Comparative analysis of outcomes in high KDPI spectrum kidney transplants using unsupervised machine learning algorithm
Transplantation with high-KDPI kidneys, though associated with lower survival rates, remains a viable option for expanding the donor pool. With appropriate recipient selection, high-KDPI kidneys can improve patient quality of life, reduce wait times, and lower healthcare costs. Our findings support a more nuanced approach to organ allocation using advanced matching strategies.
Authors
- Michael Lioudis (ORCID: https://orcid.org/0009-0003-7524-4624)
- Rezà F. Saidi (ORCID: https://orcid.org/0000-0002-7389-2981)
- Isabella M. Vlassis
- Mahmoudreza Moein (ORCID: https://orcid.org/0000-0002-3065-5759)
- Alireza Golkarieh
Institutions
- Oakland University (US)
- SUNY Upstate Medical University (US)
- Michigan United (US)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-08-26
- DOI
- https://doi.org/10.1371/journal.pone.0324265
- Citations
- 3
- Primary Topic
- Renal Transplantation Outcomes and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 5.96