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Record W2808195098 · doi:10.1097/imi.0000000000000499

A Novel Approach Using Computed Tomography Angiograms to Predict Sternotomy Or Complicated Anastomosis in Patients Undergoing Robotically Assisted Minimally Invasive Direct Coronary Artery Bypass

2018· article· en· W2808195098 on OpenAlexaff
Richard Cook, Anthony Fung, Edward Percy, John R. Mayo

Bibliographic record

VenueInnovations Technology and Techniques in Cardiothoracic and Vascular Surgery · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineAnastomosisArteryMedian sternotomyThoracotomyCoronary artery bypass surgeryRight coronary arteryCardiologySurgeryRadiologyInternal medicineMyocardial infarctionCoronary angiography

Abstract

fetched live from OpenAlex

OBJECTIVE: Robotically assisted minimally invasive direct coronary artery bypass is an alternative to sternotomy-based surgery in properly selected patients. Identifying the left anterior descending artery when it is deep in the epicardial fat can be particularly challenging through a 5- to 6-cm mini-thoracotomy incision. The objective of this study was to evaluate a technique for predicting conversion to sternotomy or complicated left anterior descending artery anastomosis using preoperative cardiac-gated computed tomography angiograms. METHODS: Retrospective review of 75 patients who underwent robotically assisted minimally invasive direct coronary artery bypass for whom a preoperative computed tomography angiogram was available. The distance from the left anterior descending artery to the myocardium was measured on a standardized "5-chamber" axial computed tomography view. The relative risk of sternotomy or complicated anastomosis was compared between patients whose left anterior descending artery was resting directly on the myocardium (left anterior descending artery to the myocardium distance = 0 mm) with those whose left anterior descending artery was resting above (left anterior descending artery to the myocardium distance > 0 mm). RESULTS: The average left anterior descending artery to the myocardium distance was 3.2 ± 2.6 mm (range = 0-11.5 mm). Fourteen patients (18.7%) had an left anterior descending artery to the myocardium distance of 0 mm. Of the entire group of 75 patients, 6 (8.0%) required conversion to sternotomy. Four others (5.3%) were reported to have a complication with the anastomosis intraoperatively. For patients with left anterior descending artery to the myocardium distance of 0 mm, the relative risk of sternotomy or complicated anastomosis was 18.0 (95% confidence interval = 4.3-75.6, P = 0.0001). CONCLUSIONS: In our experience, patients with left anterior descending artery to the myocardium distance of 0 mm were at significantly higher risk of either conversion to sternotomy or technically challenging anastomosis, with 8 (57.1%) of 14 patients in this group experiencing either end point. This novel measurement may be useful to identify patients who may have anatomy, which is not well suited to the robotically assisted minimally invasive direct coronary artery bypass approach.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.279
Teacher spread0.253 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations4
Published2018
Admission routes1
Has abstractyes

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