Towards a cardiac allocation score: a retrospective calculation for 73 patients from a German transplant center.

BACKGROUND

Due to a growing discrepancy between the transplant waiting list and decreasing numbers of available donor hearts, cardiac transplantation rates in Germany have been declining in the past years. Currently, patients on the waiting list are prioritized by medical urgency and waiting time and therefore a majority of all cardiac transplants is performed in very ill patients. Recently, a different allocation algorithm was proposed that included predicted post-transplant survival as a parameter for organ allocation. So far, little data exists on how such a "Cardiac Allocation Score" (CAS) relates to our current transplant patient population and on how such a change in organ allocation could change clinical practice.

METHODS

We calculated a theoretical retrospective Cardiac Allocation Score for 73 patients recruited and transplanted at our medium-volume center in Germany based on a hypothetical scoring algorithm recently published by Eurotransplant.

RESULTS

Overall, 37 patients (50.7%) were transplanted on high urgency status (HU), 27 (37%) were being supported by a VAD at time of transplant. 57 (78.1%) were male. We found a relatively normal distribution of the hypothetical CAS with a median of 32.91 and a mean of 31.95 +/-10.02. Overall, CAS-Scores were lower than previously described for a Eurotransplant patient cohort of high urgency patients, but there was a significant overlap in score values between patients on HU and T status. CAS-values of VAD-supported patients were lower than in patients without mechanical support. The IMPACT-score as part of the CAS was used for prediction of post-transplant survival and seems suitable to predict outcome in our patient population.

CONCLUSION

In a retrospective analysis, the recently proposed Cardiac Allocation Score seems to show a normal distribution of priority values in our patient cohort. The IMPACT-score predicted outcome after transplantation and could serve as part of the CAS-algorithm to predict post-transplant survival in this single center real-world scenario. Implementation of the CAS could significantly change organ allocation practice, including a potential prioritization of current T-status patients over HU-status patients.