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Record W1662838686 · doi:10.1097/hco.0000000000000220

Operative mortality with coronary artery bypass graft

2015· review· en· W1662838686 on OpenAlexaff
Donna May Kimmaliardjuk, Hadi Toeg, David Glineur, Benjamin Sohmer, Marc Ruel

Bibliographic record

VenueCurrent Opinion in Cardiology · 2015
Typereview
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineBypass graftingRevascularizationCardiopulmonary bypassArterySpecialtySAFERCardiologyMyocardial revascularizationInternal medicineSurgeryIntensive care medicineMyocardial infarction

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Coronary artery bypass graft (CABG) surgery has evolved and become much safer since its inception. This article outlines recent strategies in optimizing CABG mortality. RECENT FINDINGS: Improving operative mortality around CABG relates to five components. These include the role of relevant quality indicators; improved CABG techniques, such as multiple arterial grafting with less manipulation of the aorta; improvements in cardiopulmonary bypass; refinements in cardiac anaesthesia along with postoperative care; and the development of centres of excellence. SUMMARY: The development of advanced surgical revascularization techniques raises the question as to whether CABG expertise should be considered a sub-specialty of cardiac surgery. An expert CABG surgeon should be able to appropriately utilize several different revascularization techniques to adjust the operation to the patient, rather than the contrary.

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)0.004
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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.155
GPT teacher head0.440
Teacher spread0.285 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

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