A change of heart: Preliminary results of the US 2018 adult heart allocation revision

In 2018, the Organ Procurement and Transplantation Network (OPTN) modified adult heart allocation to better stratify candidates and provide broader access to the most medically urgent candidates. We analyzed OPTN data that included waiting list and transplant characteristics, geographical distribution, and early outcomes 1 year before (pre: October 18, 2017‐October 17, 2018) and following (post: October 18, 2018‐October 17, 2019) implementation. The number of adult heart transplants increased from 2954 pre‐ to 3032 postimplementation. Seventy‐eight percent of transplants in the post era were for the most medically urgent (statuses 1‐3) compared to 68% for status 1A in the pre era. The median distance between the donor hospital and transplant center increased from 83 to 216 nautical miles, with an increase in total ischemic time from 3 to 3.4 hours (all P < .001). Waiting list mortality was not different across eras (14.8 vs 14.9 deaths per 100 patient‐years pre vs post respectively). Posttransplant patient survival was not different, 93.6% pre and 92.8% post. There is early evidence that the heart allocation policy has enhanced stratification of candidates by their medical urgency and broader distribution for the most medically urgent candidates with minimal impact on overall waiting list mortality and posttransplant outcomes.     

Optimization of heart allocation: The transplant risk score

The new French heart allocation system is designed to minimize waitlist mortality and extend the donor pool without a detrimental effect on posttransplant survival. This study was designed to construct a 1‐year posttransplant graft‐loss risk score incorporating recipient and donor characteristics. The study included all adult first single‐organ recipients transplanted between 2010 and 2014 (N = 1776). This population was randomly divided in a 2:1 ratio into derivation and validation cohorts. The association of variables with 1‐year graft loss was determined with a mixed Cox model with center as random effect. The predictors were used to generate a transplant‐risk score (TRS). Donor‐recipient matching was assessed using 2 separate recipient‐ and donor‐risk scores. Factors associated with 1‐year graft loss were recipient age >50 years, valvular cardiomyopathy and congenital heart disease, previous cardiac surgery, diabetes, mechanical ventilation, glomerular filtration rate and bilirubin, donor age >55 years, and donor sex: female. The C‐index of the final model was 0.70. Correlation between observed and predicted graft loss rate was excellent for the overall cohort (r = 0.90). Hearts from high‐risk donors transplanted to low‐risk recipients had similar survival as those from low‐risk donors. The TRS provides an accurate prediction of 1‐year graft‐loss risk and allows optimal donor‐recipient matching.     

Transplantation for pulmonary arterial hypertension with congenital heart disease: Impact on outcomes of the current therapeutic approach including a high-priority allocation program

Patients with end-stage pulmonary arterial hypertension due to congenital heart disease have limited access to heart-lung transplantation or double-lung transplantation. We aimed to assess the effects of a high-priority allocation program established in France in 2007. We conducted a retrospective study to compare waitlist and posttransplantation outcomes before versus after implementation of the high-priority allocation program. We included 67 consecutive patients (mean age at listing, 33.2 ± 10.5 years) with pulmonary arterial hypertension due to congenital heart disease listed for heart-lung transplantation or double-lung transplantation from 1997 to 2016. At one month, the incidences of transplantation and death before transplantation were 3.5% and 24.6% in 1997–2006, 4.8% and 4.9% for patients on the regular list in 2007–2016, and 41.2% and 7.4% for patients listed under the high-priority allocation program (p < .001 and p = .0001, respectively). Overall survival was higher in patients listed in 2007–2016 (84.2% and 61.2% at 1 and 10 years vs. 36.8% and 22.1%, p = .0001). Increased incidence of transplantation, decreased waiting list mortality, and improved early and long-term outcomes were observed in patients with pulmonary arterial hypertension due to congenital heart disease listed for transplantation in the recent era, characterized by implementation of a high-priority allocation program.     

