Robot-assisted computer enhanced closed-chest coronary surgery: preliminary experience using a Harmonic Scalpel and ZEUS.
Bibliographic record
Abstract
BACKGROUND: Successful endoscopic harvesting of arterial conduits is critical to the performance of totally endoscopic bypass grafting. Recent success with computer-enhanced robotic systems in the performance of endoscopic single vessel coronary artery bypass (ENDOCAB) has paved the way for developing techniques for multivessel ENDOCAB. The Harmonic Scalpel (Ethicon Endo-Surgery, Cincinnati, OH) has previously demonstrated versatility and efficacy in manual endoscopic internal thoracic artery (ITA) harvesting. This study was undertaken to determine the feasibility of adapting this technology to a robotic telemanipulation system and its safety and efficacy in telerobotic ITA harvesting. METHODS: The Harmonic Scalpel was adapted to the ZEUS robotic surgical system (Computer Motion, Goleta, CA) and used to harvest the ITA in 19 patients undergoing multivessel off-pump coronary artery bypass (OPCAB) surgery. With the left lung collapsed, the ITA was harvested in all patients with CO2 insufflation through three 5 mm ports in the left chest. Postoperative angiography and transthoracic Doppler studies were performed in all patients. RESULTS: There were no ITA injuries and patients tolerated insufflation without hemodynamic compromise. Side branches were controlled easily without bleeding. Average ITA harvest time was 65 +/- 21 minutes. All vessels were patent after harvesting and demonstrated no angiographic evidence of injury. CONCLUSIONS: This paper demonstrates a technique by which the Harmonic Scalpel can be readily adapted to the ZEUS robotic telemanipulation system. Using this system, ITA's can be safely harvested totally endoscopically within a reasonable time frame for patients undergoing ENDOCAB.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".