Evidence map›Paper›PMID 40837549›Full record

ReviewJHLT open2025

Contributions, bias, and research gaps in large animal ex vivo lung perfusion models: A systematic review.

Shane Fisher, James O'Connor, Karen Redmond

Abstract readReview
In one paragraph

Review in JHLT open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

3 authors.

Shane FisherDepartment of Medicine, St James's Hospital Dublin, Dublin, Ireland.
James O'ConnorRoyal College of Surgeons Ireland, Dublin, Ireland.
Karen RedmondRoyal College of Surgeons Ireland, Dublin, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: A major challenge in lung transplantation is the shortage of viable donor lungs. Ex vivo lung perfusion (EVLP) has emerged as an effective assessment and conditioning tool to expand the donor lung pool. This systematic review sought to establish the contribution of large animal models to EVLP development and application, particularly focusing on assessing the risk of bias and the certainty of evidence. Methods: A strategic literature search was conducted using a predefined pro forma. Relevant data were extracted, and thematic analysis was applied for qualitative synthesis of key measures. Methodological quality and bias risk were assessed using systematic review centre for laboratory animal experimentation's risk of bias tool, and certainty of evidence was evaluated using the grading of recommendations assessment, development and evaluation Framework. Results: A total of 32 studies met the inclusion criteria, using porcine, ovine, rabbit, and canine models. Key themes included EVLP's role in donor lung assessment and preservation, marginal donor lung repair, and as an experimental translational platform. All studies were assessed with the systematic review centre for laboratory animal experimentation tool and had a high or unclear risk of bias. Twenty-eight (87.5%) showed low certainty of evidence, 2 (6.25%) very low, and 2 (6.25%) moderate, raising concerns about overall evidence strength. Conclusions: Large animal EVLP models have significantly advanced donor lung preservation, reconditioning, and therapeutic intervention. However, methodological bias remains a concern due to inconsistent adherence to reporting and procedural standards. Greater conformity to standardized protocols is pivotal to improve the reliability, reproducibility, and translational value of future EVLP research.

Indexed as

ex vivo lung perfusionlarge animal modellung transplantationpreclinical modelstranslational research

Identifiers

PMID40837549
PMCPMC12362082

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.