor reduction
involving smoking cessation, blood pressure control, statin use, and anticoagulation if indicated could be a poten-
tial pathway at reducing these cardiovascular events in this patient population though future prospective studies
must be conducted
[4,61]. Importantly, none of these studies reported on the prevalence or incidence of primary
hemorrhagic versus primary ischemic stroke after LT. Future studies examining the timing and risk factors for
stroke subtypes are need in LT recipients.
FIGURE 20.4 Distribution of major cardiovascular events prompting readmission within 90 days of liver transplantation. Source: Adapted
from VanWagner LB, et al. Factors associated with major adverse cardiovascular events after liver transplantation among a national sample. Am J
Transpl. 2016. 16(9):26842694.
334 20. Predicting cardiovascular complications after liver transplantation
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Pulmonary embolism
The incidence of pulmonary embolism (PE) after LT is similar or lower compared to PE incidence in patients
undergoing other major abdominal surgeries (5%10%) [3,4,6265]. A multicenter study by VanWagner et al.
showed a hospital readmission rate for PE within 90 days of transplantation at 11%, which is slightly above the
above-mentioned range (
Fig. 20.1) [4]. Given the physiology of ESLD, patients can have both thrombotic and
hemorrhagic complications due to discrepancies between the coagulation and fibrinolytic systems. There are sev-
eral risk factors for PE, some of which are uniquely associated with LT. These include, but are not limited to, pre-
vious liver disease severity and etiology, increased amounts of intraoperative cryoprecipitate and fresh frozen
plasma, diabetes, previous venous thromboembolism, end-stage renal disease, technical surgical factors (surgical
division of the IVC, VVB, prolonged vascular clamping), increased serum lactate, cardiac arrest, activation of
coagulation system after graft reperfusion, and flat-line TEG in triple channels five minutes after graft reperfu-
sion
[25,6265].
Late ( . 90-day period)
Metabolic syndrome
General overview
Metabolic syndrome is a constellation of hype rtension, dyslipidemia, diabetes mellitus, and abdominal obesity.
This syndrome in itself is an established risk factor for the development of CVD and atherosclerosis in the gen-
eral population and is of particular interest in LT as medications used for immunosuppression are known to pro-
mote metabolic syndrome (
Fig. 20.5). As future advancements continue to occur in the field of LT, recipients are
expected to live longer and thus be on immunosuppression longer
[66]. Pretransplant risk factors for metabolic
syndrome include obesity, diabetes, advanced age, male gende r, immunosuppression, smoking history, liver dis-
ease etiology (hepatiti s C, NASH/cryptogenic, alcohol), marital status, low high density lipoprotein (HDL), and
hypertriglyceridemia
[6668]. The prevalence of metabolic syndrome in LT recipients has been studied to be
FIGURE 20.5 Metabolic syndrome in the post liver transplant population. This highlights the prevalence and immunosuppressant associa-
tions with the entities that comprise metabolic syndrome in the post-liver transplant patient population. CNI, calcineurin inhibitor.
335Natural history and timing of cardiovascular events in liver transplantati on
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44%58% which is higher than the general adult population [67,68]. It is unclear how the cardiovascular risk
associated with calcineurin inhibitors (CNIs) and mechanistic target of rapamycin inhibitors (mTORis) compare
with each other based on current studies. While individual study results may vary, a review by Klintmalm et al.
found that mTORis may actually reduce the risk of metabolic syndrome, but this finding will need to be vali-
dated in larger randomized-controlled trials
[69].
Hypertension
Arterial hypertension has been recently redefined as a systolic blood pressure greater than 130 mm Hg and/or
a diastolic blood pressure greater than 80 mm Hg, and its prevalence in LT recipients ranges from 40%95%
[70,71]. Though ESLD patients are commonly characterized by hypotension given low SVR; patients post-
transplantation and after graft reperfusion have marked increases in SVR and blood pressure which plays a role
in post-LT development of hypertension. The majority of these LT recipients develop hypertension (blood pres-
sure .130/80 mmHg) within the first 6 months post-transplantation, and VanWagner et al. showed that 95% of
these patients were diagnosed with hypertension, based on their office blood pressures, within 6 years post-
transplantation
[71].
