Predicting cardiovascular complications after liver transplantation
Bibliographic record
Abstract
Recipients of orthotopic liver transplantation (OLT) are at increased risk of developing cardiovascular complications.1 Indeed, such complications occur in 25% to 70% of patients after OLT.2 For example, radiographic evidence of pulmonary edema is observed in 22% to 56% of transplant recipients during the first postoperative month.2 Moreover, mortality associated with cardiac causes accounts for up to 7% of deaths in the early- to medium-term posttransplant period.2 In some centers, all cardiovascular events are the third-leading cause of death after infection and rejection. Most liver transplant recipients have advanced cirrhosis. Such patients' cardiovascular status before transplantation is generally abnormal, so they may respond poorly to the stress of transplantation. Moreover, as a result of immunosuppressive drug therapy or other reasons, several cardiovascular risk factors, including hypertension, diabetes, hyperlipidemia, and obesity, are prevalent in OLT recipients.1 Because of this situation, the ability to predict which individuals will develop cardiovascular events during and after liver transplantation is hugely important in the patient selection process. Transplant candidates undergo a rigorous pretransplant workup that includes a careful cardiovascular history and investigations such as standard or dobutamine stress echocardiography, nuclear heart scans, and even coronary angiography if there is any lingering doubt about the presence of atherosclerotic coronary artery disease (CAD). Despite all this, every transplant center sees significant morbidity and mortality from cardiovascular complications in transplant recipients, including some with a puzzling, inexplicably severe event such as myocardial infarction or heart failure in the absence of any known predisposing risk factor or background. Cardiovascular events after transplantation can be broadly categorized into 4 major areas: CAD, peripheral vascular disease (particularly stroke), heart failure, and arrhythmia. Some of the heterogeneity in the literature is easily explained by the variable inclusion of these complications. More recently, at least some of the previously unexplained cases of heart failure after transplantation have been suspected to be due to a syndrome known as cirrhotic cardiomyopathy.3 In the future, consensus definitions of exactly what constitutes cardiovascular complications [including subdivisions into cardiac, coronary vascular, and peripheral vascular complications (stroke)] would vastly decrease the heterogeneity of results and thus allow significant progress in the field. Liver transplantation stresses the cardiovascular system,4, 5 and limited cardiac reserve preoperatively may be associated with poor outcomes postoperatively.6 Several previous studies have examined predictive factors for cardiovascular events in OLT recipients. Dec and colleagues7 found that cardiovascular complications occurred in more than 70% of liver transplant recipients. A multivariate analysis showed that preexisting cardiac disease and older age at transplantation were the only independent predictors of a major complication. A recent study8 focused on the development of CAD events in the perioperative period (defined as up to 30 days after transplantation) and found that a history of stroke, CAD, postoperative sepsis, and increased interventricular septal thickness were markers of poor perioperative cardiac outcomes. Perioperative beta-blocker usage was significantly protective. Our recent retrospective study9 included 197 patients who underwent OLT; 82 of these patients (42%) suffered 1 or more cardiovascular complications during the first 6 postoperative months. Radiographically or clinically evident pulmonary edema was the commonest complication. After adjustments for age and sex, a multivariate analysis indicated that the independent predictors of cardiovascular complications were an intraoperative cardiovascular event, a preoperative history of cardiac disease or hypertension, and the integrated Model for End-Stage Liver Disease (MELD) score (the MELD score plus adjustments for age and serum sodium). Neither the original MELD score nor the MELD score adjusted for serum sodium was an independent predictor of cardiovascular complications. There continues to be great interest in finding a preoperative cardiovascular or imaging test that provides accurate predictive ability for postoperative cardiovascular events. Using coronary angiography as a gold-standard test, Davidson and coworkers10 evaluated single-photon emission computed tomography (SPECT) scanning. They found that the sensitivity of SPECT imaging was only 37%, and the specificity was 63%. The positive predictive value was only 22%, and the negative predictive value was 77%. It is, therefore, clear that SPECT scanning is unreliable as a predictive test for OLT patients. The transplantation guidelines of the American Association for the Study of Liver Diseases recommend an evaluation for CAD if liver transplant candidates are more than 50 years old, are diabetic, are chronic smokers, or have a clinical or family history of heart disease.11 Those guidelines recommend dobutamine stress echocardiography. However, the performance characteristics of that test are not well established in this population. A positive result with dobutamine stress echocardiography should be confirmed with cardiac catheterization. Some investigators have used different combinations to create evaluation systems. The combinations include donor age, recipient age, creatinine, bilirubin, prothrombin time, ischemia time, and so forth.12, 13 These scoring systems are based mostly on MELD variables. There is a correlation between the degree of liver failure and the extent of cardiovascular abnormalities (particularly cirrhotic cardiomyopathy and hyperdynamic circulation). Therefore, MELD