Evidence map›Paper›PMID 40303214›Full record

ArticleKidney international reports2025

Outcomes for Patients With a Deceased Donor Kidney Offer in the New Allocation System.

Sumit Mohan, Miko Yu, Lindsey M Maclay, Joel T Adler, Anne M Huml, Jesse D Schold, S Ali Husain

Abstract read
In one paragraph

Article in Kidney international reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Outcomes of Deceased Donor Kidney Transplants Allocated Out of Sequence in the United States.Clinical journal of the American Society of Nephrology : CJASN · 2026
    Observational
  3. Article
  4. Out-of-Sequence Placement of Deceased Donor Kidneys Is Exacerbating Inequities in the United States.Clinical journal of the American Society of Nephrology : CJASN · 2026
    Article
  5. 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

7 authors.

Sumit MohanDivision of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA.
Miko YuDivision of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA.
Lindsey M MaclayDivision of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA.
Joel T AdlerDivision of Transplantation, Department of Surgery and Perioperative Care, Dell Medical School at the University of Texas at Austin, Austin, Texas, USA.
Anne M HumlDepartment of Kidney Medicine, Cleveland Clinic, Cleveland, Ohio, USA.
Jesse D ScholdDepartment of Surgery, University of Colorado - Anschutz Medical Campus, Aurora, Colorado, USA.
S Ali HusainDivision of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA.

Funding

Continuous Therapeutic Drug Monitoring of Antibiotics in CRRTR01DK126739 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MOHAN, SUMIT · 2021 to 2024
$2.8M
India - Factors of CKDu in Uddanam Study (India-FOCUS)U01DK130058 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Vivekanand Jha, Sumit Mohan · 2021 to 2026
$2.6M
5/14 APOL1 Long-term Kidney Transplantation Outcomes Network (APOLLO) Clinical CenterU01DK116066 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Sumit Mohan, Deirdre Sawinski · 2017 to 2026
$2.5M
Increasing Minority Population Awareness through Community Teaching for Improved Organ Donation (IMPACT for Improved Organ Donation)R01DK114893 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MOHAN, SUMIT · 2017 to 2021
$1.2M
Using Decision Making Science to Optimize Deceased Donor Kidney AllocationK23DK133729 · NIDDK · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI HUSAIN, SYED ALI · 2022 to 2025
$678k
NIDDK NIH HHS K23 DK133729NIDDK NIH HHS R01 DK114893NIDDK NIH HHS R01 DK126739NIDDK NIH HHS U01 DK116066NIDDK NIH HHS U01 DK130058
6 · The paper itself

Abstract

Introduction: In the United States (US), disparities in access to kidney transplantation exist for waitlisted candidates with end-stage kidney disease. Meanwhile, changes in kidney allocation policy have been associated with a dramatic increase in the number of organ offers declined before an organ is successfully placed. Methods: We describe transplant and mortality rates for waitlisted candidates from 2015 to 2022 following these allocation changes. Results: Among 249,145 incident waitlisted adults, 180,039 received at least 1 offer and were included in the study. Of these, 37.7% received a deceased donor kidney allograft, 14.7% received a living donor allograft, 7.4% died while on the waiting list, 12.7% were removed, and 27.5% were still waitlisted by the study end period. Overall, candidates' median number of days to receiving their first offer declined from 20 (7-48) in 2015 to 5 (2-13) in 2022. Candidates who died while on the waiting list received a median of 25 (9-56) offers and candidates who were removed received a median of 22 (8-53) offers during the study period. The total number of offers generated by the match-run algorithm, including those from nonutilized kidneys, increased sharply from 7,911,688 offers in 2015 to 13,682,914 in 2019, and to 29,332,516 in 2022. Conclusion: These findings emphasize the inefficiencies inherent in our current allocation algorithms and the need to rethink how waitlisted patients are prioritized for a given deceased donor organ in order to maximize the probability of appropriate utilization of lifesaving organs .

Indexed as

access to transplantkidney allocation

Identifiers

PMID40303214
PMCPMC12034855

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.