Immunosuppressive regimens, particularly involving calcineurin inhibitors and corticosteroids, are strongly associ-
ated with hypertension. Cyclosporine is more frequently associated with hypertension than tacrolimus and usually
develops within weeks to months
[66,67,72,73]. Prior to the introduction of cyclosporine to immunosuppressive regi-
mens, the incidence of post-transplantation hypertension was around 20% and has subsequently increased to
60%95%. Conversely, 31%38% of patients treated with tacrolimus are hypertensive post-transplant, though it is
thought to have a similar mechanism to cyclosporine in causing hypertension
[73]. VanWagner et al. demonstrated
with a single-center retrospective study that office blood pressures ,140/90 mmHg were associated with a 38%
decreased mortality rate and 36% decreased incidence of cardiovascular events compared to those post-LT patients
with blood pressures $ 140/90 mmHg, independent of comorbidities
[71]. Notably, the prevalence of hypertension in
this study was 92%95% depending on the threshold definition used and the majority of patients were treated with
tacrolimus. Current practice-based guidelines from the American Association for the Study of Liver Diseases and the
American Society of Transplantation recommend a target blood pressure goal of # 130/80 mmHg for post-LT
patients with hypertension
[74]. In the VanWagner et al. study mentioned above, only 16% of patients actually met
this goal
[71]. The threshold for blood pressure treatment and the outcomes associated with different blood pressure
target levels, in particular the effects on renal and liver graft outcomes, are currently unknown.
Dyslipidemia
Dyslipidemia occurs frequently after LT and is associated with hypercholesterolemia, hypertriglyceridemia,
high low density lipoprotein (LDL), and low HDL
[66,75,76]. Often patients pretransplantation have low choles-
terol levels due to the impaired hepatic synthetic function in ESLD
[66,75,77]. The prevalence of dyslipidemia in
post-LT patients has been found to range from 45% to 71%
[66,73,75,76]. Patel et al. found that the median time
after LT to develop dyslipidemia was 1.5 years with total cholesterol and serum triglyceride level changes great-
est within the first two years
[76]. Risk factors for development of dyslipidemia after transplantation include age,
genetic predisposition, donor factors, proteinuria, obesity, antihypertensive therapy, prednisone dosage, diabetes
mellitus, and treatment with sirolimus
[73,75].
Several immunosuppressants have been linked to promoting dyslipidemia by interfering with lipid metabo-
lism. There is a strong association between corticosteroid usage and development of hyperlipidemia in this LT
population, but studies have shown that alternate-day steroid dosing can improve serum lipid levels
[73,78,79].
Furthermore, cyclosporine treated patients have been found to have a higher occurrence of hyperlipidemia and
hypertriglyceridemia compared to tacrolimus treated patients and switching from cyclosporine to tacrolimus has
been shown to improve hyperlipidemia
[66,67,73,75]. Patients treated with sirolimus, an mTORi that can also be
combined with a CNI, demonstrated significant dyslipidemia which decreased when used in conjunction with
tacrolimus versus cyclosporine
[66,73,75].
Diabetes mellitus
New-onset diabetes mellitu s is a recognized complication of all solid organ transplantation and has a preva-
lence of 13%28% in the first year following LT
[67,75,80,81]. There are several factors associated with the devel-
opment of post-LT diabetes including immunosuppressive regimens, high dose steroids required for rejection
episodes, the surgical stress itself, and infections
[67,80,82]. Studies have shown that Hepatitis C infection, cyto-
megalovirus infection within the first year of transplantation, pretransplant diabetes, and male sex are risk factors
336 20. Predicting cardiovascular complications after liver transplantation
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for developing new-onset diabetes mellitus [66,75]. LT patients are usually treated with insulin in the pretrans-
plant and immediate post-transplantation periods, but Watt et al. showed that persistent hyperglycemia after six
months post-LT with new-onset diabetes mellitus was associated with a long-term risk of death and increased
risk of sustained diabetes after transplantation
[67,83].
