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A mathematical model to describe survival among liver recipients from deceased donors with risk of transmitting infectious encephalitis pathogens
Author(s) -
Smalley Hannah K.,
Anand Nishi,
Buczek Dylan,
Buczek Nicholas,
Lin Timothy,
Rajore Tanay,
Wacker Muriel,
Basavaraju Sridhar V.,
Gurbaxani Brian M.,
Hammett Teresa,
Keskinocak Pinar,
Sokol Joel,
Kuehnert Matthew J.
Publication year - 2019
Publication title -
transplant infectious disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.69
H-Index - 67
eISSN - 1399-3062
pISSN - 1398-2273
DOI - 10.1111/tid.13115
Subject(s) - medicine , encephalitis , proportional hazards model , organ transplantation , transmission (telecommunications) , odds ratio , immunology , transplantation , virus , electrical engineering , engineering
Background Between 2002 and 2013, the organs of 13 deceased donors with infectious encephalitis were transplanted, causing infections in 23 recipients. As a consequence, organs from donors showing symptoms of encephalitis (increased probability of infectious encephalitis (IPIE) organs) might be declined. We had previously characterized the risk of IPIE organs using data available to most transplant teams and not requiring special diagnostic tests. If the probability of infection is low, the benefits of a transplant from a donor with suspected infectious encephalitis might outweigh the risk and could be lifesaving for some transplant candidates. Methods Using organ transplant data and Cox Proportional Hazards models, we determined liver donor and recipient characteristics predictive of post‐transplant or waitlist survival and generated 5‐year survival probability curves. We also calculated expected waiting times for an organ offer based on transplant candidate characteristics. Using a limited set of actual cases of infectious encephalitis transmission via transplant, we estimated post‐transplant survival curves given an organ from an IPIE donor. Results 54% (1256) of patients registered from 2002‐2006 who died or were removed from the waiting list because of deteriorated condition within 1 year could have had an at least marginal estimated benefit by accepting an IPIE liver with some probability of infection, with the odds increasing to 86% of patients if the probability of infection was low (5% or less). Additionally, 54% (1252) were removed from the waiting list prior to their estimated waiting time for a non‐IPIE liver and could have benefited from an IPIE liver. Conclusion Improved allocation and utilization of IPIE livers could be achieved by evaluating the patient‐specific trade‐offs between (a) accepting an IPIE liver and (b) remaining on the waitlist and accepting a non‐IPIE liver after the estimated waiting time.