MétaCan
Menu
Back to cohort
Record W2060974940 · doi:10.1097/hco.0b013e3283653fd1

Minimally invasive coronary artery bypass grafting

2013· review· en· W2060974940 on OpenAlexaff
Marc Ruel, Dai Une, Johannes Bonatti, Joseph T. McGinn

Bibliographic record

VenueCurrent Opinion in Cardiology · 2013
Typereview
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineRevascularizationThoracotomyCardiopulmonary bypassArteryBypass graftingCardiologySurgeryMedian sternotomyInternal medicineAngiographyRadiologyMyocardial infarction

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Minimally invasive coronary artery bypass grafting (MICS CABG) consists of single-vessel or multivessel revascularization via a small left thoracotomy, and has been proposed as an alternative to a standard sternotomy approach. The purpose of this article is to examine the current status of MICS CABG and discuss its future directions. RECENT FINDINGS: Experience in the first 450 cases was reported in 2009, and established the efficacy and safety of a small thoracotomy approach for multivessel and single-vessel revascularization. In addition to earlier recovery and rehabilitation, MICS CABG is associated with fewer transfusions and fewer wound infections than off-pump CABG. Recently, the MICS CABG Patency Study showed excellent graft patency in patients assessed by 64-slice computed tomography angiography 6 months after operation. We also showed that the use of cardiopulmonary bypass assistance may help alleviate some of the learning curve inherent in this operation. SUMMARY: MICS CABG has developed into a reproducible, high-quality, complete surgical revascularization alternative to conventional CABG. Preservation of sternal integrity allows patients to recover earlier, require fewer transfusions, and experience fewer infections. Further research on expanding the applicability of MICS CABG and enhancing its advantages over conventional CABG is warranted.

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 score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.000
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 head0.105
GPT teacher head0.381
Teacher spread0.275 · 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

Citations38
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in CardiologySame topicCardiac and Coronary Surgery TechniquesFrench-language works237,207