Immunosuppressive regimens, specifically those involving corticosteroids and CNIs, which are nearly univer-
sally used as immu nosuppression in LT, increase the risk of new-onset diabetes mellitus after transplant. Rapid
steroid withdrawal after LT decreases the risk of developing diabetes and is practiced by most centers
[66,73,75,80]. In general, corticosteroids and CNIs lead to diabetes through mechanisms of insulin resistance and
increased gluconeogenesis
[66]. Vesco et al.’s study in renal transplant patients who received intravenous pulsed
prednisolone for antirejection therapy suggested that pulsed steroid therapy may also play a significant role in
the onset of new, post-transplant diabetes
[82]. Additionally, CNIs have a diabetogenic effect by directly damag-
ing pancreatic islet cells
[66,75]. Studies have shown that the risk of new-onset diabetes mellitus after transplanta-
tion is much higher with tacrolimus than with cyclosporine
[84]. There is not a clear relationship between
tacrolimus dose reduction and improvement in diabetes risk, thus change in immunosuppression regimen should
only be done after considering the full risks and benefits of alternative immunosuppression regimens
[80].
Abdominal obesity
There is an increased risk for obesity in the post-LT population. Of pretransplant patients that are listed,
15%30% of patients are obese though these measurements may not be reflective of a true dry weight due to the
presence of ascites in many patients with ESLD. The rates of obesity in the post-LT population range between
20% and 68%
[85]. There is also an increased risk of cardiovascular events in obese compared to nonobese post-
transplantation patients within the first five years
[66,67,75]. After LT, there are several factors that can contribute
to weight gain including immunosuppression, particularly corticosteroids, and reversal of the catabolic state
associated with cirrhosis. As discussed above, high dose corticosteroids are prescribed immediately post-LT as
induction therapy and for treatment of acute rejection, when present. These high dose steroids predispose to
weight gain, so it is important to rapidly taper steroids when appropriate to avoid these complications.
Furthermore, cyclosporine use has been associated with higher weight gain 1-year post-transplantation than
tacrolimus, but differences have not been shown to persist beyond 1 year
[67,75,86].
Renal disease/chronic kidney disease
Chronic kidney disease (CKD) and chronic renal failure are shown to have a high prevalence after LT which is
in part due to CNIs that are frequently used in immunosuppressive regimens
[74]. CKD is associated with
increased cardiovascular risk in the general population, but further studies must be conducted to explore the
relationship between worsening renal function post-LT and risk of major cardiovascular events
[6]. VanWagner
et al. demonstrated in a large, retrospective cohort study that the degree and pattern of change in estimated glo-
merular filtration rate (GFR) could better elucidate the risk of adverse cardiovascular outcomes in this patient
population than renal function at the time of transplant. At the time of this study, risk prediction models only
took into account baseline GFR prior to LT, but this study considered dynamic GFR changes in the
post-transplantation period. It demonstrated that the most significant independent predictor of cardiovascular
complications within the first year post-LT was the group with the most rapidly decreasing GFR within that first
year
[24].
Identified future areas of study in liver transplantation complications
Peripheral vascular disease
PVD is an entity that is included in the definition of CVD, but there is scarce data in regard to PVD and its place in
the natural history of LT complications. It is conceivable and likely that the complications of metabolic syndrome can
also lead to PVD, but studies must be conducted in this patient population to draw these conclusions.
Valvular heart disease
VHD is also encompassed in the definition of CVD, but VHD and its relationship to the natural history of LT reci-
pients are not well-described in literature. Though there are a few studies describing VHD in LT candidates, the area
of focus in these studies do not include the development of, or progression of, VHD after LT. Most available studies
focus on management of valvular disease at various time points in the evaluation of the pre-LT patient and the
337Natural history and timing of cardiovascular events in liver transplantati on
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perioperative complications during LT in patients with preexisting valvular disease [8790]. Further studies must be
conducted in evaluating the long-term outcomes of VHD in LT recipients.
Algorithms and risk calculators for prediction of cardiovascular risk after liver transplantation
The goals of cardiovascular risk assessment in liver transplant candidates are to: (1) determine intraoperative and
immediate postoperative survival and (2) estimate long-term cardiovascular survival to avoid futility of liver trans-
plant and maximize the benefit of a scarce donor organ. In the pretransplant setting, most risk models for noncardiac
surgery were evaluated in populations without ESLD and not created for the purpose of risk stratification of patients
undergoing LT. In addition, most current risk algorithms for cardiovascular risk prediction after noncardiac surgery
are designed to detect underlying ischemic heart disease and may not be calibratedtoappropriatelyriskstratifyliver
transplant candidates, in whom the majority of early postoperative events are nonischemic in origin
[4,24,59,91].
