Evidence map›Paper›PMID 41637670›Full record

ArticleClinical transplantation2026

"Rethinking High-KDPI Kidneys: A Multidomain Approach to Predicting Success".

Xingyu Zhang, Chethan Puttarajappa, Frank Spitz, Jason Mial-Anthony, Berkay Demirors, Abiha Abdullah, Vrishketan Sethi, Matthew Yu-Sheng Lin, Andrew Crane, Winn Cashion and 13 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical transplantation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors.

Xingyu ZhangBiostatistics and Epidemiology, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Chethan PuttarajappaDepartment of Medicine, Division of Nephrology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-4856-9242
Frank SpitzDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Jason Mial-AnthonyDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Berkay DemirorsDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.ORCID https://orcid.org/0000-0003-0321-4365
Abiha AbdullahDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Vrishketan SethiDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Matthew Yu-Sheng LinDepartment of Surgery, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
Andrew CraneDepartment of Surgery, Division of Abdominal Transplantation, Willis Knighton J. C. McDonald Transplant Center, Shreveport, Louisiana, USA.
Winn CashionDepartment of Medicine, Division of Nephrology, Maine Health, Portland, Maine, USA.
Charbel EliasDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Han ShweDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Timothy FokkenDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Bradley PhelpDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Ryugen TakahashiDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Hao LiuDepartment of Surgery, Division of Abdominal Transplantation, Houston Methodist J.C. Walter Jr. Transplant Center, Houston, Texas, USA.
Christof KaltenmeierDepartment of Surgery, Division of Abdominal Transplantation, Medical University of South Carolina, Charleston, South Carolina, USA.
Stalin DharmayanDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Vikraman GunabushanamDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Armando GanozaDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Martin N WijkstromDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Amit TevarDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Michele MolinariDepartment of Surgery, Division of Abdominal Transplantation, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-9763-6253

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

methodsThis 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.

resultsAmong 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.

conclusionsOutcomes 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.

Indexed as

Delayed Graft FunctionDonor SelectionGraft RejectionKidney Failure, ChronicKidney TransplantationPostoperative ComplicationsRegistriesTissue and Organ ProcurementTissue DonorsAdultFemaleFollow-Up StudiesGlomerular Filtration RateGraft SurvivalHumansKidney Function Testshigh‐kdpikidney donor profile index (kdpi)kidney transplantpost‐transplant outcomesrisk prediction

Identifiers

PMID41637670
PMCPMC12872201

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.