Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: The allocation and acceptance of deceased-donor kidneys in the United States is influenced by theKidney Donor Profile Index (KDPI). We conducted a national analysis of high-KDPI kidney transplants performed from 2014 to 2021 to identify key predictors of post-transplant outcomes beyond those incorporated in KDPI. METHODS: This retrospective cohort study used data extracted from the Scientific Registry of Transplant Recipients (SRTR). Adult, first-time recipients of kidney-only deceased-donor transplants with KDPI greater than 85% were included. Regression models were used to identify independent predictors of delayed graft function (DGF), primary graft nonfunction (PGNF), patient survival, overall graft survival, and death-censored graft survival. RESULTS: Among 4,911 recipients, DGF occurred in 33.8% and PGNF in 4.0%. DGF was independently associated with donation after circulatory death, terminal donor creatinine > 1.5 mg/dL, recipient obesity, dialysis duration > 3 years, and cold ischemia time (CIT) ≥ 24 h, whereas machine perfusion was protective. PGNF was associated with donation after circulatory death, terminal donor creatinine > 2.0 mg/dL, high-risk cytomegalovirus (CMV) serostatus, and donor injury patterns within the high-KDPI range, including younger donor age. Five-year patient and graft survival were 72% and 62%, respectively. Graft loss was independently associated with DGF, elevated intrarenal resistive index (RI), recipient diabetes, prolonged dialysis exposure, and high-risk CMV/EBV serostatus. CONCLUSIONS: Outcomes after high-KDPI kidney transplantation reflect both KDPI-defined donor risk and additional recipient, immunologic, and perioperative factors. A multidomain, offer-time assessment may support more individualized acceptance decisions and improve utilization.
Source: Clinical Transplantation
DOI: 10.1111/ctr.70472
Authors: Xingyu Zhang, Chethan Puttarajappa, Frank Spitz, Jason Mial‐Anthony, Berkay Demirors, Abiha Abdullah, Vrishketan Sethi, Matthew Yu‐Sheng Lin, Andrew Crane, Winn Cashion, Charbel Elias, Han Shwe, Timothy Fokken, Bradley Phelp, Ryugen Takahashi, Hao Liu, Christof Kaltenmeier, Stalin Dharmayan, Vikraman Gunabushanam, Armando Ganoza, Martin N.Wijkstrom, Amit Tevar, Michele Molinari
Language: English
Subfield: Transplantation
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,550
OpenAlex ID: W7127738923