Jaimin R Trivedi1, Allen Cheng1, Michele Gallo1, Erin M Schumer1, H Todd Massey1, Mark S Slaughter2. 1. Department of Cardiovascular and Thoracic Surgery, University of Louisville, Louisville, Kentucky. 2. Department of Cardiovascular and Thoracic Surgery, University of Louisville, Louisville, Kentucky. Electronic address: mark.slaughter@louisville.edu.
Abstract
BACKGROUND: Optimum use of donor organs can increase the reach of the transplantation therapy to more patients on waiting list. The heart transplantation (HTx) has remained stagnant in United States over the past decade at approximately 2,500 HTx annually. With the use of the United Network of Organ Sharing (UNOS) deceased donor database (DCD) we aimed to evaluate donor factors predicting donor heart utilization. METHODS: UNOS DCD was queried from 2005 to 2014 to identify total number of donors who had at least one of their organs donated. We then generated a multivariate logistic regression model using various demographic and clinical donor factors to predict donor heart use for HTx. Donor hearts not recovered due to consent or family issues or recovered for nontransplantation reasons were excluded from the analysis. RESULTS: During the study period there were 80,782 donors of which 23,606 (29%) were used for HTx, and 38,877 transplants (48%) were not used after obtaining consent because of poor organ function (37%), donor medical history (13%), and organ refused by all programs (5%). Of all, 22,791 donors with complete data were used for logistic regression (13,389 HTx, 9,402 no-HTx) which showed significant predictors of donor heart use for HTx. From this model we assigned probability of donor heart use and identified 3,070 donors with HTx-eligible unused hearts for reasons of poor organ function (28%), organ refused by all programs (15%), and recipient not located (9%). CONCLUSIONS: An objective system based on donor factors can predict donor heart use for HTx and may help increase availability of hearts for transplantation from existing donor pool.
BACKGROUND: Optimum use of donor organs can increase the reach of the transplantation therapy to more patients on waiting list. The heart transplantation (HTx) has remained stagnant in United States over the past decade at approximately 2,500 HTx annually. With the use of the United Network of Organ Sharing (UNOS) deceased donor database (DCD) we aimed to evaluate donor factors predicting donor heart utilization. METHODS: UNOS DCD was queried from 2005 to 2014 to identify total number of donors who had at least one of their organs donated. We then generated a multivariate logistic regression model using various demographic and clinical donor factors to predict donor heart use for HTx. Donor hearts not recovered due to consent or family issues or recovered for nontransplantation reasons were excluded from the analysis. RESULTS: During the study period there were 80,782 donors of which 23,606 (29%) were used for HTx, and 38,877 transplants (48%) were not used after obtaining consent because of poor organ function (37%), donor medical history (13%), and organ refused by all programs (5%). Of all, 22,791 donors with complete data were used for logistic regression (13,389 HTx, 9,402 no-HTx) which showed significant predictors of donor heart use for HTx. From this model we assigned probability of donor heart use and identified 3,070 donors with HTx-eligible unused hearts for reasons of poor organ function (28%), organ refused by all programs (15%), and recipient not located (9%). CONCLUSIONS: An objective system based on donor factors can predict donor heart use for HTx and may help increase availability of hearts for transplantation from existing donor pool.
Authors: Elizabeth A Swanson; Tony Adams; Madhukar S Patel; Salvador De La Cruz; Michael Hutchens; Kiran Khush; Mitchell B Sally; Claus U Niemann; Tahnee Groat; Darren J Malinoski Journal: J Am Coll Surg Date: 2020-06-17 Impact factor: 6.113
Authors: Philipp Angleitner; Alexandra Kaider; Jacqueline M Smits; Arezu Z Aliabadi-Zuckermann; Emilio Osorio-Jaramillo; Günther Laufer; Andreas O Zuckermann Journal: Transpl Int Date: 2021-02-22 Impact factor: 3.782