Evidence map›Paper›PMID 35730930›Full record

ArticleArtificial organs2022

Establishing an economical and widely accessible donation after circulatory death animal abattoir model for lung research using ex vivo lung perfusion.

Zhang Long Zhang, Niels Moeslund, Michiel Andy Hu, Roland Hoffmann, Leonie Harmina Venema, Caroline Van De Wauwer, Wim Timens, Toshihiro Okamoto, Erik Alfons Maria Verschuuren, Henri Gerrit Derk Leuvenink and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Artificial organs, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

12 authors at 3 institutions in 3 countries.

Zhang Long ZhangDepartment of Cardio-Thoracic Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0003-2137-7555
Niels MoeslundDepartment of Cardiology, Aarhus University Hospital, Aarhus, Denmark.ORCID https://orcid.org/0000-0003-0827-5263
Michiel Andy HuDepartment of Cardio-Thoracic Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0002-7355-099X
Roland HoffmannDepartment of Cardio-Thoracic Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0003-2473-4124
Leonie Harmina VenemaDepartment of Surgical Research, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0001-5556-6632
Caroline Van De WauwerDepartment of Cardio-Thoracic Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0002-0886-4917
Wim TimensDepartment of Pathology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0002-4146-6363
Toshihiro OkamotoDepartment of Thoracic Surgery and Lung Transplantation, Cleveland Clinic, Cleveland, Ohio, USA.ORCID https://orcid.org/0000-0002-8777-0467
Erik Alfons Maria VerschuurenDepartment of Cardio-Thoracic Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0002-6807-6744
Henri Gerrit Derk LeuveninkDepartment of Surgical Research, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0001-5036-2999
Hans EiskjaerDepartment of Cardiology, Aarhus University Hospital, Aarhus, Denmark.ORCID https://orcid.org/0000-0003-1520-1924
Michiel Elardus ErasmusDepartment of Cardio-Thoracic Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0002-6234-2976
University Medical Center Groningen · NLAarhus University Hospital · DKCleveland Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEx vivo lung perfusion (EVLP), is a platform that allows simultaneous testing and treatment of the lungs. However, use of EVLP is costly and requires access to lab animals and accompanying facilities. To increase the use of EVLP for research, we developed a method to perform EVLP using abattoir procured lungs. Furthermore, we were also able to significantly decrease costs.

methodsSix pair of lungs were procured from abattoir sheep. The lungs were then flushed and stored in ice for 3 h. A low-flow (20% of cardiac output) approach, a tidal volume of 6 ml/kg bodyweight and total perfusion time of 3 h were chosen. Perfusion fluids and circuits were self-made. Lung biopsies, perfusate collection, respiratory values, circulatory pressures were recorded and hourly blood gas analyses were performed.

resultsMean pO

conclusionsSheep lungs, acquired from an abattoir, can be ex vivo perfused under similar conditions as lab animal lungs with similar results regarding e.g., oxygenation and ATP restoration. Furthermore, costs can be significantly reduced by making use of this abattoir model. By increasing accessibility and lowering costs for experiments using lung perfusion, more results may be achieved in the field of lung diseases.

Indexed as

Lung TransplantationAbattoirsAdenosine TriphosphateAnimalsDisease Models, AnimalLungPerfusionSheepAdenosine Triphosphateabattoiranimalex vivo lung perfusionlow flow perfusionovineresearch modelsheep

Identifiers

PMID35730930
PMCPMC9796928
OpenAlexW4283313036

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.