Robotic Surgery, the First 100 Cases: Where Do We Go from Here?
Bibliographic record
Abstract
Abstract Background: Since the robot-assisted cardiac surgery program at this center was initiated in September 1998 the results have been regularly critically evaluated. We report a retrospective review of the first 100 robotic procedures and their evolution. Methods: Between September 1998 and May 2001, 146 patients underwent robot-assisted procedures. All procedures were performed using the Aesop robotically controlled camera or the Zeus robotic system. A harmonic scalpel was used for all internal thoracic artery (ITA) dissections whether the dissections were performed manually or with the Zeus robotic system. Results: There were 123 closed-heart and 23 open-heart procedures, which included 8 atrial-septal defect repairs, 11 mitral valve repairs, 4 mitral valve replacements, 57 Aesop ITA takedowns, 68 Zeus ITA takedowns, and 13 totally endoscopic coronary artery bypass grafts. Graft patency in Aesop and Zeus ITA takedown groups was 96%. All the patients were New York Heart Association class I after their procedures. Conclusion: With the development of surgical robots, it has been possible to perform endoscopic cardiac surgery for selected cases. Future directions will be demonstrated, including telementoring, telesurgery, and Zeus-assisted initiatives in cardiac surgery and other surgical disciplines.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".