Evidence map›Paper›PMID 41531838›Full record

ArticleTransplantation direct2026

Quantifying Center-level Aggressiveness in Transplanting Suboptimal, Deceased Donor Kidneys in the United States.

Teresa Po-Yu Chiang, Mackenzie A Eagleson, Jennifer D Motter, Michelle R Krach, Hannah C Sung, Nicholas L Wood, Dorry L Segev, Darren E Stewart, Allan B Massie, Jacqueline M Garonzik-Wang

Abstract read
In one paragraph

Article in Transplantation direct, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Teresa Po-Yu ChiangDepartment of Surgery, NYU Grossman School of Medicine, New York City, NY.ORCID https://orcid.org/0000-0003-0601-7420
Mackenzie A EaglesonDepartment of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD.ORCID https://orcid.org/0000-0002-0797-7960
Jennifer D MotterDepartment of Surgery, NYU Grossman School of Medicine, New York City, NY.ORCID https://orcid.org/0000-0003-1750-0119
Michelle R KrachDepartment of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD.
Hannah C SungDepartment of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD.ORCID https://orcid.org/0000-0003-4531-2094
Nicholas L WoodChronic Disease Research Group, Hennepin Healthcare Research Institute, Minneapolis, MN.ORCID https://orcid.org/0000-0003-0768-3759
Dorry L SegevDepartment of Surgery, NYU Grossman School of Medicine, New York City, NY.ORCID https://orcid.org/0000-0002-1924-4801
Darren E StewartDepartment of Surgery, NYU Grossman School of Medicine, New York City, NY.ORCID https://orcid.org/0000-0002-6764-4842
Allan B MassieDepartment of Surgery, NYU Grossman School of Medicine, New York City, NY.ORCID https://orcid.org/0000-0002-5288-5125
Jacqueline M Garonzik-WangDepartment of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI.ORCID https://orcid.org/0000-0002-2789-7503

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Understanding center-level decision-making for suboptimal kidney (SOK) offers is critical to ensure utilization of all transplantable kidneys. Methods: We quantified center-level variation in accepting SOK deceased donor kidney transplant (DDKT) offers using 2021-2023 national registry data. SOK subtypes included: donor age >60, ultimate cold ischemia time >24 h, hepatitis C positive, terminal serum creatinine >2.0 mg/dL, donation after circulatory death, kidney donor profile index >85%, and public health service increased risk donors. Gini coefficient (Gini) was used to analyze inequality in DDKT utilization by SOK subtype. Multilevel logistic regression models were used to calculate the median odds ratio (mOR), measuring center-level variation in accepting SOK donor offers among adult centers. Results: Of all DDKTs, 72.6% were from donors with at least 1 SOK characteristic. Inequality persisted in utilization of SOK DDKTs (Gini of all SOKs: 0.53, Gini of all non-SOKs: 0.47). The 193 adult centers accepted a median (interquartile range) of 12.5% (8.4%-19.2%) offered non-SOK donors and 7.2% (4.6%-10.8%) offered SOK donors. Non-SOK donors and SOK donors were refused by a median (interquartile range) of 5 (3-10) and 9 (4-23) centers, respectively. The SOK subtypes with the least and the most center-level variance in acceptance were increased risk donor (mOR = 2.06) and cold ischemia time >36 h (mOR = 4.86), respectively. Conclusions: Centers vary sharply in their willingness to accept certain types of SOK offers. Informing centers of their patterns of accepting specific donor phenotypes compared with their peers may motivate centers to accept more SOKs for clinically suitable recipients, thus improving patient access to DDKT.

Identifiers

PMID41531838
PMCPMC12795041

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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.