Review of interactions between high-risk pediatric heart transplant recipients and marginal donors including utilization of risk score models

Pediatric heart transplantation: Looking forward after five decades of learning

Heart transplantation has become the standard of care for pediatric patients with end-stage heart disease throughout the world. Since the first transplant was performed in 1967, the number of transplants has grown dramatically with 13 449 pediatric heart transplants being reported to The International Society of Heart and Lung Transplant (ISHLT) between January 1992 and June 30, 2018. Outcomes have consistently improved over the last few decades, specifically short-term outcomes. Most recent survival data demonstrate that recipients who survive to 1-year post-transplant have excellent long-term survival with more than 60% of those who were transplanted as infants being alive 25 years later. Nonetheless, the rates of graft loss beyond the first year have remained relatively constant over time; driven primarily by our poor understanding and lack of treatments for chronic allograft vasculopathy (CAV). Acute rejection, CAV, graft failure, and infection continue to be the major causes of death within the first 5 years post-transplant. In addition, renal dysfunction, malignancy, and the need for re-transplantation remain as significant issues that require close follow-up. Looking forward, key challenges include improving donor utilization rates (including donation after cardiac death (DCD) and the use of ex vivo perfusion devices), the development of non-invasive biomarkers for rejection, efforts to mitigate the long-term effects of immunosuppression, and prevention of CAV. It is not possible to cover the entire evolution of pediatric heart transplantation over the last five decades, but in this review, we hope to touch on key observations, lessons learned, and practice changes that have advanced the field, as well as glance ahead to the next decade.

Prediction of Outcomes After Heart Transplantation in Pediatric Patients Using National Registry Data: Evaluation of Machine Learning Approaches

BACKGROUND

The prediction of posttransplant health outcomes for pediatric heart transplantation is critical for risk stratification and high-quality posttransplant care.

OBJECTIVE

The purpose of this study was to examine the use of machine learning (ML) models to predict rejection and mortality for pediatric heart transplant recipients.

METHODS

Various ML models were used to predict rejection and mortality at 1, 3, and 5 years after transplantation in pediatric heart transplant recipients using United Network for Organ Sharing data from 1987 to 2019. The variables used for predicting posttransplant outcomes included donor and recipient as well as medical and social factors. We evaluated 7 ML models-extreme gradient boosting (XGBoost), logistic regression, support vector machine, random forest (RF), stochastic gradient descent, multilayer perceptron, and adaptive boosting (AdaBoost)-as well as a deep learning model with 2 hidden layers with 100 neurons and a rectified linear unit (ReLU) activation function followed by batch normalization for each and a classification head with a softmax activation function. We used 10-fold cross-validation to evaluate model performance. Shapley additive explanations (SHAP) values were calculated to estimate the importance of each variable for prediction.

RESULTS

RF and AdaBoost models were the best-performing algorithms for different prediction windows across outcomes. RF outperformed other ML algorithms in predicting 5 of the 6 outcomes (area under the receiver operating characteristic curve [AUROC] 0.664 and 0.706 for 1-year and 3-year rejection, respectively, and AUROC 0.697, 0.758, and 0.763 for 1-year, 3-year, and 5-year mortality, respectively). AdaBoost achieved the best performance for prediction of 5-year rejection (AUROC 0.705).

CONCLUSIONS

This study demonstrates the comparative utility of ML approaches for modeling posttransplant health outcomes using registry data. ML approaches can identify unique risk factors and their complex relationship with outcomes, thereby identifying patients considered to be at risk and informing the transplant community about the potential of these innovative approaches to improve pediatric care after heart transplantation. Future studies are required to translate the information derived from prediction models to optimize counseling, clinical care, and decision-making within pediatric organ transplant centers.

External validation and comparison of risk score models in pediatric heart transplants

BACKGROUND

Pediatric heart transplant (PHT) patients have the highest waitlist mortality of solid organ transplants, yet more than 40% of viable hearts are unutilized. A tool for risk prediction could impact these outcomes. This study aimed to compare and validate the PHT risk score models (RSMs) in the literature.

METHODS

The literature was reviewed to identify RSMs published. The United Network for Organ Sharing (UNOS) registry was used to validate the published models identified in a pediatric cohort (<18 years) transplanted between 2017 and 2019 and compared against the Scientific Registry of Transplant Recipients (SRTR) 2021 model. Primary outcome was post-transplant 1-year mortality. Odds ratios were obtained to evaluate the association between risk score groups and 1-year mortality. Area under the curve (AUC) was used to compare the RSM scores on their goodness-of-fit, using Delong's test.

RESULTS

Six recipient and one donor RSMs published between 2008 and 2021 were included in the analysis. The validation cohort included 1,003 PHT. Low-risk groups had a significantly better survival than high-risk groups as predicted by Choudhry (OR = 4.59, 95% CI [2.36-8.93]) and Fraser III (3.17 [1.43-7.05]) models. Choudhry's and SRTR models achieved the best overall performance (AUC = 0.69 and 0.68, respectively). When adjusted for CHD and ventricular assist device support, all models reported better predictability [AUC > 0.6]. Choudhry (AUC = 0.69) and SRTR (AUC = 0.71) remained the best predicting RSMs even after adjustment.

