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early transplantation maximizes survival in severe acute on chronic liver failure results of a markov decision process model

Authors: Suyanpeng Zhang; Sze-Chuan Suen; Cynthia L. Gong; Jessica Pham; Jonel Trebicka; Christophe Duvoux; Andrew S. Klein; +3 Authors

early transplantation maximizes survival in severe acute on chronic liver failure results of a markov decision process model

Abstract

Background & Aims Uncertainties exist surrounding the timing of liver transplantation (LT) among patients with acute-on-chronic liver failure grade 3 (ACLF-3), regarding whether to accept a marginal quality donor organ to allow for earlier LT or wait for either an optimal organ offer or improvement in the number of organ failures, in order to increase post-LT survival. Methods We created a Markov decision process model to determine the optimal timing of LT among patients with ACLF-3 within 7 days of listing, to maximize overall 1-year survival probability. Results We analyzed 6 groups of candidates with ACLF-3: patients age ≤60 or >60 years, patients with 3 organ failures alone or 4-6 organ failures, and hepatic or extrahepatic ACLF-3. Among all groups, LT yielded significantly greater overall survival probability vs. remaining on the waiting list for even 1 additional day (p 60 years old or with 4-6 organ failures. The probability of improvement from ACLF-3 to ACLF-2 does not influence these recommendations, as the likelihood of organ recovery was less than 10%. Conclusion During the first week after listing for patients with ACLF-3, earlier LT in general is favored over waiting for an optimal quality donor organ or for recovery of organ failures, with the understanding that the analysis is limited to consideration of only these 3 variables. Lay summary In the setting of grade 3 acute-on-chronic liver failure (ACLF-3), questions remain regarding the timing of transplantation in terms of whether to proceed with liver transplantation with a marginal donor organ or to wait for an optimal liver, and whether to transplant a patient with ACLF-3 or wait until improvement to ACLF-2. In this study, we used a Markov decision process model to demonstrate that earlier transplantation of patients listed with ACLF-3 maximizes overall survival, as opposed to waiting for an optimal donor organ or for improvement in the number of organ failures.

Highlights • We created a Markov decision process model to maximize overall survival ACLF-3 patients within 7 days of listing. • We examined three variables: earlier transplantation, organ quality, and recovery of organ failures. • Earlier transplantation maximizes overall survival probability, due to high waitlist mortality of patients with ACLF-3. • The impact of a marginal organ on post-LT mortality is less consequential than the mortality from delaying transplantation. • The likelihood of organ failure recovery within 7 days of listing was less than 10%.

Graphical abstract

Country
United Kingdom
Keywords

UNOS, United Network for Organ Sharing, donor risk index, UNOS database; organ failure; MELD-Na score; donor risk index, RC799-869, Diseases of the digestive system. Gastroenterology, UNOS database, DRI, donor risk index, MELD, model for end-stage liver disease, ACLF, acute-on-chronic liver failure, MELD-Na score, organ failure, ACLF-3, acute-on-chronic liver failure grade 3, Research Article

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  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    22
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
Top 10%
Average
Top 10%
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gold