Improving the Prediction of Mortality in the High Model for End-Stage Liver Disease Score Liver Transplant Recipient: A Role for the Left Atrial Volume Index

The role of echocardiographic assessment for the risk of adverse events in liver transplant recipients: A systematic review and meta-analysis

BACKGROUND & AIMS

Echocardiographic findings may provide valuable information about the cardiac conditions in cirrhotic patients waiting for liver transplantation (LT). However, data on the ability of the different echocardiographic parameters to predict post-transplant risk of mortality are scarce and heterogeneous. This systematic review evaluates the role of different echocardiographic features as predictors of post-LT mortality. A meta-analysis was also performed according to the observed results.

METHODS

A systematic review was conducted according to PRISMA guidelines. Medline (PubMed) database was searched through February 2023 for relevant published original articles reporting the prognostic value of echocardiographic findings associated with outcomes of adult LT recipients. The risk of bias in included articles was assessed using ROBINS-E tool. Methodological quality varied from low to high across the risk of bias domains.

RESULTS

Twenty-three studies were identified after the selection process; ten were enrollable for the meta-analyses. According to the results observed, the E/A ratio fashioned as a continuous value (HR = 0.43, 95%CI = 0.25-0.76; P = 0.003), and tricuspid regurgitation (HR = 2.36, 95%CI = 1.05-5.31; P = 0.04) were relevant predicting variables for post-LT death. Other echocardiographic findings failed to merge with statistical relevance.

CONCLUSION

Tricuspid regurgitation and left ventricular diastolic dysfunction play a role in the prediction of post-LT death. More studies are needed to clarify further the impact of these echocardiographic features in the transplantation setting.

Hemodynamic and Clinical Determinants of Left Atrial Enlargement in Liver Transplant Candidates

New-onset heart failure is a frequent complication after orthotopic liver transplantation (OLT). Left atrial enlargement (LAE) may be a sign of occult left heart disease. Our primary objective was to determine invasive hemodynamic and clinical predictors of LAE and then investigate its effect on post-transplant outcomes. Of 609 subjects who received OLT between January 1, 2010, and October 1, 2018, 145 who underwent preoperative right-sided cardiac catheterization and transthoracic echocardiography were included. Seventy-eight subjects (54%) had pretransplant LAE. Those with LAE had significantly lower systemic vascular resistance with higher cardiac and stroke volume index (61.0 vs 51.7 ml/m²; p <0.001), but there was no difference in pulmonary artery wedge pressure. There was a linear relation between left atrial volume index and stroke volume index (R² = 0.490, p<0.001), but not pulmonary artery wedge pressure. The presence of severe LAE was associated with a reduced likelihood (hazard ratio = 0.26, p = 0.033) of reaching the composite end point of new-onset systolic heart failure, heart failure hospitalization, or heart failure death within 12 months post-transplant. There was also a significant reduction in LAE after transplantation (p = 0.013). In conclusion, LAE was common in OLT recipients and was more closely associated with stroke volume than left heart filling pressures. The presence of LAE was associated with a reduced likelihood of reaching composite outcomes and tended to regress after transplant.

Training and Validation of Deep Neural Networks for the Prediction of 90-Day Post-Liver Transplant Mortality Using UNOS Registry Data

Prediction models of post-liver transplant mortality are crucial so that donor organs are not allocated to recipients with unreasonably high probabilities of mortality. Machine learning algorithms, particularly deep neural networks (DNNs), can often achieve higher predictive performance than conventional models. In this study, we trained a DNN to predict 90-day post-transplant mortality using preoperative variables and compared the performance to that of the Survival Outcomes Following Liver Transplantation (SOFT) and Balance of Risk (BAR) scores, using United Network of Organ Sharing data on adult patients who received a deceased donor liver transplant between 2005 and 2015 (n = 57,544). The DNN was trained using 202 features, and the best DNN's architecture consisted of 5 hidden layers with 110 neurons each. The area under the receiver operating characteristics curve (AUC) of the best DNN model was 0.703 (95% CI: 0.682-0.726) as compared to 0.655 (95% CI: 0.633-0.678) and 0.688 (95% CI: 0.667-0.711) for the BAR score and SOFT score, respectively. In conclusion, despite the complexity of DNN, it did not achieve a significantly higher discriminative performance than the SOFT score. Future risk models will likely benefit from the inclusion of other data sources, including high-resolution clinical features for which DNNs are particularly apt to outperform conventional statistical methods.

The decreasing predictive power of MELD in an era of changing etiology of liver disease

The field of liver transplantation has shifted considerably in the MELD era, including changing allocation, immunosuppression, and liver failure etiologies, as well as better supportive therapies. Our aim was to evaluate the predictive accuracy of the MELD score over time. The United Network for Organ Sharing provided de-identified data on 120 156 patients listed for liver transplant from 2002-2016. The ability of the MELD score to predict 90-day mortality was evaluated by a concordance (C-) statistic and corroborated with competing risk analysis. The MELD score's concordance with 90-day mortality has downtrended from 0.80 in 2003 to 0.70 in 2015. While lab MELD scores at listing and transplant climbed in that interval, score at waitlist death remained steady near 35. Listing age increased from 50 to 54 years. HCV-positive status at listing dropped from 33 to 17%. The concordance of MELD and mortality does not differ with age (>60 = 0.73, <60 = 0.74), but is lower in diseases that are increasing most rapidly-alcoholic liver disease and non-alcoholic fatty liver disease-and higher in those that are declining, particularly in HCV-positive patients (HCV positive = 0.77; negative = 0.73). While MELD still predicts mortality, its accuracy has decreased; changing etiology of disease may contribute.