Insufficient use of technical variant grafts: An unfulfilled promise in pediatric liver transplantation
Bibliographic record
Abstract
Pediatric liver transplantation in the United States faces an important challenge. While outcomes have improved, with current 1- and 5-year patient survival >97% and 94%, respectively, many children continue to die on the waitlist (WL) or are removed because they are too sick.1,2 These are often the youngest and most vulnerable candidates: the highest US pediatric WL mortality occurs in children <1 year of age.2 In this issue, Mazariegos and colleagues reviewed the Organ Procurement and Transplantation Network (OPTN) data over a 16-year period (2004–2020).3 Of the 9934 children listed for primary transplant during the study period, 2092 did not receive a transplant, including 657 who died. As expected, these children were younger, smaller, sicker (more status 1 listings), and remained on the WL longer than children who received a transplant during the same time period (Table 1). These small infants are particularly at risk because of the difficulty of obtaining an appropriately sized-matched graft. Data indicate that this problem can be solved largely by increasing the use of technical variant grafts (TVGs), which includes living donor (LD) grafts and split/reduced grafts from deceased donors (DDs).4,5 Here, the authors link individual center TVG utilization with WL outcomes. Although some programs do not use TVGs as frequently to successfully transplant their patients, there are 17 “Low TVG use, High WL mortality” programs distributed across 8 of the 11 OPTN regions, including regions 4 and 5 where they make up or equal the majority of programs.3 Furthermore, programs that performed <10 pediatric liver transplants (LTs) during the study period were excluded from the analysis, raising the possibility of even more compelling data if they were included.3 The authors demonstrate that center volume and living donor liver transplantation (LDLT) expertise protect against graft failure and death, confirming prior studies.4,6,7 As data continue to underscore the importance of being able to offer a TVG to reduce WL mortality, a key question is this: how should equal access to these options be ensured? The authors note that over half of pediatric transplants in 2021 were performed by 11 centers, and over half of the pediatric LDLTs were performed by 7 centers.3 Overall, utilization of LDLT for pediatric recipients in the United States remains low (12.7% in 2020) and has not changed substantially over the last decade. Similarly, split/reduced liver usage has remained static, and as the authors highlight, only 3.8% of DD livers that meet “splittable” criteria are actually used for that purpose. Following the implementation of the acuity circles policy in 2020, pediatric LT candidates now receive priority for pediatric donors nationally before they are offered to adult recipients. This change appears to have had a positive effect on pretransplant pediatric mortality, primarily for infants <1 year of age, which decreased from 12.4 to 4.9 per 100 WL-years, the lowest rate seen since 2011.2 Whether this improvement is durable remains to be seen. Increasing the utilization of LDLT in pediatrics would seem to be a logical answer to this problem. This solution, however, rubs up against a current issue in the American transplant community: given the highly regulated environment and the significant programmatic consequences for “suboptimal” outcomes, tension may exist between what is “right for the patient” versus what is “right for the center.” Expansion of LDLT at all centers, including low-volume programs, may not be a wise path forward, as center volume correlates directly with outcomes.8 Instead, incentivizing regional partnerships between larger programs with excellent LDLT outcomes (high TVG use, low WL mortality) and smaller programs with longer wait times (low TVG use, high WL mortality) may provide greater benefit. Recipients at high-volume LDLT centers also benefit from increased center comfort in utilizing LD grafts in higher risk settings, such as pediatric acute liver failure, and from nontraditional donors, particularly anonymous nondirected donors, who are increasing in frequency in the United States.2,7,9 We reported our first experience in Toronto of anonymous nondirected donation for a pediatric recipient in 2007 and subsequently showed the superiority of LD grafts (n = 135) versus DD (n = 158) grafts in 2019, 22 of which were from anonymous donors.7,10 Since that time, our experience has increased to ~120 cases, over half of which have been directed to children. This has helped us to extend the benefits of LDLT to children without access to a LD, shorten wait times, and virtually eliminate our pediatric WL. Finally, this manuscript obliquely touches on another pressing issue within the pediatric LT community, namely, the core skill set of a pediatric LT surgeon. Currently, there is no such distinct designation in the North American training environment, and therefore, no training requirements exist. To provide the full spectrum of surgical care, the technical skill set should include LD hepatectomies and graft implantations, DD graft reduction/splitting, the reduction or hyper-reduction of left lateral segment grafts, and staged abdominal closure. Similarly, it would include clinical fluency in pediatric cholestatic liver disease, extrahepatic portal vein obstruction, metabolic disorders, and pediatric hepatobiliary malignancies. It seems that there is space for the American Society of Transplant Surgeons and the Society of Pediatric Liver Transplantation to begin formally defining core cognitive and technical competencies to craft a curriculum to achieve these standards. Creating distinct training requirements for trainees with plans to practice pediatric liver transplantation, including acquiring the technical skills to expand TVG usage, may require programmatic partnerships or secondary hyperspecialized training. However, without robust exposure, limited access to TVGs and prolonged wait times may continue to be a problem for pediatric candidates. Here, Mazariegos and colleagues illustrate important center-level differences in TVG usage that is not explained by regional variability and has a direct impact on patient outcomes.3 These important data should galvanize the pediatric liver community as they further underscore that establishing the availability of TVGs as a standard of care for all pediatric LT recipients is an important component in moving toward the goal of zero WL mortality.11
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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; a candidate call from one teacher head, not a consensus.
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".