CONCLUSION

Although the RSMs by SRTR and Choudhry provided the best prediction for 1-year mortality, none demonstrated a strong (AUC ≥ 0.8) concordance statistic. All published studies lacked advanced analytical approaches and were derived from an inherently limited dataset.

Pediatric heart transplantation in infants and small children under 3 years of age: Single center experience - "Early and long-term results"

OBJECTIVES

We analyzed the early and long-term survival after ABO-compatible heart transplantation in children under 3 years of age from 1991 to 2021 at our center. This retrospective and descriptive study aimed to identify serious adverse events associated with mortality after pediatric heart transplantation.

PATIENTS AND METHODS

46 patients with congenital heart failure (37%) in end-stage heart failure have undergone a pediatric heart transplantation. Primary outcome of interest was survival at follow-up time.

RESULTS

Median (IQR) follow-up time (y), age (y), body-weight (kg) and BMI (kg/cm²) were 13.2 (5.7-19.5), 0.9 (0.2-2.0), 6.8 (4.3-10.0) and 14.2 (12.3-15.7). Twenty-four (52%) patients were male. 15 patients (33%) had a single ventricle physiology. At 30- days survival rate was 94 ± 4%. Survival rate at 1, 5, 10 and 15 years post HTx was 87 ± 5%, 84 ± 6%, 79 ± 6% and 63 ± 8%. One child underwent re-transplantation after 4 years, and another one after 11 years - in both cases due to graft failure. Higher early mortality in patients under 3 months of age and in patients with single ventricle physiology. Transplant free survival at 15 years was in children with cardiomyopathy better (71 ± 10%) than in those with congenital heart disease (50 ± 13%). One or more previous heart surgeries prior to HTx (n = 21) were associated to more mortality.

CONCLUSION

Pediatric heart transplantation has acceptable long-term results and is still the best therapeutic option in children with end-stage cardiac failure. Underlying anomalies and single ventricle physiology, age below 3 months had a significant impact on survival.

A coordinated approach to improving pediatric heart transplant waitlist outcomes: A summary of the ACTION November 2019 waitlist outcomes committee meeting

The number of children needing heart transplantation continues to rise. Although improvements in heart failure therapy, particularly durable mechanical support, have reduced waitlist mortality, the number of children who die while waiting for a suitable donor organ remains unacceptably high. Roughly, 13% of children and 25% of infants on the heart transplant waitlist will not survive to transplantation. With this in mind, the Advanced Cardiac Therapies Improving Outcomes Collaborative Learning Network (ACTION), through its Waitlist Outcomes Committee, convened a 2-day symposium in Ann Arbor, Michigan, from 2-3 November 2019, to better understand the factors that contribute to pediatric heart transplant waitlist mortality and to focus future efforts on improving the organ allocation rates for children needing heart transplantation. Using improvement science methodology, the heart failure-transplant trajectory was broken down into six key steps, after which modes of failure and opportunities for improvement at each step were discussed. As a result, several projects aimed at reducing waitlist mortality were initiated.

A comprehensive strategy in donor acceptance: Impact on pediatric waitlist and heart transplant outcomes

Significant inter- and intra-center practice variability is present in pediatric donor heart acceptability. This may contribute to variation in the donor refusal rate and may impact waitlist time, morbidity, mortality, and transplant rates. In order to reduce practice variability, our center developed and implemented a comprehensive strategy regarding donor acceptance in September 2017. The aim of this study was to assess the impact of this strategy on waitlist time and outcomes as well as early post-transplant outcomes. We performed a single-center, retrospective analysis of all pediatric (<18 years) patients listed for single-organ heart transplant at our center from September 2015 to September 2018. Patients were divided into those listed before (Group 1) and after implementation of the comprehensive strategy (Group 2). The primary end-point was waitlist time. Secondary end-points included waitlist removal due to death or clinical deterioration, donor refusals per listed patient, early post-transplant outcomes (graft failure, mechanical ventilation time, inotropic support, length of hospital stay) and 1-year post-transplant survival. Of 78 listed patients, 54 were transplanted (29 in Group 1), 9 were removed due to death or clinical deterioration (7 in Group 1) and 15 were removed due to clinical improvement (12 in Group 1). The waitlist time was significantly shorter in Group 2 (17 days, IQR 7-53) vs Group 1 (90 days, IQR 14-162); P = .006. The number of donor refusals was lower in Group 2 (1, IQR 0-2.2) vs Group 1 (4, IQR 2-19); P < .001. The percentage of refused donors with normal function (Left ventricular ejection fraction > 50%) was lower in Group 2 vs Group 1 (53% vs 84%; P < .001). Difference in removal from the waitlist for death or deterioration in Group 2 vs Group 1 (n = 2, 7% vs n = 7, 20%, P = .18) did not reach statistical significance. There was no difference in post-transplant outcomes between groups. The waitlist time and donor refusals significantly decreased after implementation of a comprehensive donor acceptance strategy without impacting transplant outcomes. This analysis supports the need for a comprehensive approach to donor organ acceptance within a pediatric transplant center.