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Record W2951991056 · doi:10.1097/hco.0000000000000654

Right internal thoracic or radial artery as the second arterial conduit for coronary artery bypass surgery

2019· review· en· W2951991056 on OpenAlexaff
Cristiano Spadaccio, Stephen E. Fremes, Mario Gaudino

Bibliographic record

VenueCurrent Opinion in Cardiology · 2019
Typereview
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRadial arteryInternal thoracic arteryArteryStenosisSurgeryCircumflexCoronary artery bypass surgeryCardiologyInternal medicineRadiologyBypass grafting

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To summarize the available evidence on the use of the right internal thoracic artery (RITA) and the radial artery as the second arterial graft in coronary artery bypass surgery. RECENT FINDINGS: The current data support the equipoise of the two conduits in terms of clinical and angiographic outcomes. Both RITA and radial artery have better patency than saphenous vein grafts. The use of the RITA carries an increased risk of deep sternal wound infection (DSWI) if the artery is harvested as pedicle. Bilateral internal thoracic artery grafting is more technically demanding than radial artery use and there is a volume-outcome relationship in terms of mortality and incidence of DSWI. The radial artery is preferable over RITA in right-sided or distal circumflex artery targets with high-degree stenosis and in patients at higher risk for DSWI, whereas it is not recommended to graft vessels with moderate stenosis and in cases of insufficient collateralization from the ulnar artery or previous transradial procedures. SUMMARY: The patency rate and clinical outcomes of radial artery and RITA are similar. The use of one or the other should be based on a careful evaluation of the patient's coronary anatomy and comorbidities, the conduit availability and the surgeon's and center's experience.

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 score0.825
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
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)0.0010.000

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 head0.131
GPT teacher head0.412
Teacher spread0.281 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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