Assessing Deceased-Donor Kidneys Through Posttransplant Survival Prediction Algorithms
Improving the discrimination and calibration of kidney allograft survival prediction models is achievable by including recipient characteristics. These enhanced models have potential to improve the system of kidney allocation.
Authors
- Sarah J. Ratcliffe (ORCID: https://orcid.org/0000-0002-6644-8284)
- Roy D. Bloom (ORCID: https://orcid.org/0000-0003-4783-7775)
- Jeremy Rubin (ORCID: https://orcid.org/0000-0002-8288-6022)
- Vishnu S. Potluri (ORCID: https://orcid.org/0000-0002-3307-8926)
- David Goldberg (ORCID: https://orcid.org/0000-0001-6514-9365)
- Jarcy Zee (ORCID: https://orcid.org/0000-0003-0586-1160)
- Chirag R. Parikh (ORCID: https://orcid.org/0000-0001-9051-7385)
- Emily A. Vail (ORCID: https://orcid.org/0000-0002-1849-5780)
- Alessandro Gasparini (ORCID: https://orcid.org/0000-0002-8319-7624)
- Peter P. Reese (ORCID: https://orcid.org/0000-0003-1440-069X)
- Peter L. Abt (ORCID: https://orcid.org/0000-0002-8682-972X)
- Michael J. Crowther (ORCID: https://orcid.org/0000-0001-8378-8259)
- Michael O. Harhay (ORCID: https://orcid.org/0000-0002-0553-674X)
Institutions
- Children's Hospital of Philadelphia (US)
- Johns Hopkins University (US)
- University of Miami (US)
- University of Miami Health System (US)
- University of Virginia (US)
- University of Pennsylvania (US)
- Vanderbilt University Medical Center (US)
Publication Details
- Journal
- American Journal of Kidney Diseases
- Published
- 2025-10-22
- DOI
- https://doi.org/10.1053/j.ajkd.2025.07.016
- Citations
- 1
- Primary Topic
- Renal Transplantation Outcomes and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.99