MétaCan
Menu
Back to cohort
Record W4413419778 · doi:10.1097/txd.0000000000001855

Platelet Activation on Lung Function During Ex Vivo Lung Perfusion, Lung Transplantation, and the Role of Antiplatelet Therapy: A Narrative Review

2025· review· en· W4413419778 on OpenAlexaff
Ryaan EL‐Andari, Jimmy J.H. Kang, Nicholas M. Fialka, Jason Weatherald, Parnian Alavi, Nadia Jahroudi, Darren H. Freed, Jayan Nagendran

Bibliographic record

VenueTransplantation Direct · 2025
Typereview
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineLung transplantationLungEx vivoCardiologyPlateletLung functionInternal medicineIn vivo

Abstract

fetched live from OpenAlex

Background: Ischemia/reperfusion injury after lung transplantation is a significant cause of morbidity. In the realm of ex vivo lung perfusion (EVLP), inflammation, edema formation, and reduced compliance have limited the durability of EVLP. Previous evidence has suggested that platelet activation and thrombosis may play a role in both conditions. Methods: A literature search of PubMed and Embase was conducted, including all articles describing all human or animal investigations of platelet activation or the use of antiplatelet agents in the settings of EVLP or lung transplantation. Articles published from database inception to July 15, 2024, were analyzed. Results: In total, 9 studies were included in the review. Studies on EVLP have found an association between platelet activation and adverse effects on lung function, whereas in lung transplantation, platelet activation appears to play a role in primary graft dysfunction. In both settings, the inhibition of platelets ameliorated these effects. Conclusions: Platelet activation in EVLP and lung transplantation results in distal arterial thrombosis and has been associated with graft dysfunction. The use of antiplatelet agents in the included studies was associated with reduced lung injury and improved lung function on EVLP or during lung transplantation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.452
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.328
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueTransplantation DirectSame topicTransplantation: Methods and OutcomesFrench-language works237,207