Association of center-level temporary mechanical circulatory support use and waitlist outcomes after the 2018 adult heart allocation policy

Kim, Samuel T.; Tran, Zachary; Xia, Yu; Mabeza, Russyan Mark; Hernández, Roland A.; Benharash, Peyman

doi:10.1016/j.surg.2022.03.032

Cited by 5 publications

(5 citation statements)

References 20 publications

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“…Within the first year, centers noted a substantial increase in temporary circulatory support systems such as IABP and a significant decrease in patients getting transplanted from a durable VAD. [11][12][13][14] The wait time decreased significantly for those listed at a higher listing status. The current generation of durable VADs carries a low rate of device complications and has provided a reliable way of supporting patients with heart failure.…”

Section: Discussionmentioning

confidence: 99%

“…This policy change was very significant and drastically altered the landscape of transplantation in the United States. Within the first year, centers noted a substantial increase in temporary circulatory support systems such as IABP and a significant decrease in patients getting transplanted from a durable VAD 11–14 . The wait time decreased significantly for those listed at a higher listing status.…”

Section: Discussionmentioning

confidence: 99%

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Impact of new allocation policy on waitlist and transplant outcomes of adult congenital heart patients supported with ECMO

Deshpande,

Das,

Kumar

et al. 2024

Artificial Organs

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BackgroundThe use of ECMO as a bridge to heart transplantation has been growing rapidly in all heart transplant recipients since the implementation of the new UNOS allocation policy; however, the impact on adult congenital heart disease (ACHD) patients is not known.MethodsWe analyzed the UNOS data (2015–2021) for ACHD patients supported with extracorporeal membrane oxygenation (ECMO) during the waitlist, before and after October 2018, to assess the impact on the waitlist and posttransplant outcomes. We compared the characteristics and outcomes of ACHD patients with or without ECMO use during the waitlist and pre‐ and postpolicy changes.ResultsA total of 23 821 patients underwent heart transplantation, and only 918 (4%) had ACHD. Out of all ACHD patients undergoing heart transplants, 6% of patients in the prepolicy era and 7.6% in the postpolicy era were on ECMO at the time of listing. Those on ECMO were younger and sicker compared to the rest of the ACHD cohort. Those on ECMO had similar profiles pre‐ and postpolicy change; however, there was a very significant decrease in the waitlist time [136 days (IQR 29–384) vs. 38 days (IQR 11–108), p = 0.01]. There was no difference in waitlist mortality; however, competing risk analyses showed a higher likelihood of transplantation (51% vs. 29%) and a lower likelihood of death or deterioration (31% vs. 42%) postpolicy change. Long‐term outcomes posttransplant for those supported with ECMO compared to the non‐ECMO cohort are similar for ACHD patients, although there was higher attrition in the first year for the ECMO cohort.ConclusionThe new allocation policy has resulted in shorter waitlist times and a higher likelihood of transplantation for ACHD patients supported by ECMO. However, the appropriate use of ECMO and the underuse of durable circulatory support devices in this population need further exploration.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Impact of new allocation policy on waitlist and transplant outcomes of adult congenital heart patients supported with ECMO

Deshpande,

Das,

Kumar

et al. 2024

Artificial Organs

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“…The purpose of these regions is to ensure a balance between the availability of organs and the number of people waiting for transplants in any given area. We have included the region in model derivation to account for the wide variation in tMCS utilization between regions ( 4 , 10 ). We excluded region 6 due to the small number of patients (<150 patients).…”

Section: Methodsmentioning

confidence: 99%

“…The majority of IABP and Impella evidence comes from the population of acute coronary syndrome or peri-cardiac intervention use. Identifying the suitable device for the right patient at the right time to achieve optimal pre and post-HTx outcomes remains a formidable task and a knowledge gap ( 4 ).…”

Section: Introductionmentioning

confidence: 99%

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An explainable machine learning approach using contemporary UNOS data to identify patients who fail to bridge to heart transplantation

Mardini,

Bai,

Bledsoe

et al. 2024

Front. Cardiovasc. Med.

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BackgroundThe use of Intra-aortic Balloon Pump (IABP) and Impella devices as a bridge to heart transplantation (HTx) has increased significantly in recent times. This study aimed to create and validate an explainable machine learning (ML) model that can predict the failure of status two listings and identify the clinical features that significantly impact this outcome.MethodsWe used the UNOS registry database to identify HTx candidates listed as UNOS Status 2 between 2018 and 2022 and supported with either Impella (5.0 or 5.5) or IABP. We used the eXtreme Gradient Boosting (XGBoost) algorithm to build and validate ML models. We developed two models: (1) a comprehensive model that included all patients in our cohort and (2) separate models designed for each of the 11 UNOS regions.ResultsWe analyzed data from 4,178 patients listed as Status 2. Out of them, 12% had primary outcomes indicating Status 2 failure. Our ML models were based on 19 variables from the UNOS data. The comprehensive model had an area under the curve (AUC) of 0.71 (±0.03), with a range between 0.44 (±0.08) and 0.74 (±0.01) across different regions. The models' specificity ranged from 0.75 to 0.96. The top five most important predictors were the number of inotropes, creatinine, sodium, BMI, and blood group.ConclusionUsing ML is clinically valuable for highlighting patients at risk, enabling healthcare providers to offer intensified monitoring, optimization, and care escalation selectively.

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Waitlist and transplant outcomes in heart transplant candidates bridged with temporary endovascular right ventricular assist devices

Kwon,

Skidmore,

Bhandari

et al. 2024

The Journal of Heart and Lung Transplantation

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Association of center-level temporary mechanical circulatory support use and waitlist outcomes after the 2018 adult heart allocation policy

Cited by 5 publications

References 20 publications

Impact of new allocation policy on waitlist and transplant outcomes of adult congenital heart patients supported with ECMO

Impact of new allocation policy on waitlist and transplant outcomes of adult congenital heart patients supported with ECMO

An explainable machine learning approach using contemporary UNOS data to identify patients who fail to bridge to heart transplantation

Waitlist and transplant outcomes in heart transplant candidates bridged with temporary endovascular right ventricular assist devices

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