Purpose: In Model for End-stage Liver Disease (MELD)-based allocation systems patients with cancer and some other diseases are assigned a special score. The goal of this study was to assess the fairness of organ distribution by the MELD system among different groups of diseases. Methods: Retrospective study with adult patients between 2009 and 2013. Demographics and MELD scores were compared with the incidence of transplant or death, patient origin and disease groups. Results: 260 selected patients were submitted to transplant or died before the transplant. Their median age was 54.9 years (12.1 -73.9 years); 70.4% were men; 63.3% had chronic liver diseases (alcoholic cirrhosis 33.1%, C-virus cirrhosis 24.2%). Exception score was assigned to 26.5% of listed patients. These patients received 31% of transplanted organs and had lower pre-transplant mortality or dropout (14.2 times less) rates than the other patients (p <0.001). Receiving exception points resulted in a higher likelihood of being transplanted. Conclusion: The authors propose the use of a regional variable score for transplantation in special situations, which should be based on the median MELD score of the latest transplants for chronic liver diseases, to refrain from harming patients who have access to transplant according to the calculated MELD score.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.