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Record W4392247660 · doi:10.1016/j.healun.2024.02.1454

Randomized trial of routine versus on-demand intraoperative extracorporeal membrane oxygenation in lung transplantation: A feasibility study

2024· article· en· W4392247660 on OpenAlexaff
Basil Nasir, Jason Weatherald, Tim Ramsay, Marcelo Cypel, Laura Donahoe, Chris Durkin, Travis Schisler, Jayan Nagendran, Moïshe Liberman, Caroline Landry, Charles Overbeek, Alex Moore, Pasquale Ferraro

Bibliographic record

VenueThe Journal of Heart and Lung Transplantation · 2024
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsVancouver General HospitalUniversity of British Columbia HospitalUniversity of AlbertaUniversity Health NetworkOttawa HospitalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsExtracorporeal membrane oxygenationMedicineLung transplantationRandomized controlled trialTransplantationClinical trialSurgeryMulticenter trialSingle CenterIntensive care medicineMulticenter studyInternal medicine

Abstract

fetched live from OpenAlex

In most centers, extracorporeal membrane oxygenation (ECMO) is the preferred means to provide cardiopulmonary support during lung transplantation. However, there is controversy about whether intraoperative venoarterial (VA) ECMO should be used routinely or selectively. A randomized controlled trial is the best way to address this controversy. In this publication, we describe a feasibility study to assess the practicality of a protocol comparing routine versus selective VA-ECMO during lung transplantation. This prospective, single-center, randomized controlled trial screened all patients undergoing lung transplantation. Exclusion criteria include retransplantation, multiorgan transplantation, and cases where ECMO is mandatory. We determined that the trial would be feasible if we could recruit 19 participants over 6 months with less than 10% protocol violations. Based on the completed feasibility study, we conclude that the protocol is feasible and safe, giving us the impetus to pursue a multicenter trial with little risk of failure due to low recruitment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0110.002

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 head0.040
GPT teacher head0.376
Teacher spread0.336 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations4
Published2024
Admission routes1
Has abstractno

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