RAVECAB: improving outcome in off-pump minimal access surgery with robotic assistance and video enhancement.
Bibliographic record
Abstract
OBJECTIVE: To determine the efficacy of using the harmonic scalpel and robotic assistance to facilitate thoracoscopic harvest of the internal thoracic artery (ITA). DESIGN: A case series. SETTING: London Health Sciences Centre, University of Western Ontario, London, Ont. PATIENTS AND METHODS: Fifteen consecutive patients requiring harvest of the ITA for coronary artery bypass grafting. INTERVENTION: Robot-assisted, video-enhanced coronary artery bypass (RAVECAB) through limited-access incisions, using the harmonic scalpel and a voice-activated robotic assistant. MAIN OUTCOME MEASURES: Ease and duration of the harvesting technique, complications of the procedure, graft flow and patency, and duration of postoperative hospitalization. RESULTS: RAVECAB facilitated thoracoscopic dissection of the ITA with the harmonic scalpel in all cases. There were no conversions to a standard approach and no reoperations for bleeding. The mean (and standard deviation) ITA harvest time was 64.1 (22.9) minutes (range from 40 to 118 minutes). Robotic voice command capture rate was greater than 95%. Mean (and SD) intraoperative graft flows were 33.1 (26.8) mL/min (range from 14 to 126 mL/min). There was 100% graft patency on postoperative angiography. There were no deaths, perioperaive myocardial infarction or arrhythmias. Mean (and SD) postoperative hospitalization was 3.3 (0.8) days. CONCLUSIONS: RAVECAB is a demanding procedure that addresses many of the disadvantages of the "conventional" minimally invasive coronary artery bypass. It allows complete pedicle dissection with minimal ITA manipulation and assures sufficient conduit length and a tension-free coronary artery anastomosis. All anastomoses were performed under direct vision through a 5- to 8-cm inferior mammary incision.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".