Impact of the new kidney allocation system A2/A2B → B policy on access to transplantation among minority candidates

Blood group B candidates, many of whom represent ethnic minorities, have historically had diminished access to deceased donor kidney transplantation (DDKT). The new national kidney allocation system (KAS) preferentially allocates blood group A2/A2B deceased donor kidneys to B recipients to address this ethnic and blood group disparity. No study has yet examined the impact of KAS on A2 incompatible (A2i) DDKT for blood group B recipients overall or among minorities. A case‐control study of adult blood group B DDKT recipients from 2013 to 2017 was performed, as reported to the Scientific Registry of Transplant Recipients. Cases were defined as recipients of A2/A2B kidneys, whereas controls were all remaining recipients of non‐A2/A2B kidneys. A2i DDKT trends were compared from the pre‐KAS (1/1/2013‐12/3/2014) to the post‐KAS period (12/4/2014‐2/28/2017) using multivariable logistic regression. Post‐KAS, there was a 4.9‐fold increase in the likelihood of A2i DDKT, compared to the pre‐KAS period (odds ratio [OR] 4.92, 95% confidence interval [CI] 3.67‐6.60). However, compared to whites, there was no difference in the likelihood of A2i DDKT among minorities post‐KAS. Although KAS resulted in increasing A2/A2B→B DDKT, the likelihood of A2i DDKT among minorities, relative to whites, was not improved. Further discussion regarding A2/A2B→B policy revisions aiming to improve DDKT access for minorities is warranted.     

Sociodemographic Determinants of Waitlist and Posttransplant Survival Among End‐Stage Liver Disease Patients

While regional organ availability dominates discussions of distribution policy, community‐level disparities remain poorly understood. We studied micro‐geographic determinants of survival risk and their distribution across Donor Service Areas (DSAs). Scientific Registry of Transplant Recipients records for all adults waitlisted for liver transplantation 2002–2014 were reviewed. The primary exposure variables were county‐level sociodemographic risk, as measured by the Community Health Score (CHS), a previously‐validated composite index local health conditions, and distance to listing transplant center. Among 114 347 patients, the median CHS was 19.4 (range: 0–40). Compared the lowest risk counties (CHS 1–10), highest‐risk counties (CHS 31–40) had more black (14.6% vs. 5.4%), publicly insured (44.9% vs. 33.0), and remote candidates (34.0% vs. 15.1% living >100 miles away). Higher‐CHS candidates had greater waitlist mortality in Cox multivariable (HR 1.16 for CHS 31–40, 95% CI 1.11–1.21) and competing risks analysis (sHR 1.07, 95% CI 0.99–1.14). Post‐transplant survival was similar across CHS quartiles. Living >25 miles from the transplant center conferred excess mortality risk (sHR 1.08, 95% CI 1.03–1.12). Proposed distribution changes would disproportionately impact DSAs with more high‐CHS or distant candidates. Low‐income, rural and minority patients experience excess mortality while awaiting transplant, and risk disproportionately worse outcomes with reduced organ availability under current proposals.     

Racial/ethnic disparities in waitlisting for deceased donor kidney transplantation 1 year after implementation of the new national kidney allocation system

The impact of a new national kidney allocation system (KAS) on access to the national deceased‐donor waiting list (waitlisting) and racial/ethnic disparities in waitlisting among US end‐stage renal disease (ESRD) patients is unknown. We examined waitlisting pre‐ and post‐KAS among incident (N = 1 253 100) and prevalent (N = 1 556 954) ESRD patients from the United States Renal Data System database (2005‐2015) using multivariable time‐dependent Cox and interrupted time‐series models. The adjusted waitlisting rate among incident patients was 9% lower post‐KAS (hazard ratio [HR]: 0.91; 95% confidence interval [CI], 0.90‐0.93), although preemptive waitlisting increased from 30.2% to 35.1% (P < .0001). The waitlisting decrease is largely due to a decline in inactively waitlisted patients. Pre‐KAS, blacks had a 19% lower waitlisting rate vs whites (HR: 0.81; 95% CI, 0.80‐0.82); following KAS, disparity declined to 12% (HR: 0.88; 95% CI, 0.85‐0.90). In adjusted time‐series analyses of prevalent patients, waitlisting rates declined by 3.45/10 000 per month post‐KAS (P < .001), resulting in ≈146 fewer waitlisting events/month. Shorter dialysis vintage was associated with greater decreases in waitlisting post‐KAS (P < .001). Racial disparity reduction was due in part to a steeper decline in inactive waitlisting among minorities and a greater proportion of actively waitlisted minority patients. Waitlisting and racial disparity in waitlisting declined post‐KAS; however, disparity remains.     

