Prediction of Waitlist Mortality in Adult Heart Transplant Candidates

Jasseron, Carine; Legeai, Camille; Jacquelinet, Christian; Leprince, Pascal; Cantrelle, C.; Audry, Benoît; Porcher, Raphaël; Bastien, Olivier; Dorent, Richard

doi:10.1097/tp.0000000000001724

Cited by 41 publications

(25 citation statements)

References 27 publications

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“…For example, it is possible that patients bridged with durable LVAD under the old allocation system are instead being bridged to direct transplantation with IABP in a way to prioritize sicker patients toward transplantation. Standardized and validated temporary MCS criteria or the use of candidate risk scores 8‐10 could be considered for future changes to the allocation system. This may decrease variation in application of listing strategies and increase system equity.…”

Section: Discussionmentioning

confidence: 99%

Impact of heart transplant allocation change on competing waitlist outcomes among listing strategies

Patel

Chung

Seliem

et al. 2021

Clinical Transplantation

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United Network for Organ Sharing (UNOS) updated the heart transplant allocation system in 2018 in an effort to improve waitlist times and better prioritize the sickest candidates. The new allocation system added new statuses 1 through 3 at the top of the waitlist in place of former status 1A, with temporary mechanical support (MCS) including extracorporeal membrane oxygenation (ECMO), intra-aortic balloon pump (IABP), and other temporary ventricular and biventricular support associated with the highest two statuses. 1 Other common listing strategies such as high-dose inpatient inotrope use and durable ventricular assist devices (LVAD) became statuses 3 and 4, respectively. Early experiences with the impact of the new allocation system identified an increase in temporary MCS (predominantly IABP) and variable effects on post-transplant survival. [2][3][4][5][6] However, there are limited data about the effects of the new allocation system on waitlist outcomes, 3,6 and specifically, the effects on waitlist outcomes stratified by various transplant listing strategies. Ongoing updates to the UNOS dataset allow for additional follow-up time and analyses of waitlist outcomes based on listing strategy. These

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Section: Discussionmentioning

confidence: 99%

Impact of heart transplant allocation change on competing waitlist outcomes among listing strategies

Patel

Chung

Seliem

et al. 2021

Clinical Transplantation

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“…11 While more follow-up is required to closely evaluate the impact of these center practice changes on the critical outcomes of wait-list and post-transplant mortality, work must continue to build an objective, score-based allocation system resistant to changes in treatment practices. 22,23 Such a system is vital to direct donor hearts to the most urgent candidates and save the most lives.…”

Section: Discussionmentioning

confidence: 99%

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

Ran

Chung

Anderson³

et al. 2021

American Journal of Transplantation

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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 postpolicy (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 highpriority 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.

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“…Existing heart failure survival models use information obtained at 1 time point—listing—to predict death (22–25). Often their formulation preceded the era of contemporary mechanical support.…”

Section: Discussionmentioning

confidence: 99%

“…This may explain why this model underestimated a combined endpoint of death, urgent transplantation, and MCS for patients with advanced heart failure at Cleveland Clinic (24). The Candidate Risk Score is 1 of the first heart allocation scores with a contemporary cohort (25). The survival model was derived from data obtained at initial listing for transplantation in France.…”

Section: Discussionmentioning

confidence: 99%

Continuously Updated Estimation of Heart Transplant Waitlist Mortality

Blackstone¹,

Rajeswaran

Cruz

et al. 2018

Journal of the American College of Cardiology

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Prediction of Waitlist Mortality in Adult Heart Transplant Candidates

Abstract: The candidate risk score provides an accurate objective prediction of waitlist mortality. It is currently being used to develop a modified cardiac allocation system in France.

Cited by 41 publications

References 27 publications

Impact of heart transplant allocation change on competing waitlist outcomes among listing strategies

Impact of heart transplant allocation change on competing waitlist outcomes among listing strategies

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

Continuously Updated Estimation of Heart Transplant Waitlist Mortality

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