Pediatric donor heart acceptance practices in the United States: What is really being considered?

Machine Learning for Predicting Waitlist Mortality in Pediatric Heart Transplantation

BACKGROUND

Waitlist mortality remains a critical issue for pediatric heart transplant (HTx) candidates, particularly for candidates with congenital heart disease. Listing center organ offer acceptance practices have been identified as a factor influencing waitlist outcomes. We utilized machine learning (ML) to identify factors associated with waitlist mortality, combining variables associated with institutional offer acceptance practices as well as candidate-specific risk factors.

METHODS

We analyzed the Organ Procurement and Transplantation Network database for pediatric HTx candidates listed between 2010 and 2020. Various statistical and ML models were employed to identify predictors of waitlist mortality or clinical deterioration leading to waitlist removal. The dataset was split into training (82%) and testing (18%), and the final model was selected based on predictive performance. SHAP values were used to assess variable importance.

RESULTS

Among 5523 pediatric candidates, overall waitlist mortality was 9.8%. The CatBoost model achieved the highest predictive performance with an AUC-ROC score of 0.74 and a recall score of 0.75. Key predictors included candidate diagnosis, age/size, ventilator use, eGFR, serum albumin, ECMO, and institutional factors such as high offer refusal rates and low transplant volume.

CONCLUSIONS

Institutional organ offer acceptance practices influence waitlist outcomes for pediatric HTx candidates. Centers with higher organ refusal rates are associated with worse outcomes, independent of candidate-specific risk factors, underscoring the need for standardizing organ acceptance criteria across institutions to reduce variability in decision-making and improve waitlist survival. Additionally, addressing modifiable risk factors such as malnutrition and renal dysfunction could further optimize patient outcomes.

A comprehensive, multifaceted strategy to increase pediatric donor heart utilization

BACKGROUND

In 2016, we initiated a quality improvement endeavor to increase pediatric heart offer acceptance. This study assessed the effect of these interventions at our center.

METHODS

We evaluted pre- and postimplementation cohorts (January 1, 2008-December 31, 2016 vs January 1, 2017-July 1, 2023) comparing donor heart utilization. Six interventions were iterated over time to increase offer acceptance ("extended criteria"): ABO-incompatible transplant, ex vivo perfusion for distanced donors, 3-dimensional total cardiac volume (TCV) assessment, acceptance of hepatitis-C or Severe Acute Respiratory Syndrome Coronavirus 2 infected donors, and institutional culture change favoring consideration of donors previously considered unacceptable. Outcomes studied included annual HT volume, median waitlist duration, sequence number at acceptance, and post-transplant clinical outcomes.

RESULTS

During the study period, annual transplant volume increased from 16/year to 25/year pre- and postimplementation. Three hundred thirteen of 389 (80%) listed patients were transplanted. Waitlist duration shortened postimplementation (p = 0.01), as did the percentage of accepted heart offers utilizing at least 1 extended criterion (p < 0.001). Institutional culture change and TCV assessment had the largest impact on donor heart utilization (p = 0.04 and p < 0.001). There was no difference in post-HT intubation or intensive care unit days (p = 0.05-0.9), though post-transplant hospitalization duration (p < 0.001) increased. Post-transplant survival was unaffected by the use of extended criteria hearts (p = 0.3).

CONCLUSIONS

We report a successful longitudinal, multifaceted effort to increase organ offer utilization, with institutional culture change and TCV assessments most impactful. The use of extended criteria hearts was not associated with inferior survival.

Survival after partial heart transplantation in a piglet model

Partial heart transplantation (PHT) is a novel surgical approach that involves transplantation of only the part of the heart containing a valve. The rationale for this approach is to deliver growing heart valve implants that reduce the need for future re-operations in children. However, prior to clinical application of this approach, it was important to assess it in a preclinical model. To investigate PHT short-term outcomes and safety, we performed PHT in a piglet model. Yorkshire piglets (n = 14) were used for PHT of the pulmonary valve. Donor and recipient pairs were matched based on blood types. The piglets underwent PHT at an average age of 44 days (range 34-53). Post-operatively, the piglets were monitored for a period of two months. Of the 7 recipient piglets, one mortality occurred secondary to anesthesia complications while undergoing a routine echocardiogram on post-operative day 19. All piglets had appropriate weight gain and laboratory findings throughout the post-operative period indicating a general state of good health and rehabilitation after undergoing PHT. We conclude that PHT has good short-term survival in the swine model. PHT appears to be safe for clinical application.

Pediatric donor heart utilization variability among organ procurement organizations

BACKGROUND

Organ procurement organizations (OPOs) are responsible for the medical management of organ donors. Given the variability in pediatric donor heart utilization among OPOs, we examined factors that may explain this variability, including differences in donor medical management, organ quality, and candidate factors.

METHODS

The Organ Procurement and Transplant Network database was queried for pediatric (<18 years) heart donors and candidates receiving pediatric donor heart offers from 2010 to 2019. OPOs were stratified by pediatric donor heart utilization rate, and the top and bottom quintiles were compared based on donor management strategies and outcomes. A machine learning algorithm, combining 11 OPO, donor, candidate, and offer variables, was used to determine factors most predictive of whether a heart offer is accepted.

RESULTS

There was no clinically significant difference between the top and bottom quintile OPOs in baseline donor characteristics, distance between donor and listing center, management strategies, or organ quality. Machine learning modeling suggested neither OPO donor management nor cardiac function is the primary driver of whether an organ is accepted. Instead, number of prior donor offer refusals and individual listing center receiving the offer were two of the most predictive variables of organ acceptance.

CONCLUSIONS

OPO clinical practice variation does not seem to account for the discrepancy in pediatric donor heart utilization rates among OPOs. Listing center acceptance practice and prior number of donor refusals seem to be the important drivers of heart utilization and may at least partially account for the variation in OPO heart utilization rates given the regional association between OPOs and listing centers.