Between-center variation in high-priority listing status under the new heart allocation policy

Under the new US heart allocation policy, transplant centers listed significantly more candidates at high priority statuses (Status 1 and 2) with mechanical circulatory support devices than expected. We determined whether the practice change was widespread or concentrated among certain transplant centers. Using data from the Scientific Registry of Transplant Recipients, we used mixed-effect logistic regression to compare the observed listings of adult, heart-alone transplant candidates post-policy (December 2018 to February 2020) to seasonally matched pre-policy cohort (December 2016 to February 2018). US transplant centers (N = 96) listed similar number of candidates in each policy period (4472 vs. 4498) but listed significantly more at high priority status (25.5% vs. 7.0%, p < .001) than expected. Adjusted for candidate characteristics, 91 of 96 (94.8%) centers listed significantly more candidates at high-priority status than expected, with the unexpected increase varying from 4.8% to 50.4% (interquartile range [IQR]: 14.0%–23.3%). Centers in OPOs with highest Status 1A transplant rate pre-policy were significantly more likely to utilize high-priority status under the new policy (OR: 9.73, p = .01). The new heart allocation policy was associated with widespread and significantly variable changes in transplant center practice that may undermine the effectiveness of the new system.     

Analysis of public discourse on heart transplantation in Japan using social network service data

The clarification of public concerns regarding heart transplantation is important for improving low organ donation rates in Japan. In the present study, we used the Twitter data of 4986 tweets (between August 2015 and January 2016) and 1429 tweets (between April 2016 and May 2016) to analyze public discourse on heart transplantation in Japan and identify the reasons for low organ donation rates. We manually categorized all tweets relevant to heart transplantation into nine categories and counted the number of tweets in each category per month. During the study period, the most popular category of tweets was related to the media, followed by money (tweets questioning or even criticizing the high price of fundraising goals to go overseas for heart transplantations), while some tweets were misconceptions. We also conducted a sentiment analysis, which revealed that the most popular negative tweets were related to money, while the most positive tweets were related to reports on the favorable outcomes of recipients. Our results suggest that listening to concerns, providing correct information (particularly for some misconceptions), and emphasizing the outcomes of recipients will facilitate an increase in the number of people contemplating heart transplantation and organ donation.     

Changes in heart transplant waitlist and posttransplant outcomes in patients with restrictive and hypertrophic cardiomyopathy with the new heart transplant allocation system

Historically, patients with restrictive (RCM) and hypertrophic cardiomyopathy (HCM) experienced longer wait-times for heart transplant (HT) and increased waitlist mortality. Recently, a new HT allocation system was implemented in the United States. We sought to determine the impact of the new HT system on RCM/HCM patients. Adult patients with RCM/HCM listed for HT between November 2015 and September 2019 were identified from the UNOS database. Patients were stratified into two groups: old system and new system. We identified 872 patients who met inclusion criteria. Of these, 608 and 264 were classified in the old and new system groups, respectively. The time in the waitlist was shorter (25 vs. 54 days, P < .001), with an increased frequency of HT in the new system (74% vs. 68%, P = .024). Patients who were transplanted in the new system had a longer ischemic time, increased use of temporary mechanical circulatory support and mechanical ventilation. There was no difference in posttransplant survival at 9 months (91.1% vs. 88.9%) (p = .4). We conclude that patients with RCM/HCM have benefited from the new HT allocation system, with increased access to HT without affecting short-term posttransplant survival.     

