Evidence map›Paper›PMID 41542700›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Newly designed expedited allocation pathways cannot be expected to rely on data that does not currently exist.

Cameron D Ekanayake, Syed A Husain, Miko E Yu, Joel T Adler, Chetan Sree Muppavarapu, Jesse D Schold, Sumit Mohan

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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

5 · Who and what money

Authors and funding

7 authors.

Cameron D EkanayakeORCID 0000-0002-6891-7865
Chetan Sree Muppavarapu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Allocation out of sequence (AOOS) allows organ procurement organizations (OPOs) to bypass the standard match-run to expedite kidney placement and prevent nonuse. Inclusion of all AOOS attempts is vital when attempting to assess impact of AOOS on organ utility, including those attempts that do not lead to successful transplant. We assessed the frequency of AOOS documentation in discarded kidneys. Using Scientific Registry of Transplant Recipients (SRTR) Potential Transplant Recipient (PTR) offer data from 2021-2024, we identified match-runs with at least one discarded kidney. AOOS was defined according to Health Resources and Services Administration (HRSA) guidelines and match runs were stratified by kidney recovery and disposition patterns, focusing on 2024 when AOOS was well established. AOOS coding frequency was assessed within each group and across OPOs. In 2024, only 4.3% of all match-runs with at least one discarded kidney contained evidence of AOOS documentation. Across OPOs, AOOS-coded discards ranged from 0.0% to 17.1% (median 3.9%, IQR [2.7-7.6%]). AOOS documentation among discarded kidneys remains rare and inconsistent, suggesting major data-capture deficiencies when attempting to accurately assess AOOS efforts. Improved AOOS reporting is essential before future expedited allocation pathways can be effectively evaluated or implemented.

Identifiers

PMID41542700
PMCPMC12803366

What OpenQuestion holds

Textmetadata
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.