Therefore risk stratification tools and algorithms that incorporate ESLD related, LT surgery specific, and comorbidity
related predictors are of utmost importance to improve risk stratification for CVD related morbidity and mortality
and to aid with recipient selection and recipient-donor matching. Risk models and tools can be divided into those
that predict general CVD risk and those specifically designed to predict CV risk after surgery.
Liver specific risk predictors
The MELD score is a disease severity scoring system initially developed to predict mortality in patients unde r-
going transjugular intrahepatic portosystemic shunt (TIPS), and in the Un ited States is used to prioritize patients
for liver transplant
[92]. It is calculated using international norm alized ratio (INR), total bilirubin (mg/dL), serum
creatinine (mg/dL), need for hemodialysis $ 2 times a week and recently, also includes serum sodium
(mmol/L) (e.g, MELD-Na Score). Scores range from 640 with higher scores correlating with worse outcomes
and higher 3-month mortality
[91]. The Child-Tur cotte-Pugh score (CTP) is a classification system that categorizes
patients into 3 classes: A, B, or C bas ed on albumin (g/dL), total bilirubin (mg/dL), prothrombin time-INR,
severity of ascites (none, mild, severe), and grade of encephalopathy (none, Grade III, Grade IIIIV). CTP Clas s
correlates with 1- and 2-year patient survival
[91]. Both MELD and CTP capture the severity of liver dysfunction
which impacts both overall mortality as well as postoperative mortality
[91]. These scores are limited as they do
not incorporate risk factors related to LT or any risk factors related to the existence of comorbidities that may
impact postoperative survival.
Nonsurgical general cardiac risk assessment tools
Several prognostic risk scores have been created and validated to predict the development of CVD in the general
population (
Table 20.3). These include the German Prospective Cardiovascular Munster Study (PROCAM), the
European Systemic Coronary Risk Evaluation Project (SCORE), the Framingham Risk Score (FRS), the American
Heart Association (AHA)/ American College of Cardiology (ACC) pooled cohort equations (PCE), and the
Reynolds Risk Score (RRS)
[93]. Of these, the FRS is the most frequently used in the general population and is a
multivariable risk prediction algorithm that predicts the 10-year risk of fatal or nonfatal coronary events
[9496].In
the Framingham Heart Study, CVD was defined as CHD, cerebrovascular events, peripheral artery disease, and HF
[9496]. The FRS is calculated using sex, age, BMI, systolic blood pressure, use of antihypertensive medications,
total and HDL cholesterol, cigarette smoking status, and diabetes mellitus
[9496]. This score has moderate dis-
crimination for mortality and cardiovascular events in LT candidates with a C statistic ranging from 0.76 to 0.79
[93]. A study by Di Maira et al. conducted in Spain demonstrated that at 1 year post-LT, both the number of partici-
pants with moderate-high FRS had increased as well as the median FRS score, which is likely attributable to
increases in DM, hypertension, dyslipidemia, and development of metabolic syndrome
[93]. Study participants
identified with high FRS were more likely to develop CVD after LT. In multivariate analysis, FRS was significantly
associated with the development of cardiovascular events with a hazard ratio 1.06 [95% Confidence Interval
(1.021.10; P 5 0.0002)]
[93]. This study also demonstrated an inverse relationship between FRS at time of LT and
patient survival and 1, 3, and 5 years. After the first year from time of liver transplant, participants with a high FRS
had significantly worse survival compared to participants with low and moderate risk FRS (P 5 0.004)
[93].
338 20. Predicting cardiovascular complications after liver transplantation
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The R RS is a risk calculator derived using a cohort of 25,000 US women that uses the traditional CVD risk
factors used in the FRS and also includes parental family history of premature CHD and high-sensitivity C-
reactive protein (CRP). It has been validated and calibrated for both men and women and has been shown to
be better at predicting CVD events compared to FRS
[97]. The RRS has not specifically been applied to LT can-
didates or recipients. Another commonly used risk calculator is the PCE Risk Calculator developed by the
ACC and AHA to predict 10-year and lifetime risk of atherosclerotic cardiovascular disease (ASCVD) events.
