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Record W4405938442 · doi:10.3390/life15010037

Donor Lungs’ Procurement Implementation with Ex Vivo Lung Perfusion in a Low-Volume Lung Transplant Center

2024· article· en· W4405938442 on OpenAlexaboutno aff
Matteo Petroncini, Elena Salvaterra, Leonardo Valentini, Silvia Bonucchi, Niccolò Daddi, Saverio Pastore, Pietro Bertoglio, Piergiorgio Solli, Filippo Antonacci

Bibliographic record

VenueLife · 2024
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsnot available
FundersMinistero della Salute
KeywordsMedicineLungLung transplantationSepsisPerfusionTransplantationSurgeryInternal medicine

Abstract

fetched live from OpenAlex

(1) Background: Ex Vivo Lung Perfusion (EVLP) is a technique designed to assess and recondition marginal lungs, potentially expanding the donor pool and improving transplant outcomes (2) Methods: This retrospective study evaluated lung transplantation outcomes after EVLP. Donor lungs were assessed using the Toronto protocol, with data on hemodynamics, gas exchange, and perfusion parameters collected and analyzed. Post-transplant complications and survival rates were also examined. (3) Results: Over five years, 17 EVLP procedures were performed. Despite an improvement in lung function, 47% of donor lungs were rejected after EVLP. EVLP-reconditioned lungs showed comparable survival rates to standard transplants, but complications like sepsis and primary graft dysfunction (PGD) occurred. (4) Conclusions: EVLP shows promise in expanding the donor organ availability and reducing PGD, but nearly half of the lungs assessed were rejected. Further research is necessary to optimize EVLP and address potential complications like lung injury and sepsis.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.323
Teacher spread0.309 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2024
Admission routes1
Has abstractyes

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