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Record W3196729662 · doi:10.1097/hco.0000000000000906

Less invasive multivessel coronary artery bypass grafting: now is the time

2021· review· en· W3196729662 on OpenAlexaff
Sathyaki Nambala, Yugal Mishra, Marc Ruel

Bibliographic record

VenueCurrent Opinion in Cardiology · 2021
Typereview
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineBypass graftingArteryCardiopulmonary bypassRevascularizationCardiologyInternal medicineGraftingMinimally invasive cardiac surgerySurgeryMyocardial infarction

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Less invasive multivessel coronary artery bypass grafting techniques have seen a progressive evolution over the last two decades. In their current state, they are easily reproduced and applicable to most patients requiring multivessel revascularization. The purpose of this review is to highlight their importance among a spectrum of evolving therapies and the accruing evidence in their favour. RECENT FINDINGS: The first large dual center experience with minimally invasive coronary artery bypass grafting (MICS CABG) demonstrated the feasibility of performing multivessel surgical revascularization without the need for sternotomy or cardiopulmonary bypass. Subsequent angiographic studies to assess graft patency showed excellent early results. Studies comparing MICS CABG to conventional CABG demonstrate faster recovery while reducing hospitalization and cost. SUMMARY: Multivessel less invasive coronary artery bypass grafting is basically limited to two procedures, MICS CABG and robotically assisted totally endoscopic CABG (TECAB). MICS CABG has evolved as a procedure that preserves the safety and efficacy of conventional CABG while avoiding the associated morbidity. It is reproducible, versatile and holds promise as the procedure of choice for multivessel coronary revascularization in the future. TECAB is likely the pinnacle of minimally invasive coronary surgery, the growth of which is hindered by widespread acceptance and industry involvement.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.106
GPT teacher head0.384
Teacher spread0.277 · 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 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

Citations12
Published2021
Admission routes1
Has abstractyes

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