This calculator is commonly used to provide risk thresholds to guide initiation of statin therapy to lower CVD
risk
[96]. As the data for the discrimination of these scores is limited and have not undergone validation and
calibration in the LT population, these scores have significant shortcomings as a useful predictive tool in LT.
Additionally, these scores were developed to identify coronary events while most earlyCVDmortalityafterLT
is attributable to noncoronary events potentially making the FRS, RRS, and PCE less relevant for early ri sk
stratification.
TABLE 20.3 Nonsurgical general cardiac risk assessment tools.
Risk score Components Predicted outcomes
Framingham risk score Age
Sex
Smoker
Total cholesterol
HDL cholesterol
Systolic BP
Use of antihypertensives
Diabetes
10-year risk of fatal or nonfatal coronary events
*
Reynolds risk score Age
Sex
Smoker
Total cholesterol
HDL cholesterol
Systolic BP
Parental history of premature
CHD
hsCRP
10-year risk of fatal or nonfatal coronary events
*
Pooled cohort equations risk
calculator
Age
Sex
Smoker
Total cholesterol
HDL cholesterol
Systolic BP
Use of antihypertensives
Race
Diabetes
10-year risk of atherosclerotic cardiovascular disease events
*
Prospective cardiovascular
munster
Age
Smoker
LDL cholesterol
HDL cholesterol
Triglycerides
Systolic BP
Family history of premature
MI
Diabetes
10-year risk of acute coronary events (myocardial infarction, sudden
cardiac death)
Systematic coronary risk
evaluation
Age
Sex
Smoker
Total cholesterol
Systolic BP
10-year risk of CVD mortality
*Major coronary event defined as occurrence of sudden cardiac death, fatal or nonfatal myocardial infarction.
BP, blood pressure; CHD, coronary heart disease; hsCRP, high sensitivity C-reactive protein; HDL, high density lipoprotein; LDL, low density lipoprotein.
339Algorithms and risk calculators for prediction of cardiovascular risk after liver transplantation
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Serum biomarkers
Several serum biomarkers may serve a role in predicting CVD, in general (Table 20.4). There are numerous
serum biomarkers under evaluation and a detailed review of all of these are beyond the scope of this review.
However, a few biomarkers have been evaluated in the context of LT. Serum troponin I and T are structural pro-
teins released after cardiac myocyte death and are the most sensitive and specific markers of myocardial injury
and/or death
[2,98,99]. Serum troponin levels have been found to be elevated in up to 25%30% of patients with
ESLD who are asymptomatic
[2]. Asymptomatic elevations in troponin may be a marker of subclinical CVD and
microvascular disease that may not be detected even with stress test. It is hypothesized that the stress of trans-
plantation may unmask or even accelerate this microvascular disease into overt clinical CVD. Pretransplant tro-
ponin I elevation ( . 0.07 ng/mL) has been found to be associated with post-transplant de novo CVD and
mortality, and early post-LT troponin elevation ( . 0.1 ng/mL) is associated with higher 30-day mortality
[2,98].
Troponin may not only be elevated in situations from myocardial necrosis in the setting of myocardial ische-
mia and infarction but may also be elevated in other cardiac conditions including AF, structural cardiac abnor-
malities, HF, and subclinical coronary atherosclerosis
[99]. High sensitivity assays to detect troponin have been
developed to detect troponin I and T at lower concentrations with the goal of early detection of myocardial injury
[99]. A study by Willeit et al. conducted a systematic review and meta-analysis of 154,052 participants without
prior history of CVD and found that 80% of participants had detectable levels of troponin I and T using a high
sensitivity assay. Participants with troponins in the highest tertile were at 43% increased risk of any CVD, 59% of
increased risk of CHD, and 67% increased risk of CVD related mortality
[99]. The use of high sensitivity troponin
has not been well studied in the liver transplant population.
