Robotic-Assisted Off-Pump Sole Transmyocardial Revascularization: Case Report
Bibliographic record
Abstract
Thoracoscopic transmyocardial revascularization (TMR) has been recently demonstrated. We report 2 patients who underwent robotic-assisted thoracoscopic off-pump sole TMR. A 2-inch minimally invasive left anterolateral thoracotomy was made. Pericardial dissection and TMR were performed in an open manner facilitated by improved visualization using voice-activated robotic-assisted thoracoscopy (AESOP, Computer Motion, Santa Barbara, CA, USA). Patient 1 was a 73-year-old man with class IV angina who underwent coronary artery bypass grafting (CABG) x4 20 years earlier. Cardiac catheterization revealed occluded grafts, no native vessels that were amenable to percutaneous coronary intervention (PCI) or CABG, and an ejection fraction (EF) of 55%. Forty-five Holmium-Yag (CardioGenesis, Foothill Ranch, CA, USA) laser channels were created in the left ventricular wall. Total operating room (OR) time was 93 minutes. He was extubated in the OR and was discharged from the intensive care unit (ICU) in 18 hours and from the hospital on the second postoperative day angina free. Patient 2 was a 48-year-old woman with class IV angina who had undergone CABG x6 3 years earlier but who had persistent chest pain following the revascularization. After 12 cardiac readmissions in 1 year, including multiple PCIs, a recent catheterization showed patent grafts except for the circumflex branches and an EF of 45%. Forty-six channels were created in the left ventricle in a similar fashion. OR time was 62 minutes, ICU time was 20 hours, and postoperative length of stay was 2 days. The patient also was angina free at discharge. This report suggests that robotic-assisted thoracoscopy provides enhanced visualization and efficient delivery during off-pump sole TMR, and this technique may be associated with reduced operative times and improved recovery time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".