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Expert Systematic Review on the Choice of Conduits for Coronary Artery Bypass Grafting: Endorsed by the European Association for Cardio-Thoracic Surgery (EACTS) and The Society of Thoracic Surgeons (STS)

2023· article· en· W4385502437 on OpenAlexaff
Mario Gaudino, Faisal G. Bakaeen, Sigrid Sandner, Gabriel S. Aldea, Hirokuni Arai, Joanna Chikwe, Scott Firestone, Stephen E. Fremes, Walter J. Gomes, Ki Bong-Kim, Kalie Kisson, Paul Kurlansky, Jennifer S. Lawton, Daniel Navia, John D. Puskas, Marc Ruel, Joseph F. Sabik, Thomas A. Schwann, David P. Taggart, James Tatoulis, Moritz Wyler von Ballmoos

Bibliographic record

VenueThe Annals of Thoracic Surgery · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsUniversity of OttawaHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineElectrical conduitBypass graftingArteryInternal thoracic arteryCardiothoracic surgerySurgeryCardiologyCardiac surgeryCoronary artery bypass surgeryVeinInternal medicine

Abstract

fetched live from OpenAlex

Coronary artery bypass grafting surgery (CABG) is the most common cardiac surgery operation in the USA and worldwide.1 The first choice of conduit and standard of care is use of the left internal thoracic artery (LITA) to the left anterior descending (LAD) artery. While the saphenous vein graft (SVG) remains the most commonly used conduit for multivessel CABG, there is a variety of arterial conduits and technical variations of the SVG that may also be used for the operation. Individualization of the grafting strategy to the anatomic and clinical characteristics of each patient, as well as to the operating surgeon’s experience and comfort with the different conduits, is key to the success of the operation.

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)0.051
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0510.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.113
GPT teacher head0.379
Teacher spread0.266 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations21
Published2023
Admission routes1
Has abstractyes

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