CRP is an acute phase reactant and an inflammatory marker that correlates with the presence of metabolic syn-
drome and CVD
[100]. As previously discussed, CRP is a component of the RRS as it has been shown to be sig-
nificantly associated with the incidence of CHD and CVD
[97]. However, CRP has not been found to correlate
with CVD in the post liver transplant population
[101]. Because CRP is produced by hepatocytes, ESLD may
result in decreased production of CRP, and it may not be a relevant biomarker in risk stratifying patients under-
going LT.
Brain natriuretic peptide (BNP) is a cardiac hormone synthesized as a prohormone by myocytes in the ventricles
[102]. The prohormone, pro-BNP, is cleaved and results in conversion to the physiologically active form, BNP [102].
BNP has been well studied in the context of HF and has been found to play a role by exerting hemodynamic and
remodeling effects. Zardi et al. demonstrated that BNP levels were elevated in CCM and that the BNP correlated
with QT time, low ventricular stroke volume, and increased left ventricular mass
[103]. Pretransplant levels of BNP
may actually serve as a predictive biomarker for the development of systolic HF after liver transplant
[104].
Cardiac titin is a sarcomere protein that is responsible for the elastic recoil of cardiac myocytes
[105]. Thus it
plays a role in left ventricular filling during diastole as well as length dependent activation which helps mediate
the Frank-Starling relationship curve
[105]. As altered diastolic relaxation is a hallmark of CCM, this protein may
be an interesting target for future research.
TABLE 20.4 Serum biomarkers and their predictive role in liver transplantation.
Serum biomarker Physiology Predictive role
Troponin I, T Sensitive and specific marker of myocardial
injury and death
Elevated in ESLD, may be marker of subclinical CVD
High sensitivity
troponin
Early detection of myocardial injury Not well studied in ESLD
C-reactive protein Acute phase reactant, inflammatory marker. May be
marker of metabolic syndrome, CVD
Unclear role in ESLD
Brain natriuretic
peptide, pro-BNP
Prohormone secreted by ventricles, marker in heart failure Elevated in cirrhotic cardiomyopathy, may be predictive
of post-LT systolic heart failure
Titin Sarcomere protein, implicated in diastolic
filling, Frank-Starling curve
Unclear role in ESLD
CVD, cardiovascular disease; ESLD, end-stage liver disease; LT, liver transplant.
340 20. Predicting cardiovascular complications after liver transplantation
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Surgical cardiac risk calculators
Perioperative cardiac events are a leading cause of death after noncardiac surgery. The Revised Cardiac Risk
Index (RCRI) is a widely used perioperative cardiac risk tool to help determine which patients are at high risk
for perioperative MI or cardiac arrest
[106]. The RCRI uses 6 variables (history of ischemic heart disease, HF,
stroke, insulin-dependent diabetes, CKD, high-risk surgery) to classify individuals as low, intermediate, or high
risk for perioperative cardiac complications in noncardiac surgeries. This score has several limitations. It was val-
idated using a cohort of only 4315 patients and the categorization of “high-risk surgeries” may not be applicable
today with advances in surgeries such as minimally invasive techniques
[106,107]. The RCRI has only moderate
discriminative ability with a receiver operator characteristic area under the curve of 0.76 and C statistic of 0.75.
Additionally, RCRI may not be an ideal risk tool for use in LT as the original study excluded ESLD patients
[107]. As the goal of the RCRI is to detect underlying ischemic heart disease, this score may be less relevant to
ESLD patients undergoing LT as CHD represents a smaller proportion of CVD complications (at 1 year) in this
population. A study by Park et al. investigated whether the RCRI in conjunction with the MELD score could
improve risk prediction of perioperative cardiac events. In multivariate analyses, RCRI and MELD were found to
be independent predictors of 30-day postoperative cardiac events
[108]. This study also demonstrated that
patients with higher MELD and RCRI scores had a higher rate of cumul ative cardiac events
[108]. When compar-
ing predictive ability, the model using both MELD and RCRI scores was significantly more predictive than the
model using MELD score alone
[108]. Therefore the RCRI could be a useful predictive risk tool if adapted to
include ESLD and transplant specific risk factors (Table 20.5).
TABLE 20.5 Surgical risk calculators.