Socioeconomic Status and Ethnicity of Deceased Donor Kidney Recipients Compared to Their Donors

Public perception and misperceptions of socioeconomic disparities affect the willingness to donate organs. To improve our understanding of the flow of deceased donor kidneys, we analyzed socioeconomic status (SES) and racial/ethnic gradients between donors and recipients. In a retrospective cohort study, traditional demographic and socioeconomic factors, as well as an SES index, were compared in 56,697 deceased kidney donor and recipient pairs transplanted between 2007 and 2012. Kidneys were more likely to be transplanted in recipients of the same racial/ethnic group as the donor (p < 0.001). Kidneys tended to go to recipients of lower SES index (50.5% of the time, p < 0.001), a relationship that remained after adjusting for other available markers of donor organ quality and SES (p < 0.001). Deceased donor kidneys do not appear to be transplanted from donors of lower SES to recipients of higher SES; this information may be useful in counseling potential donors and their families regarding the distribution of their organ gifts.     

Can donor narratives yield insights? A natural language processing proof of concept to facilitate kidney allocation

Although expedited placement could ameliorate stagnant kidney utilization, precisely identifying difficult‐to‐place organs is crucial to mitigate potential harms associated with this policy. Existing algorithms have only leveraged structured data from the Organ Procurement and Transplantation Network (OPTN); however, detailed, free text case information about a donor exists. No known research exists about the utility of these data. We developed a model to predict the probability of delay or discard for adult deceased kidney donors between 2010 and 2018, leveraging donor free text data. The resultant model had a c‐statistic of 0.75 compared to 0.80 (

1. Reduced Probability of Delay or Discard [model],

r‐PODD) and 0.77 (

1. Kidney Donor Profile Index,

KDPI) on the test dataset. Analysis of the top predictive words suggest both known and potentially novel clinical factors (ie, a known factor such as hypertension vs a novel factor such as stents), and nuanced social factors (intravenous drug use) could negatively affect kidney utilization. These findings suggest that donor narratives have utility; the natural language processing (NLP) model is only moderately correlated with existing indices and provides directional evidence about additional cardiovascular risk factors that may affect kidney utilization. More research is needed to understand the potential to enhance existing indices of kidney utilization to better enable and mitigate the effects of policy interventions such as expedited placement.     

Use of Population‐based Data to Demonstrate How Waitlist‐based Metrics Overestimate Geographic Disparities in Access to Liver Transplant Care

Liver allocation policies are evaluated by how they impact waitlisted patients, without considering broader outcomes for all patients with end‐stage liver disease (ESLD) not on the waitlist. We conducted a retrospective cohort study using two nationally representative databases: HealthCore (2006–2014) and five‐state Medicaid (California, Florida, New York, Ohio and Pennsylvania; 2002–2009). United Network for Organ Sharing (UNOS) linkages enabled ascertainment of waitlist‐ and transplant‐related outcomes. We included patients aged 18–75 with ESLD (decompensated cirrhosis or hepatocellular carcinoma) using validated International Classification of Diseases, Ninth Revision (ICD‐9)–based algorithms. Among 16 824 ESLD HealthCore patients, 3‐year incidences of waitlisting and transplantation were 15.8% (95% confidence interval [CI] : 15.0–16.6%) and 8.1% (7.5–8.8%), respectively. Among 67 706 ESLD Medicaid patients, 3‐year incidences of waitlisting and transplantation were 10.0% (9.7–10.4%) and 6.7% (6.5–7.0%), respectively. In HealthCore, the absolute ranges in states' waitlist mortality and transplant rates were larger than corresponding ranges among all ESLD patients (waitlist mortality: 13.6–38.5%, ESLD 3‐year mortality: 48.9–62.0%; waitlist transplant rates: 36.3–72.7%, ESLD transplant rates: 4.8–13.4%). States' waitlist mortality and ESLD population mortality were not positively correlated: ρ = ?0.06, p‐value = 0.83 (HealthCore); ρ = ?0.87, p‐value = 0.05 (Medicaid). Waitlist and ESLD transplant rates were weakly positively correlated in Medicaid (ρ = 0.36, p‐value = 0.55) but were positively correlated in HealthCore (ρ = 0.73, p‐value = 0.001). Compared to population‐based metrics, waitlist‐based metrics overestimate geographic disparities in access to liver transplantation.     

