Computer-enhanced telemanipulation in mitral valve repair: preliminary experience in Canada with the da Vinci robotic system.
Bibliographic record
Abstract
BACKGROUND: Investigation into the surgical application of robot technology continues to expand. We report on the first case series of robotic-assisted mitral valve (RAMV) repair in Canada with use of the da Vinci telemanipulation system (Intuitive Surgical, Sunnyvale, Calif.). METHODS: Between February 2004 and August 2004, 10 patients with normal left ventricular function and severe mitral valve regurgitation underwent RAMV repair with use of the da Vinci system. Peripheral cardiopulmonary bypass, transthoracic aortic cross-clamping and antegrade cardioplegia were used in all cases. A minithoracotomy in the fourth intercostal space and 2 ports in the third and fifth intercostal spaces allowed surgical access. All mitral valve valvuloplasties and band annuloplasties were done endoscopically with robotic assistance. RESULTS: Nine of 10 patients had successful valve repair, and 1 had conversion to mitral valve replacement due to persistent regurgitation. There were no deaths, strokes or need for sternotomy. One patient required re-exploration for bleeding. CONCLUSION: Minimally invasive RAMV repair is feasible and safe with promising early postoperative results when performed by experienced surgical personnel accomplished in both mitral valve procedures and robotic techniques.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".