Surgical cardiac risk calculators Variables Predicted outcome
Revised cardiac risk index (RCRI) Ischemic heart disease
Heart failure
Stroke
Insulin-dependent diabetes
Chronic kidney disease
High-risk surgery
Classifies individuals as low, intermediate,
high risk for perioperative cardiac complications
in noncardiac surgeries
MICA (MI or Cardiac Arrest) risk calculator Dependent functional status
Abnormal Cr
ASA class
Age
Type of surgery
Estimate of probability of perioperative MI
and cardiac arrest
American College of Surgeons National Surgical
Quality Improvement Program (ACS NSQIP)
Age
Sex
Functional status
Emergency case
ASA class
Steroid use for chronic condition
Ascites within 30 days prior to surgery
Systemic sepsis within 48 h prior to surgery
Ventilator dependent
Disseminated cancer
Diabetes
Hypertension
CHF 30 days prior to surgery
Dyspnea
Current smoker within 1 year
History of severe COPD
Dialysis
Acute renal failure
BMI
30-day risk of post-operative complications
Cr, creatinine; ASA, American Society of Anesthesiologists; CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease; BMI, body mass index.
341Algorithms and risk calculators for prediction of cardiovascular risk after liver transplantation
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Given the limitations in discriminat ive and predictive ability of the RCRI, Gupta et al. developed an interactive
risk calculator to identify risk factors associated with intraoperative and postoperative MI or cardiac arrest
(MICA)
[107]. They were able to identify five predictors of perioperative MI and cardiac arrest: type of surgery,
dependent functional status, abnormal creatinine, American Society of Anesthesiologists’ class, and increasing
age
[107]. The MICA risk calculator has a C statistic 0.88 [107]. In contrast to the RCRI, which stratifies patients
into low, medium, and high risk categories, the MICA risk calculator provides an estimate of an individual’s
MICA probability. The MICA risk calculator is able to both identify high risk patients and may help provide use-
ful information for patient-centered informed consent
[107]. This score has not yet been studied in the liver trans-
plant population.
The American College of Surgeons Nationa l Surgical Quality Improvement Program (ACS NSQIP) is a nation-
ally validated, risk-adjusted, outcomes-based program that aims to track post-transplant outcomes. This group
developed a surgical risk calculator to predict 30-day postoperative risks and to aid in shared decision making
with patients. The ACS NSQIP risk calculator uses 21 variables including type of surgery, American Society of
Anesthesiology class, and functional status to calculate the risk of multiple postoperative complications including
cardiac complications
[109]. This model demonstrated good discrimination with C statistics ranging from 0.806 to
0.944; specifically for cardiac complications, the C statistic was 0.895
[109]. Although this risk calculator was vali-
dated using the data from more than 1.4 million patients at 393 different hospitals, LT is a relatively uncommon
surgical procedure and likely comprised only a small proportion of the data. There is little data validating this
risk score and its ability to predict CVD in LT.
Individual predictors of perioperative cardiovascular disease mortality after liver transplantation
As most currently available CVD risk calculators (see Table 20.3) are not adequately calibrated to risk stratify
ESLD patients undergoing LT, this has necessitated clinical investigation into the identification of individual risk
factors for prediction of CVD risk in this population.
Several studies have identified risk factors for major post-LT cardiovascular events (
Table 20.6). Safadi et al.
conducted a retrospective cohort study aimed to identify prognostic marker s of perioperative cardiac outcomes
in older, intermediate coronary artery risk patients undergoing LT to better risk stratify this population
[111].In
the 30-day postoperative period, pretransplant history of CAD and stroke were found to significantly increase
the incidence of perioperative cardiac outcomes. In multivariate analysis, history of stroke was associated with
postoperative MI, increased interventricular septal thickness was associated with death and prior history of
CAD, stroke, and postoperative sepsis were significantly associated with the combined outcome of MI and death.
A positive noninvasive stress test also predicted early post op mortality and a normal stress test had a high nega-
tive predictive value for adverse outcomes in LT candidates
[111]. In the Safadi study, only a subset of partici-
pants underwent invasive testing with cardiac catheterization and subsequent revascularization; however, due to
small numbers, this study was not able to evaluate if revascularization affected perioperative outcomes. Multiple
recent studies have demonstrated that patients with revascularized CAD have outcomes that are equivalent to
liver transplant recipients without CAD
[58,113,114]. However, protocols for detection of CAD vary widely by
transplant center and multicenter pr ospective investigation into identifying appr opriate preoperative risk stratifi-
cation for patients undergoing LT is sorely needed.
