Evidence map›Paper›PMID 32492441›Full record

ArticleThe Annals of thoracic surgery2020

Predictors of Older Donor Lung Use: Are We Too Good at Saying No?

Ashley Y Choi, Oliver K Jawitz, Vignesh Raman, Samantha E Halpern, John C Haney, Jacob A Klapper, Matthew G Hartwig

Open access · greenAbstract read
In one paragraph

Article in The Annals of thoracic surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Acceptance of deceased donor livers in the United Kingdom - development of a liver "donor utilisation index".Transplant international : official journal of the European Society for Organ Transplantation · 2026
    Article
  4. Article
  5. Development and validation of the lung donor (LUNDON) acceptability score for pulmonary transplantation.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2023
    Article
  6. Article
  7. Review
  8. A three-tier system for evaluation of organ procurement organizations' willingness to pursue and utilize nonideal donor lungs.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2021
    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 at 2 institutions in 1 country.

Ashley Y ChoiSchool of Medicine, Duke University, Durham, North Carolina. Electronic address: choi.ashley@duke.edu.
Oliver K JawitzDivision of Cardiovascular and Thoracic Surgery, Department of Surgery, Duke University Medical Center, Durham, North Carolina.
Vignesh RamanDivision of Cardiovascular and Thoracic Surgery, Department of Surgery, Duke University Medical Center, Durham, North Carolina.
Samantha E HalpernSchool of Medicine, Duke University, Durham, North Carolina.
John C HaneyDivision of Cardiovascular and Thoracic Surgery, Department of Surgery, Duke University Medical Center, Durham, North Carolina.
Jacob A KlapperDivision of Cardiovascular and Thoracic Surgery, Department of Surgery, Duke University Medical Center, Durham, North Carolina.
Matthew G HartwigDivision of Cardiovascular and Thoracic Surgery, Department of Surgery, Duke University Medical Center, Durham, North Carolina.
Duke Medical Center · USDuke University · US

Funding

Postdoctoral Training in Cardiovascular Clinical ResearchT32HL069749 · NHLBI · DUKE UNIVERSITY · PI MARK, DANIEL B · 2003 to 2023
$6.7M
Translational Research in Surgical OncologyT32CA093245 · NCI · DUKE UNIVERSITY · PI ALLEN, PETER J, HARPOLE, DAVID H. · 2002 to 2020
$5.2M
NRSA Training CoreTL1TR002555 · NCATS · DUKE UNIVERSITY · PI EDELMAN, DAVID · 2018 to 2022
$3.7M
NCATS NIH HHS TL1 TR002555NCI NIH HHS T32 CA093245NHLBI NIH HHS T32 HL069749
6 · The paper itself

Abstract

backgroundPatterns of use of older donor lungs within this previously underused donor population are poorly characterized. This study examined factors associated with the use of older donor lung allografts and factors associated with survival in recipients of these lungs.

methodsAdult donors in the United Network for Organ Sharing registry who donated 1 or more organs for transplantation between 2006 and 2018 were analyzed and stratified into older (age >55 years) and younger (age ≤55 years) cohorts. Multivariable logistic and Cox regression were used to identify factors associated with transplantation of older donor lungs and factors associated with survival, respectively.

resultsOverall, 202,477 donors were included and stratified by age (older, 40,406 [20%]; younger, 162,071 [80%]). Compared with younger donors, older donors had an increased rate of consent for donation not requested by organ procurement organizations (7.5% vs 1.7%). Donor factors significantly associated with decreased lung use included male sex, increasing donor age, black race, Hispanic ethnicity, cigarette use, cocaine use, donation after circulatory death status, and PaO

conclusionsBarriers in consenting practices, concerns about organ function, and recipient survival prevent the widespread use of aged allografts for lung transplantation. Better understanding of factors associated with worse outcomes of older donors and modification of organ procurement organization consenting practices may increase the use of these higher-risk donor organs.

Indexed as

Lung TransplantationTissue DonorsAdultAgedAge FactorsFemaleHumansLogistic ModelsMaleMiddle AgedProportional Hazards ModelsTransplantation, Homologous

Identifiers

PMID32492441
PMCPMC7606398
OpenAlexW3030304825

What OpenQuestion holds

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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.