MELD is MELD is MELD? Transplant center–level variation in waitlist mortality for candidates with the same biological MELD

Recently, model for end-stage liver disease (MELD)-based liver allocation in the United States has been questioned based on concerns that waitlist mortality for a given biologic MELD (bMELD), calculated using laboratory values alone, might be higher at certain centers in certain locations across the country. Therefore, we aimed to quantify the center-level variation in bMELD-predicted mortality risk. Using Scientific Registry of Transplant Recipients (SRTR) data from January 2015 to December 2019, we modeled mortality risk in 33 260 adult, first-time waitlisted candidates from 120 centers using multilevel Poisson regression, adjusting for sex, and time-varying age and bMELD. We calculated a "MELD correction factor" using each center's random intercept and bMELD coefficient. A MELD correction factor of +1 means that center's candidates have a higher-than-average bMELD-predicted mortality risk equivalent to 1 bMELD point. We found that the “MELD correction factor” median (IQR) was 0.03 (−0.47, 0.52), indicating almost no center-level variation. The number of centers with “MELD correction factors” within ±0.5 points, and between ±0.5–± 1, ±1.0–±1.5, and ±1.5–±2.0 points was 62, 41, 13, and 4, respectively. No centers had waitlisted candidates with a higher-than-average bMELD-predicted mortality risk beyond ±2 bMELD points. Given that bMELD similarly predicts waitlist mortality at centers across the country, our results support continued MELD-based prioritization of waitlisted candidates irrespective of center.     

Maximizing donor allocation: A review of UNOS region 9 donor heart turn‐downs

This study was performed to determine if organ selection practices for heart utilization by Region 9 transplant programs were optimal, and to identify opportunities to increase local organ recovery. A retrospective review of de‐identified region‐wide donor data January 1, 2010 through December 31, 2013 was performed. Over the study period 537 heart donors were identified, of which 321 (60%) were transplanted. Two hundred‐sixteen consented hearts were not used; 190 of these were not recovered, and 26 were recovered but not transplanted. Of these, 245/321 (76%) hearts were transplanted at one of 5 regional programs, 15 (5%) were transplanted out of region as primary offers, and 61 (19%) were turned down in region and exported. Of the 61 exported hearts, 43 were turned down in region for donor‐related “quality” codes (UNOS 830, 833‐837) by at least one program, the remaining 18 hearts were turned down for non‐”quality” reasons, primarily histocompatibility and size. Only 5/43 exported were turned down for “quality” reasons by all regional programs offered the organ. A review of consented, not recovered donor offers suggested an additional 28 organs were possibly appropriate for transplant. Our review of regional turn‐downs suggests transplant centers could potentially identify additional usable organs without compromising short‐term outcomes.     

Removing administrative boundaries using a gravity model for a national liver allocation system

Geographic disparities emerged as an increasing issue in organ allocation policies. Because of the sequential and discrete geographical models used for allocation scores, artificial regional boundaries may impede the access of candidates with the greatest medical urgency to vital organs. This article describes a continuous geographical allocation model that provides accurate organ access by introducing a multiplicative interaction between the patient's condition and the distance to the graft by using a gravity model. Patients with the most urgent need will thus have access to organs from farther away, while those in less urgent need may only have access to organs geographically closer. Compared to the previous French liver allocation scheme, the gravity model precluded transplantations for candidates with a Model for End-Stage Liver Disease (MELD) ≤ 14 for decompensated cirrhosis from 10.3% to 0.6%. Death and delisting while on the waiting list at 1 year also decreased from 30.1% to 22.4% for MELD ≥ 35. Waiting list (cumulative hazard ratio (CHR)  0.84 after adjustment) and posttransplant survival improved significantly (hazard ratio = 0.83 after adjustment). This new liver allocation system provides more equitable access to liver transplants and an efficient and safe alternative to administrative boundaries for geographical models in organ allocation.