A study by Albeldawi et al. found that the development of components of metabolic syndrome after LT were
predictive of an increased risk of CVD
[1]. Compared to study participants who did not experience a cardiac
event after LT, participants who had a cardiac event post-LT were more likely to have post-transplant metabolic
syndrome, DM, HTN, hypertriglyceridemia, low HDL, and obesity. In multiva riate analysis, CVD risk was most
strongly associated with older age at time of LT, male sex, post-transplant diabetes, post-transplant hypertension,
and the use of mycophenolate mofetil as immunosuppression. Post-transplant metabolic syndrome may be
related to the immunosuppressive regimens as well as the pathophysiology of the underlying liver disease.
Specifically, participants whose indication for LT was NASH cirrhosis had a significantly higher risk of CVD at
1- and 3- years post-LT compared to other etiologies. This study posits that more rigorous pre transplant cardiac
risk stratification may be indicated in this population and that post-transplant management of metabolic syn-
drome is necessary to prevent CVD.
342 20. Predicting cardiovascular complications after liver transplantation
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Risk models for prediction of perioperative cardiovascular disease mortality after liver
transplantation
Several studies have attempted to create risk models to predict the incidence of CVD after LT (Table 20.6).
Umphrey et al. found that a model that included maximum achieved heart rate during preoperative dobutamine
stress echo and MELD score may predict CVD up to 4 months after LT
[112]. This study’s main limitations were
its small sampl e size (n 5 157), lack of C statistic reporting, and limited generalizability. Josefsson et al. created a
point-based model using renal impairment, prolonged QTc, and age .52 to predict post-LT cardiac events
among 202 patients in Sweden
[110]. This study had a C statistic 0.73 for 1 year CVD mortality, arrhythmia, and
TABLE 20.6 Identified risk factors and associated cardiovascular disease outcomes after liver transplantation.
Risk factor Outcome Studies
Demographics
Male sex Major CV event
a
[1]
Age Major CV event
a
, 1-year CVD mortality, 30-day CVD mortality [1,3,110]
Pretransplant risk factors
CAD Postoperative MI
[111]
Atrial fibrillation Major CV event
a
[4]
Stroke Postoperative MI, major CV event
a
[4,111]
Interventricular septal thickness 30-day mortality [111]
Positive noninvasive stress test Early postoperative mortality, CVD mortality, major CV event
a
[111,112]
NASH Major CV event
a
[1,4]
MELD CVD mortality, major CV event
a
, 30-day CVD mortality [3,112]
Prolonged QTc CVD mortality, major CV event
a
[110]
Renal impairment CVD mortality, major CV event
a
[4,110]
Hospitalization status 30-day CVD mortality [3]
ICU status 30-day CVD mortality [3]
Respiratory failure on ventilator 30-day CVD mortality [3]
History of PVT 30-day CVD mortality [3]
Transplant risk factors
Donor BMI 30-day CVD mortality
[3]
Cold ischemia time 30-day CVD mortality [3]
National organ sharing 30-day CVD mortality [3]
Postoperative risk factors
Metabolic syndrome Major CV event
a
[1]
Diabetes Major CV event
a
[1]
Hypertension Major CV event
a
[1]
Hypertriglyceridemia Major CV event
a
[1]
Low HDL Major CV event
a
[1]
Obesity Major CV event
a
[1]
Mycophenolate Major CV event
a
[1]
a
Major CV event defined as acute coronary syndrome, congestive heart failure, ischemic stroke, peripheral artery disease, arrhythmias.
BMI, body mass index; CAD, coronary artery disease; CV, cardiovascular; CVD, cardiovascular disease; HDL, high density lipoprotein; ICU, intensive care unit;
MELD, model for end-stage liver disease; NASH, nonalcoholic steatohepatitis; PVT, portal vein thrombosis.
343Algorithms and risk calculators for prediction of cardiovascular risk after liver transplantation
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