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Record W4298006436 · doi:10.1093/eurheartj/ehac542

Left main coronary disease: evolving management concepts

2022· review· en· W4298006436 on OpenAlexaff
Paul W. Armstrong, Eric Bates, Mario Gaudino

Bibliographic record

VenueEuropean Heart Journal · 2022
Typereview
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsCanadian VIGOUR CentreUniversity of Alberta HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineCoronary artery diseaseRevascularizationCardiologyMedical therapyArteryStenosisInternal medicinePercutaneousDiseaseInterventional cardiologyCoronary artery bypass surgeryPercutaneous coronary interventionIntensive care medicineMyocardial infarction

Abstract

fetched live from OpenAlex

Remarkable advances in the management of coronary artery disease have enhanced our approach to left main coronary artery (LMCA) disease. The traditional role of coronary artery bypass graft surgery has been challenged by the less invasive percutaneous coronary interventional approach. Additionally, major strides in optimal medical therapy now provide a rich menu of treatment choices in selected circumstances. Although a LMCA stenosis >70% is an acceptable threshold for revascularization, those patients with a LMCA narrowing between 40 and 69% present a more complex scenario. This review examines the relative merits of the different treatment options, addresses key diagnostic and therapeutic unknowns, and identifies future work likely to advance progress.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.764
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0300.001

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 head0.096
GPT teacher head0.391
Teacher spread0.296 · 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
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

Citations13
Published2022
Admission routes1
Has abstractyes

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