MétaCan
Menu
Back to cohort
Record W1937892252 · doi:10.1002/ccd.24554

Current percutaneous treatment strategies for saphenous vein graft disease

2012· review· en· W1937892252 on OpenAlexaff
Kostantinos Marmagkiolis, Cindy L. Grines, Luc Bilodeau

Bibliographic record

VenueCatheterization and Cardiovascular Interventions · 2012
Typereview
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineRevascularizationAngioplastyPercutaneousCoronary artery diseasePerforationStentSurgeryCardiologyPercutaneous coronary interventionCoronary artery bypass surgeryBalloonInternal medicineArteryMyocardial infarction

Abstract

fetched live from OpenAlex

Coronary artery bypass graft surgery remains one of the most widely performed surgical procedures in North America and aortocoronary saphenous vein grafts (SVG) are the most frequently used surgical conduits. SVG disease (SVGD) remains the leading cause of symptomatic coronary artery disease postcoronary artery bypass graft. When optimal medical therapy is ineffective, repeat surgery is associated with higher mortality combined with less favorable clinical and angiographic results, thus percutaneous revascularization on SVG is currently the standard of care for the revascularization of SVGD. Balloon angioplasty, bare metal stents, polytetrafluoroethylene-covered stents, and drug-eluting stents have been extensively investigated for SVG interventions. Multiple recent randomized trials and meta-analyses have confirmed the pathophysiologic and clinical differences between SVGD and coronary artery disease. Decisions such as patient selection, premedication, stent, and protection device characteristics should be carefully considered to achieve optimal procedural and clinical results. Acute coronary syndromes due to SVG involvement, chronic total occlusions, retrograde approaches, and SVG perforation management are newer fields requesting additional research.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.008
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)0.0000.000

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 head0.119
GPT teacher head0.377
Teacher spread0.258 · 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 designOther design
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

Citations9
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCatheterization and Cardiovascular InterventionsSame topicCoronary Interventions and DiagnosticsFrench-language works237,207