components may predict cardiovascular events after liver transplantation. However, some of the components reported by Brandao et al.13 in these scoring systems rely on postoperative data that are typically unavailable before transplantation; this limits their usefulness. Other shortcomings of previous studies of the prediction of cardiovascular complications include their retrospective nature, insufficient sample sizes, and single-center design as well as the fact that some are now more than 15 years old, so newer management/diagnostic modalities were not used. It is obvious that patients with overt evidence of heart disease are easily identified during the pretransplant selection process. However, because of the marked peripheral vasodilatation of end-stage cirrhosis that autotreats a potentially latent heart failure, cardiac abnormalities in patients with cirrhosis are usually subclinical. Patients with subclinical or asymptomatic heart disease create the greatest challenge in pretransplant risk stratification. A simple and reliable marker for identifying such patients has been unavailable until now. In popular movie culture, many world-threatening problems have been resolved by James Bond, Agent 007. In a case of life imitating art, this number (0.07) is coincidentally the exact demarcation point of abnormality (in nanograms per milliliter) of the troponin I assay used by Coss et al.14 in their study published in this issue of Liver Transplantation. A multivariate analysis of 230 transplant recipients showed that an abnormal pretransplant troponin I level (>0.07 ng/mL) was 1 of only 4 factors predicting postoperative cardiovascular complications up to 8 years after transplantation. The other 3 factors were a previous cardiovascular history, smoking, and pretransplant diabetes. These 3 factors have been previously described in some studies, but the troponin I result is novel. Pretransplant troponin I levels were increased in approximately one-quarter of their patients and correlated with markers of cardiac dysfunction/disease, such as left ventricular wall thickness and a low ejection fraction. Table 3 in Coss et al.'s article14 details the 7 patients who suffered perioperative cardiovascular events. In this group, 2 cases illustrated the aforementioned unpredictable and often inexplicable occurrence of cardiovascular events and the potential utility of troponin I. A 19-year-old woman with only diabetes as a risk factor but no smoking or cardiovascular history and a normal echocardiogram inexplicably developed congestive heart failure. A 43-year-old woman with a smoking history but no other risk factor and again a normal echocardiogram suffered fatal cardiac arrest. For both, elevated troponin I levels were the only clue to underlying cardiac dysfunction or disease. Why should an abnormal troponin I value predict cardiovascular outcomes after transplantation? Both troponin I and T isoforms are elaborated by cardiomyocytes in response to conditions that injure or severely stress the heart, such as ischemia, ventricular dilatation or failure, cardiomyopathy, and inflammation.15 In contrast to the troponin T isoform, the I isoform is not dependent on glomerular filtration for elimination and is thus unaffected by renal dysfunction. In Coss et al.'s study,14 neither troponin T nor other serum markers of inflammation such as C-reactive protein showed any predictive value. On the other hand, troponin I as a marker perhaps of cirrhotic cardiomyopathy may somehow indicate latent cardiac dysfunction that is not recognized by conventional screening methods. The limitations of this study, as the authors noted, are its retrospective nature and relatively small number of patients. The latter means a risk of a type 2 error; other studies have demonstrated that MELD scores and renal dysfunction are associated with cardiac complications after OLT.9, 12, 13 Another limitation is that the authors did not calculate the sensitivity, specificity, positive predictive value, or negative predictive value of the troponin I level. Finally, it might have been interesting to determine if other serum markers of cardiac distress or dysfunction, such as B-type or brain natriuretic peptide and pro-brain natriuretic peptide, are similarly predictive. The cardiac calcium score, also called the coronary artery calcium (CAC) score, uses computerized tomography to measure the buildup of calcium in the arterial wall plaque. CAC scoring has been most thoroughly evaluated in asymptomatic patients with an intermediate risk of major adverse cardiovascular events as predicted by the Framingham risk score. In this population, the annual risk of CAD death or myocardial infarction is 0.4% with a CAC score of 0 to 99, 1.3% with a CAC score of 100 to 399, and 2.4% with a CAC score higher than 399.16 The relative risk of all coronary disease events is 1.9 with a CAC score of 1 to 99, 10.2 with a CAC score of 100 to 399, and 26.2 with a CAC score higher than 399.17 This diagnostic modality merits examination in candidates for liver transplantation. Overall, the ability to identify patients at the highest risk of death after liver transplantation has been improved over the last several years. However, our predictive ability remains relatively weak, so studies such as this one will help tremendously. Because cardiovascular events are often fatal, using a simple marker such as serum troponin I, if it is proven to be valid in larger prospective studies, will help us to better identify and select patients who will do well after transplantation. Better prediction and recipient selection will thus ultimately reduce mortality so that these patients, like Agent 007, can “die another day.” CAC, coronary artery calcium; CAD, coronary artery disease; MELD, Model for End-Stage Liver Disease; OLT, orthotopic liver transplantation; SPECT, single-photon emission computed tomography.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".