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Record W2737671506 · doi:10.1007/s40119-017-0094-6

Management and Prevention of Saphenous Vein Graft Failure: A Review

2017· review· en· W2737671506 on OpenAlexaff
Peter McKavanagh, Bobby Yanagawa, George Zawadowski, Asim N. Cheema

Bibliographic record

VenueCardiology and Therapy · 2017
Typereview
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineRevascularizationSaphenous vein graftCoronary artery diseaseCardiologyInternal medicineInternal thoracic arteryArteryVeinBypass graftingPercutaneousPercutaneous coronary interventionSurgeryMedical therapyMyocardial infarction

Abstract

fetched live from OpenAlex

Coronary artery bypass grafting (CABG) remains a vital treatment for patients with multivessel coronary artery disease (CAD), especially diabetics. The long-term benefit of the internal thoracic artery graft is well established and remains the gold standard for revascularization of severe CAD. It is not always possible to achieve complete revascularization through arterial grafts, necessitating the use of saphenous vein grafts (SVG). Unfortunately, SVGs do not have the same longevity, and their failure is associated with significant adverse cardiac outcomes and mortality. This paper reviews the pathogenesis of SVG failure, highlighting the difference between early, intermediate, and late failure. It also addresses the different surgical techniques that affect the incidence of SVG failure, as well as the medical and percutaneous prevention and treatment options in contemporary practice.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.064
GPT teacher head0.371
Teacher spread0.307 · 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 designNot applicable
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

Citations89
Published2017
Admission routes1
Has abstractyes

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